Hindawi Publishing CorporationEvidence-Based Complementary and Alternative MedicineVolume 2013 Article ID 360371 12 pageshttpdxdoiorg1011552013360371
Research ArticleSpatially Nonlinear Interdependence of Alpha-OscillatoryNeural Networks under Chan Meditation
Pei-Chen Lo1 and Chih-Hao Chang2
1 Department of Electrical Engineering Institute of Electrical and Control Engineering National Chiao Tung UniversityHsinchu 30010 Taiwan
2 Institute of Electrical and Control Engineering National Chiao Tung University Hsinchu 30010 Taiwan
Correspondence should be addressed to Pei-Chen Lo pclofacultynctuedutw
Received 9 June 2013 Revised 12 October 2013 Accepted 13 November 2013
Academic Editor Hector Tsang
Copyright copy 2013 P-C Lo and C-H Chang This is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work is properlycited
This paper reports the results of our investigation of the effects of Chan meditation on brain electrophysiological behaviorsfrom the viewpoint of spatially nonlinear interdependence among regional neural networks Particular emphasis is laid on thealpha-dominated EEG (electroencephalograph) Continuous-time wavelet transform was adopted to detect the epochs containingsubstantial alpha activities Nonlinear interdependence quantified by similarity index S(X|Y) the influence of source signal Y onsink signal X was applied to the nonlinear dynamical model in phase space reconstructed from multichannel EEG Experimentalgroup involved ten experienced Chan-Meditation practitioners while control group included ten healthy subjects within the sameage range yet without any meditation experience Nonlinear interdependence among various cortical regions was explored forfive local neural-network regions frontal posterior right-temporal left-temporal and central regions In the experimental groupthe inter-regional interaction was evaluated for the brain dynamics under three different stages at rest (stage R pre-meditationbackground recording) in Chan meditation (stage M) and the unique Chakra-focusing practice (stage C) Experimental groupexhibits stronger interactions among various local neural networks at stagesMandC comparedwith those at stage RThe intergroupcomparison demonstrates that Chan-meditation brain possesses better cortical inter-regional interactions than the resting brain ofcontrol group
1 Introduction
For several decades scientific exploration has corroboratedthe effectiveness of meditation practice on health promotionParticular evidence includes the improvement of cardiovas-cular functions immunity and hormone-level regulation Inaddition meditation makes positive changes in the brainand mind including the positive emotional states betterstress manipulation enhanced mindful attention noticeableanxiety reduction and depression relief [1ndash7]
During the past decades a number of meditation tech-niques have been developed and practiced all over the worldAlthough with somewhat different practicing scheme almostall the practices are aimed to better manipulate the mindbrain function and physical state of practitioners throughmindfulness concentration and respiratory regulation For
many centuries eastern religious and secular groups suchas the Buddhists Taoist traditionalists and the Indian Yogishave been practicing meditation in order to achieve certainphysical mental and spiritual realm Meditation is a uniquestate of transcendental consciousness beyond the normalmind and mental process Meditation may induce a series ofintegrated physiological changes Among the diverse typesof meditation most practitioners are able to experiencecomplete relaxation and the so-called tranquil awareness
Although individuals in the East have been practicingvarious forms of meditation throughout history scientificstudy of meditation did not begin until it became popular inthe West In recent years meditation having been extendedto complementary medical practices further motivated sci-entific studies with the focus of physiological alterationsinduced by the process [8 9] Increasing reports ofmeditation
2 Evidence-Based Complementary and Alternative Medicine
benefits further draw attention of researchers to the assess-ment of meditation in different indications The research forphysical and psychological correlation ofmeditation has beenconcentrated mostly on Yoga and transcendental meditation(TM) from India Japanese Zen and Tibetan Buddhism[10 11] Up to the present little has yet been disclosedregarding the phenomena of Chan-Buddhist meditation (orsimply ldquoChan meditationrdquo) In the past decade orthodoxChan meditation as an unconventional therapy has provedto be efficacious for many chronic diseases infections andeven some malignant tumors Consequently more peoplebegan to practice orthodox Chan meditation in TaiwanAccumulation of the effective evidences and health benefitsof Chanmeditation aroused our attention to the physiologicalinvestigation on the Chan-Buddhist disciples
Since meditation process involves different states ofmental activities and consciousness EEG (electroencephalo-graph) thus became ourmajor focus for exploring the humanlife system under Chan meditation EEG applications inclinic and medical centers have become favorable since the1970s because of its advantages of economy safety andconvenience Most of all more scientific evidences of EEGvariations have been disclosed in a number of differentphysiological pathological conscious and mental states inaccordance with the various temporal spectral and spectralEEG characteristics Although with the rapid progress insophisticated medical imaging technologies EEG still playsan important and irreplaceable role in long-term monitor-ing of brain functions exhibited as the lump variations ofelectrical activities New findings have been continuouslyobserved and reported [12ndash15] As normally characterizedby frequency the EEG patterns are conveniently classifiedinto five frequency ranges including delta (Δ below 4Hz)theta (120579 4ndash8Hz) alpha (120572 8ndash13Hz) beta (120573 13ndash30Hz)and gamma (120574 30ndash70Hz) Earlier paper [16] based onEEG spectral power and coherence estimates reported thebrain regions involved in meditative states as the selectiveassociations of theta and alpha oscillating networks activitywith states of internalized attention and positive emotionalexperience According to our preliminary results differen-tiation in frontaloccipital alpha activities plays a key rolein comparing EEG between Chan-meditation practitioners(Appendix) and normal healthy non-meditating subjects
To explore the spatial interactions among brain localneural networks under alpha-rhythmic oscillation methodsdeveloped in nonlinear dynamical theory become moreversatile and favorable [17 18] The interactions amongseparate brain regions play a significant role in understandingthe neurophysiological behavior of human brain Accord-ingly multivariate time series analysis based on nonlineardynamical modeling becomes much appealing to investigatethe important mechanism by which specialized cortical andsubcortical regions integrate their activities into differentfunctions and different spatial scales [19ndash23] In recentstudies brain dynamics can be conceived as a large ensembleof coupled nonlinear dynamical subsystemsWe have focusedon investigating the nonlinear chaotic characteristics ofChan-meditation EEG during the past decade based onnonlinear deterministic modeling of brain dynamics [14
24] Significant nonlinear synchronization has been detectedbetween the macroscopic scale of EEG channels Thus vari-ous types of synchronization based on the concepts of nonlin-ear dynamical systems theory have previously been proposedas a more powerful mechanism than narrow band frequencysynchronization (eg coherence function) for achieving inte-grative neural processing This type of ldquononlinear couplingrdquoallows studying nonlinear interdependence between multi-channel recording sites and represents an alternative to thecoherence function which addresses all of these limitationssimultaneously [24ndash32] As a consequence this study aims toprobe into the 120572-wave nonlinear interdependence behaviorsamong multichannel electroencephalograph (EEG) signalscollected from the orthodox Chan-Buddhist practitioners(experimental group) and normal healthy subjects (controlgroup)
2 Material and Methods
21 Voluntary Subjects and Procedures This study involvedtwo groups of subjects the experimental group including 10volunteers with an average of 58-year Heart-Sealing Chan-meditation experience and the control group including 10volunteers without any meditation experience Seven menand three women were in either group In the experimentalgroup the average age was 28 years while in the controlgroup the average age was 23 years Heart-Sealing Chan-meditation practitioners participated in one 90-minute groupmeditation session every week and practiced approximately30-minute individual meditation on a daily basis Heart-Sealing Chan meditation has been the only orthodox wayof inheriting the lineage of Chan sect The core essenceof orthodox Chan-meditation practice is to transcend thephysiological (fifth) mental (sixth) subconscious (seventh)and Alaya (eighth) states of consciousness and finally attainthe realm of true self characterized by the pure golden lightwith eternal wisdom (Appendix) All the consciousness-transcending preprocesses inside can be completed for a wellexperienced orthodoxChan-meditation practitionerwho hasbeen able to spontaneously activate ten Chakras in ourbody [33] These ten Chakras are important energy spots foraltering states of consciousness by converting our physicallyand mentally dominant characteristics to a particular stateof detachment Accordingly novice practitioners put lotsof effort into the practice from Chakra focusing Chakraperception up to Chakra sealing In the beginning stageof Chakra focusing practitioners may practice the specialbrain-drilling technique to reduce all the wandering thoughtsabiding in the brain The brain-drilling technique involvesfirstly focusing alternately on frontal and posterior regionsof the brain with mindfulness attention and next focusingalternately on left and right regions and perceiving theinterconnections between two regions
In the experiment we conducted overall 50-minuterecording of EEG signals for both groups The EEG signalswere recorded by the 30-channel common-reference (linked-mastoid MS1-MS2) electrode montage based on the interna-tional 10ndash20 system Figure 1 illustrates the EEG recordingmontage of the 30 electrode locations The protocol designed
Evidence-Based Complementary and Alternative Medicine 3
FP1 FP2
F7 F3 Fz F4 F8
FT7 FC3 FCz FC4 FT8
T7 C3 Cz C4 T8
TP7 CP3 CPz CP4 TP8
P7 P3 Pz P4 P8
O1 Oz O2
Figure 1 EEG electrode locations of the 30-channel recordingmontage
for the experimental group involved three sessions 5-minute premeditation relaxation (stage R) 40-minute Chan-meditation practice (stageM) and 5-minute Chakra focusing(stage C) In stage C practitioners focused their mind andperception on a particular chakra named Chan Chakra (thethird ventricle inside the brain as illustrated in Appendix)No particular intervention was applied to the control groupduring the 50-minute EEG recording The control subjectsonly sat in a relaxing position with eyes being closed yet inthe awake state
22 Signal Acquisition and Preprocessing The EEG signalswere originally sampled at 1000Hz after being filtered by theanalog instrumentational band-pass filter with a passbandof 05ndash50Hz The band-pass filter setting was selected toeliminate the 60Hz interference by the power lines A highsampling rate of 1000Hz was adopted to preserve the wave-form quality of gamma rhythms (gt25Hz) often observed inChan-meditation EEG that had been investigated in the otherstudy of our research group In this study we downsampledthe EEG with a sampling rate of 200Hz since the majorfocus of this study is the alpha-dominated EEG epochs Thesegments contaminated by such artifacts as eye blinkingeyeball movement and muscle activities were prescreened inthe preprocessing stage
Wavelet decomposition provides an effective tool toextract the particular EEG rhythm of interest [34ndash36] Inaddition wavelet transform (WT) possesses such appealingproperties as time-frequency localization and multirate fil-tering Specific EEG rhythmmay be extracted by dedicatedlydesigning the WT parameters Wavelet transform can beimplemented either in continuous configuration (CWT) orin discrete form (DWT) Due to the problem of extremelynarrow-band EEG rhythmic pattern CWT (continuous-time
wavelet transform) was implemented in our study to reliablylocalize the correct spectral components of alpha rhythm
In CWT the signal to be analyzed is matched andconvolved with the continuous wavelet basis function withthe continuous time and frequency The original signal isexpressed as a weighted sum of the continuous basis waveletfunction digitized by the sampling rate of the correspondingscale The basis for wavelet transform is called the motherwavelet prototypeWavelet functions are families of functionssatisfying prescribed conditions such as continuity zero-mean amplitude and finite or near finite duration Somecategories of wavelet functions may involve such propertieslike orthogonality and biorthogonality regularity and soforth [35ndash37]
Mother wavelet prototype needs to be appropriatelyselected according to the properties of the particular signalunder investigationAdeli et al [38] successfully captured andlocalized the 3Hz spike andwave complex in the epileptiformEEG by applying wavelet decomposition with Daubechieswavelets Our previous study has corroborated the feasibilityof adopting Daubechies 6 (DB6) wavelet as the motherwavelet in EEG rhythmic analysis [37]
The family of Daubechies wavelets is known for itsorthogonal property and efficient implementation Thelower-order Daubechies wavelets are too coarse to properlyrepresent EEG sharp transients The higher-order ones withextra oscillations are beyond the requirements for analyz-ing the low-frequency EEG rhythms Particularly order 6Daubechies wavelet becomes most appealing in our studybecause its waveform pattern appears to mimic the neuronalaction potentials
23 Nonlinear Interdependence Measure The scheme forevaluating the nonlinear interdependence was based on themodified algorithm employed in computing the similarityindex S(X|Y) [24] Major tasks involved in the algorithm arereconstruction of the 119898-dimensional phase-space trajectoryand computation of the average cloud radius centered at agiven state point
231 Reconstruction of 119898-Dimensional Trajectory Considerthe brain as a nonlinear dynamical system The nonlinearinteractions of the local neuronal networks can be assessed bythe analysis of the collective dynamics underlying EEG timeseries simultaneously recorded from different brain regionsThe first step is to reconstruct the multidimensional phase-space portrait of the system dynamics X and Y respectivelyfrom EEG time series 119909[119894] and 119910[119894] According to the Takensembedding theory [39] a smooth map from the EEG timeseries 119909[119894] | 119894 = 1 119873+(119898minus1)120591 to the phase-space trajec-tory X = 119883
preserves some important topological invariants of the orig-inal system The reconstruction assumes a total number of119873 system-state points in the 119898-dimensional phase-spacetrajectory utilizing a rational time delay 120591 (in sample point)[40 41]The dimension119898 indicates the number of degrees offreedom of the nonlinear system and accordingly reflects thecomplexity of the system dynamics
4 Evidence-Based Complementary and Alternative Medicine
232 Computation of the Average Cloud Radius Considera state point 119883
119894on the 119898-dimensional phase trajectory As
illustrated in Figure 2 a119870NNhypersphere formed by the119870rsquosnearest neighboring (119870NN) points ofX
119894 is a cloud composed
of 119870119898-dimensional neighboring points around 119883119894 Let 119903
119894119895
and 119904119894119895 119895 = 1 119870 denote the time indices of the 119870NN
points of119883119894and119884119894 respectivelyThen the set of state points in
the 119870NN hypersphere centered at 119883119894is 119883119903119894119895
| 119895 = 1 119870The average square Euclidean distance from 119883
119894to its 119870NN
neighbors (or the average square radius of the cloud centeredat119883119894) is defined as
Then for two strongly synchronized systems both self andmutual neighborsmostly coincide so that119877(119870)
119894(119883) asymp 119877
(119870)
119894(119883 |
119884) ≪ 119877119894(119883) whereas for independent systems mutual
neighbors aremore scattered that leads to119877(119870)119894(Χ) ≪ 119877
(119870)
119894(Χ |
119884) asymp 119877119894(119883) Accordingly the degree of interdependence
of these two systems is reflected by the similarities (ordissimilarities) between these two cloud patterns formed byself andmutual neighborsThe strength of similarity betweenthese two point clouds is termed as similarity index 119878 [24 37]and is defined as follows
119878(119870)
(119883 | 119884) =1
119873
119873
sum119894=1
119877(119870)
119894(119883)
119877(119870)
119894(119883 | 119884)
(4)
119878(119870)(119883 | 119884) assesses the statistical dependence of the
state-space structure ofX on that ofY in the sense of testifyingwhether closeness in X implies closeness in Y and vice versaTwo identical systems with the same sets of self and mutualneighbors result in the maximum similarity index (119878 =
1) whereas the index is close to zero (119878 asymp 0) for com-pletely independent systems The opposite interdependence(119878(119870)(119884 | 119883)) can be computed analogically Notice that
similarity indexes are in general asymmetric that is 119878(119870)(119884 |
119883) = 119878(119870)(119883 | 119884) 119878(119870)(119883 | 119884) evaluates the effect of system Y
on system X From the point of view of the system theory
signal Y is regarded as the source or the active role in theinteraction while signal X plays a passive role (a sink) Onthe other hand 119878(119870)(119884 | 119883) analysis considers Y as the sinkthat plays the passive role [24 37]
The asymmetry of 119878 is one of the main advantagesover the other nonlinear measures such as the mutualinformation and the phase synchronizations The fact that119878 is asymmetric allows us to study not only topographicpatterns but also functional properties By considering eachEEG electrode either as a sink or as a source in the nonlinear-interdependence interaction we may thereby further explorethe brain functional topological profile and the direction ofinteraction among local neuronal networks [19] For examplethe condition of 119878(119884 | 119883) gt 119878(119883 | 119884) indicates thatY depends more on X than vice versa In other words Xhas a greater influence on Y than vice versa In such acase X is said to be more active and Y is more passive Byconsidering each electrode either as a sink or as a source inthe nonlinear dynamical interaction we may thereby explorethe spatial direction of the interaction and the dominance oflocal neuronal networks under Chan meditation [42]
In order to maximize the sensitivity to the underlyingsynchronization and gain the robustness against noise weproposed a modified version of 119878measure with an adjustablerange of 119870NN Following our previous study of dimensionalcomplexity index [27 28] a reliable estimate of dimen-sional complexity of a system was obtained by averagingthe complexity indexes over a moderate range of 119870rsquos Asmall 119870 causes superimposed noise while a large 119870 resultsin a measurement involving multimodal effects [27] Todetermine a robust measure against noise it follows that thefinal estimate of nonlinear interdependence is the average119878(119870)(119883 | 119884) over an appropriate range of 119870rsquos and is denoted
by 119878(119883 | 119884)In the practical implementation previous studies of
dimensional complexity for meditation EEG have establisheda moderate choice of parameters The time delay 120591 can bedetermined by the first zero-crossing of the correspondingautocorrelation function Embedding dimension 119898 can bedetermined by the convergent estimate of dimensionalityThewindow length 119873 is selected to encompass the stabilizationof dynamical behavior in the phase space in the sense ofthe convergent estimate of quantitative nonlinear dynami-cal property of reconstructed EEG trajectory for examplecorrelation dimension As a consequence the implementingparameters were selected to be 120591 = 5 (sample points)119898 = 10andwindow length119873 = 1 000 sample points (5 seconds) thatensure convergent and reliable estimates [24 27 28]The finalestimate 119878(119883 | 119884) was obtained by averaging the 119878(119870)(119883 | 119884)
for119870 ranging from 20 to 35
233 Outline of the Scheme The entire scheme employed inthis study is illustrated in Figure 3 that integrates differenttheories and methods to evaluate the nonlinear interdepen-dence for multichannel EEG
To investigate the nonlinear-interdependent behaviorsof alpha activities CWT is employed to identify alpha-dominated epochs in the entire EEG record AnEEG segment
Evidence-Based Complementary and Alternative Medicine 5
X
1 2
3
4
567
8 9
1011
1213
14
15
16
17
18
19
20
2122
r2j = 1 3 4 5 6 7 15 16 17 18
(a)
Y
12
34
5
6
7
8
9
10
11
12
13
1415
1617
18
19
20
21
22
(b)
X
1 2
3
4
56
7
8 9
10
11
12
13
14
15
16
17
18
19
20
2122
(c)
Y
1
2
34
5
6
7
8
9
10
11
12
13
14
15
1617
18
19
20
21
22
s2j = 1 3 5 11 12 13 14 15 21 22
(d)
Figure 2 Illustration for (a) self neighbors 1198831199032119895
( ⃝) (b) state points in 119884 and (c) mutual neighbors 1198831199042119895
() where the indexes 1199042119895
aredetermined from the indexes of (d)119870NN of 119884
Figure 3 Scheme for evaluating nonlinear interdependence ofmultichannel EEG
is identified to be alpha dominant if the percentage of120572 powerto the total power is at least 50 in more than 15 channels(one half of the total channels) Figure 4 displays the resultsof interpreting the 5-second EEG recorded from channels OzCz and Fz The alpha-power percentage (denoted as 120588) foreach one-second epoch is listed beneath the EEG tracingThe5-second EEG tracing is plotted with the amplitude rangingfrom minus50120583V to 50120583V Parameter 120588 evaluated for differentchannels may reflect the focalized behavior of alpha activity
To extend the capacity of assessing the neural-networkinteraction the source119883
119895can be generalized as an integrated
local network involving 119871 active electrode sites so that 119878119901(119883119894)
becomes the average of 119871rsquos 119878(119883119894| 119883119895) assuming119883
119895= 119883119894
119878119901(119883119894) =
1
119871sum119895
119878 (119883119894| 119883119895) (5)
Equation (5) then evaluates the integrative effects of 119871 activeelectrodes on119883
119894 On the other hand the influence of an active
6 Evidence-Based Complementary and Alternative Medicine
50
0
minus500 05 1 15 2 25 3 35 4 45 5
Time (s)120588 58 59 52 55 60
(a) Oz
50
0
minus500 05 1 15 2 25 3 35 4 45 5
Time (s)120588 56 60 50 51 60
(b) Cz
50
0
minus500 05 1 15 2 25 3 35 4 45 5
Time (s)120588 62 61 51 59 60
(c) Fz
Figure 4 Percentage of alpha power to total power for each one-second epoch of the five-second EEG segments (amplitude in 120583V)recorded from (a) Oz (b) Cz and (c) Fz
electrode119883119895on the integrative neural network encompassed
by 119871 passive electrodes (119883119894) can be evaluated by
119878119886(119883119895) =
1
119871sum119894
119878 (119883119894| 119883119895) (6)
assuming119883119894= 119883119895 Both 119878
119901(119883119894) and 119878
119886(119883119895) are called regional
interdependence index (RII)In Chan-meditation practice practitioners often focus on
five regions alternately frontal posterior left right and cen-tral regions after activating the Chan Chakra inside the thirdventricle The purpose is to eliminate the stream of jumbledthoughts and produce a tranquil mind To investigate theeffect of such regional focusing we accordingly divided 30EEG recording sites into five regions
frontal (F) Fp1 Fp2 F7 F3 Fz F4 and F8posterior (P Parietal + Occipital) O1 Oz O2 P7 P3Pz P4 and P8central (C) FCz Cz and CPzleft Temporal (LT) FC3 FT7 T7 C3 TP7 and CP3right Temporal (RT) FC4 FT8 T8C4 TP8 andCP4
3 Results and Discussion
31 Interdependence Matrix of Chan-Meditation EEG Con-sider a given source signal Y The influence of source signalY on sink signal X 119878(X | Y) can be expressed as a 30 times
30 interdependence matrix with the element 119878119894119895= 119878(119883
119894| 119884119895)
denoting the coupling strength of interaction of the source119884119895affecting the sink 119883
119894 The similarity index (SI) was
calculated for 870 (30 times 29) electrode pairs As displayed inFigure 5(a) the color image encoded the quantities in the 30times 30 interdependence matrix S The right-side color chartencodes the strength level of 119878
119894119895 from blue to red indicating
the range of 119878 from the smallest to the largest value EEGchannels are in the order of (from topleft) O2 Oz O1 P7P3 Pz P4 P8 TP8 CP4 CPz CP3 TP7 T7 C3 Cz C4 T8FT8 FC4 FCz FC3 FT7 F7 F3 Fz F4 F8 Fp2 and Fp1 Forexample the box at the lower-left corner characterizes theeffect of O2 channel on Fp1 channel as denoted by 119878(Fp1 |
O2) Accordingly the first row reveals the effect of sourceO2Oz and Fp1 respectively on sink O2 On the other handthe first column indicates how source O2 affects sink O2 Oz and Fp1 respectivelyThe dark red along the diagonal lineindicates the highest similarity index 119878 = 1 when the sourceand sink signals are identical
This figure exhibits some typical behavior in the 119878matrixthat is stronger interdependence occurs in the pairs ofnearby EEG channels On the other hand weaker interactionis measured as two channels are much apart Moreoverbox (119894 119895) does not equal its transposed partner box (119895 119894)indicating the asymmetry of 119878 matrix Figures 5(b)ndash5(d)display the top viewof brain topographicmapping of 119878
119886(FP1)
119878119886(FP2) and 119878
119886(Oz) extracted respectively from the 30th
29th and 2nd columns of Figure 5(a) The topographicmapping was plotted by the function topoplotm providedby EEGLab The mappings exhibit the efficacy of the givenchannel acting as the source role The results in Figures 5(b)to 5(d) reveal the right-frontal dominance The occipitalchannels are comparably less active with respect to the frontalneuronal networks Such weaker influence of occipital andposterior regions on the other regions can be clearly observedfrom the blue color dominating in the left three columns of Smatrix (Figure 5(a)) corresponding to the source at O2 Ozand O1
32 Inter-Region Interdependence AnalysismdashExperimentalGroup Inter-regional nonlinear interdependence was ana-lyzed for EEG recorded in three different sessions (stage RM and C) Due to the premeditation brain-drilling practicedescribed in previous section we particularly focused onthe left-right temporal (LT-RT) and frontal-posterior (F-P)neural-network interactions For example 119878(F rarr P) iscomputed by averaging all 119878
119886(119883119895) in (6) for all 119883
119895isin F and
119883119894isin P to assess the integrative source effect of all electrodes
in frontal region driving the posterior region On the otherhand 119878(P rarr F) is computed by averaging all 119878
119886(119883119895) in
(6) for all 119883119895isin P and 119883
119894isin F when all the electrodes in
the posterior region play the source role to drive the frontalregion
Table 1 lists the group averages and standard deviationsof 119878(F rarr P) 119878(P rarr F) 119878(LT rarr RT) and 119878(RT rarr
LT) at three experimental stages (R M and C) Evidently119878(F rarr P) is consistently greater than 119878(P rarr F) for all threestages The 119875 values (00055 00031 and 00302) of pairedsample 119905-test are all smaller than 005 that demonstrates the
Evidence-Based Complementary and Alternative Medicine 7
Figure 5 SI analysis for experienced practitioner during Chanmeditation (StageM) (a) 30 times 30 Smatrix and brain topographical mappings(top view) of (b) 119878
119886(FP1) (c) 119878
119886(FP2) and (d) 119878
119886(Oz) indicating the average driving strength of the EEG sites FP1 FP2 and Oz
070
065
060
055
050
045
040
Source
Stage RStage MStage C
F P C LT RT
(a)
Sink070
065
060
055
050
045
040
Stage RStage MStage C
F P C LT RT
(b)
Figure 6 Average effectiveness of each region playing the role of a source (a) and sink (b) Three bars in each RII cluster correspond to threeexperimental stages
statistical significance of frontal-alpha dominance at all threestages On the other hand results of the left-right temporalanalysis of nonlinear interdependence reveal no distinctlydominant role of the laterally neural-network operation thatis 119878(LT rarr RT) asymp 119878(RT rarr LT) The higher 119875 values forthe 119878(LT rarr RT)-119878(RT rarr LT) paired 119905-test indicate nostatistically significant difference between two sets of resultsWe may further infer the balancing operations between theleft-brain and right-brain hemispheres
Our results demonstrate that interactions between leftand right hemispheres are much more intensive than theinteractions between frontal and posterior regions with 119875 =
00016 considering all the experimental subjects at all threestages
Figure 6 provides an alternative viewpoint for exploringhow a given region of interest ROI (F P C LT or RT)influences or is influenced by the other regions In Figure 6left (right) group of five 3-bar clusters corresponds to theaverage effectiveness of each region playing the active (pas-sive) role at three stages For example the leftmost barindicates the average of 119878(F rarr P) 119878(F rarr LT) 119878(F rarr
RT) and 119878(F rarr C) for stage R while the rightmostbar indicates the average of 119878(F rarr RT) 119878(P rarr RT)119878(C rarr RT) and 119878(LT rarr RT) for stage C Among allfive regions posterior region as either the source or sinkapparently exhibits the weakest link to the other regions Inaddition the effectiveness of active role of posterior regionis weaker than that of passive role The results strongly
8 Evidence-Based Complementary and Alternative Medicine
Table 1 Group averages and standard deviations of 119878(FrarrP) 119878(Prarr F) 119878(LTrarrRT) and 119878(RTrarr LT) at three experimental stages (R Mand C) including the 119875 values of student 119905-test for 119878(FrarrP)-119878(Prarr F) and 119878(LTrarrRT)-119878(RTrarr LT) pairs
Group average 056 051 060 061Group std 005 005 007 005119875 value 00055 03476
MGroup average 056 050 060 061Group std 003 006 006 004119875 value 00031 01987
CGroup average 055 049 061 061Group std 007 006 006 006119875 value 00302 03953
suggest the inactive behaviors of parietal-occipital lobes sinceregion P encompasses the EEG-electrode sites of parietal andoccipital lobesThe parietal lobe is responsible for integratingsensory information from various parts of the body withthe particular functions of determining spatial sense andnavigation Functions of occipital lobe mainly include visualreception visual-spatial processing and color recognitionAs described previously the core essence of orthodox Chan-meditation practice is to transcend physiological mental andall states of consciousness to prove the existence of true beingThe inactive posterior regions may provide the evidence ofbrain rewiring in preparation for such transcendence
Region C encompasses three midline electrodes locatingfrom precentral to postcentral cortex Region C as the sourceapparently dominates over the other four regions regardlessof the stages On the other hand region C as the passive role isaffected mostly among the five regions Region C constantlyexhibits the largest RII at all stages
Wemay draw a tentative hypothesis from the mechanismof Chan-meditation practice Practitioners are required tokeep Chan Chakra active at any moment that results inthe formation of an energy pathway between Chan Chakraand Qian-Ding acupoint on scalp (Figure 10(b)) Does suchphysiological reformation correlate to the significant effec-tiveness of region C It leaves an open question for futureinvestigation
RII characterizing the regional interdependence behavesdifferently for each region when the experimental subjectsswitch their mental states from R (resting) to M (medita-tion) or from R to C (Chakra focusing) To investigate theeffect of different experimental sessions the RII percentageincreasedecrease from stage R to M and from stage R to Cwere computed for each of the five regions (F P C LT andRT)acting as either the active or the passive role In comparisonof RII between stage M and stage R the percentage largerthan 1 was observed in the regions of LTactive(minus124)RTactive (125) and Cpassive (minus107) On the other handthe regions of significant change in RII when comparingstage C with R include Factive (minus184) Pactive (minus178) andCactive (239) On the basis of RII of stage R for each
individual region we summarize the changes of RII at stagesM and C as follows
(1) In the active-role analysis region LT becomes moredeactivated at stage M while region RT becomesmore activatedWhenmeditation subjects focused onChan Chakra the active driving strength of regionC increases significantly (239) On the other handsuppression of the source activity occurs to bothregions F and P (the regions anterior to and posteriorto region C)
(2) In the passive-role analysis only region C becomesnotably deactivated at stage M (free meditation) Ingeneral differences are trivial in comparison of119877119868119868passive between stages M and R
(3) Chan meditation deactivates the left brain hemi-sphere whereas it inactivates the right brain hemi-sphere
Except for region P the active-role effectiveness of a givenregion is better than its passive-role effectiveness
33 Inter-Region Interdependence AnalysismdashControl GroupIn control group the group average and standard deviationof 119878(F rarr P) 119878(P rarr F) 119878(LT rarr RT) and 119878(RT rarr LT) atstage R are respectively 055 plusmn 004 051 plusmn 004 059 plusmn 003and 058 plusmn 004 The 119875 values of student 119905-test for 119878(F rarr
P)-119878(P rarr F) and 119878(LT rarr RT)-119878(RT rarr LT) pairs are0002 and 0457The results also reveal the frontal dominanceand left-right lateral balance for the control group at rest Yetcompared with the Chan-meditation practitioners controlgroup exhibits weaker strength of effectiveness no matter ifthe region plays an active or a passive role
To explore the average effectiveness of a given ROI weaveraged the RIIs for the region in connection with the otherfour regions Figure 7 displays how a given ROI (F P C LT orRT) influences (active) or is influenced (passive) by the otherregions Similar to the results of experimental group regionP as either the active or passive role exhibits the weakest linksto the other regions
Evidence-Based Complementary and Alternative Medicine 9
Sink
Source
070
065
060
055
050
045
040F P C LT RT
Figure 7 Average effectiveness of each region playing either theactive or passive role
Comparing the efficacy of two counteractive roles playedby the same region we observe that the source-role effective-ness of a given ROI is higher than its sink-role effectivenessexcept region P
34 Comparison between Experimental and Control GroupsFigure 8 illustrates the group averages of RIIs including119878(F rarr P) 119878(P rarr F) 119878(LT rarr RT) and 119878(RT rarr LT)for the experimental group at three stages (R M and C)and for the control group at rest Experimental group revealsmuch more intensive lateral (LT larrrarr RT) interactions thancontrol group The differences are statistically significant forexperimental group at stage M (119875 = 00336) and at stage C(119875 = 00411) On the other hand region P responsible forspatial sense and navigation becomes comparatively inactivefor Chan-meditation practitioners at stage C
The assembling illustration in Figure 9 is used to comparethe average effectiveness of each region between two groupsExperimental group playing either a source role or a sinkrole apparently exhibits higher average effectiveness in allfive regions The extraordinarily large RIIs for region Cparticularly acting the source role may be assumed to becorrelated with the strengthening of neural networks ofregion C dominating over the other regions through thespiritual focusing on Chan Chakra According to the post-experimental interview with Chan-meditation practitionerssuch central (FCz-Cz-CPz) dominating behavior could belinked to theChan-Chakra activation that further induces theperception of grand solemn energy flow in and out throughthe cortical regions defined by acupoints DU20 (Baihui)DU21 (Qianding) and DU22 (Xinhui) in TCM (traditionalChinese Medicine) Figure 10(b) (Appendix) illustrates thelocations of these three acupoints
4 Conclusion
The time-transcending nonmaterial sacred spiritual experi-ences of Chan-meditation practitioners bring our attention tothe study of the unique interactions among regional neuralnetworks in the brain Scientific approach to the scope of
Exp (stage R)Exp (stage M)
Exp (stage C)Control
065
060
055
050
045F rarr P P rarr F LT rarr RT RT rarr LT
Figure 8 Group averages of RIIs (119878(F rarr P) 119878(P rarr F) 119878(LT rarr
RT) and 119878(RT rarr LT)) for experimental group at three stages andfor control group at rest
Chan meditation provides insight into the mechanism inaddition to the vague sketch of meditation sensation and itsmultiform benefits to human beings This paper presents ourpreliminary results based on nonlinear dynamical theory ofexploring the spatial interactions among brain local neuralnetworks under alpha-rhythmic oscillationQuantification ofnonlinear interdependence based on similarity index revealssignificant intergroup difference Significant higher lateralinteractions between left and right temporal regions wereobserved in Chan-meditation practitioners at the stages ofChan meditation and Chakra-focusing practice In Chanpractice practitioners follow the doctrine that the mind canbe enlightened only if it surrenders its leadership power tothe ldquoheartrdquo (Bodhi the true self with eternal wisdom) Theyaccordingly can experience better balance and integrationof the brain hemispheres through years of Chan-meditationpractice
Chan-Chakra spiritual focusing (at stage C) remarkablystrengthens the central neural-network dominance over theother regions On the other hand suppression of the sourceactivity in regions F and P at stage C appears to reveal themeditation state of transcending the realm of physical bodyand mind The particular central (FCz-Cz-CPz) dominatingphenomenon is reflected in long-term Chan practitioners asone of the metamorphosing processes that opens the energypathway between Chan Chakra and the central-line scalpfrom acupoint DU20 to DU22 (Figure 10(b) in Appendix)In the case practitioners experience tranquil brain and calmmind in every moment Chan-meditation practice is to real-ize a Chan-style brain and Chan-style physical body insteadof merely sitting still for one hour to pursue temporary peaceof mind and relief of body
Appendix
Chan meditation originating more than 2500 years ago hasbeen proved to benefit the health while on the way toward theultimate Buddhahood state Buddha Shakyamuni disclosedthe eternal truth the supreme wisdom the noumenal energy
10 Evidence-Based Complementary and Alternative Medicine
Source070
065
060
055
050
F P C LT RT
Exp (R)Exp (M)
Exp (C)Control
(a)
Sink070
065
060
055
050
F P C LT RT
Exp (R)Exp (M)
Exp (C)Control
(b)
Figure 9 Comparison of average effectiveness of each region as a source (a) or a sink (b) between experimental and control groups
Chan Chakra
(a)
DU20
DU21DU22
Anteriorhairline
Posteriorhairline
(b)
Figure 10 (a) Location of the Chan Chakra (inside the third ventricle) (b) Illustration of acupoints DU20 (Baihui) DU21 (Qianding) andDU22 (Xinhui) on DU meridian
and the natural powers of the universe in Chan meditationunder a linden tree The orthodox Chan Buddhism wasoriginated by such an exceptional affair that Buddha Shakya-muni transmitted this light of supreme wisdom to the GreatKashiyapa The same path towards perfect enlightenment(Buddhahood) was promulgated in mainland China in 527
by Bodhidharma the 28th patriarch The current patriarchis Chan master Wu Jue Miao Tian the 85th patriarch of theorthodox Chan-Buddhism Sect since the Great KashiyapaIn orthodox Chan-Buddhist practice very few disciples wereable to catch the quintessence since it cannot be taught inany form of lectures Written material and spoken words
Evidence-Based Complementary and Alternative Medicine 11
cannot promulgate the true wisdom of Chan which can onlybe conveyed by the Buddhist Heart-seal Imprint from a truemaster
In Chan meditation practitioners aim to attain the trueself (Buddha nature) with eternal wisdom (Bodhi) throughbody-mind-soul purification Substantially speaking suchpurification procedure involves the journal of transcendingthe physiological state (five sensory organs) themental activ-ities and normal consciousness the subliminal (the manas)consciousness and the Alaya state at which practitioners areable to perceive the sacred light emitted from Buddha natureBuddhist Heart-seal Imprint from the Chan Patriarch is amust to assist in the purification and accomplishment Toprepare for attaining such realm practitioners meditate withfull-lotus half-lotus or leg-crossing posture and sit still tocultivate spiritual Reiki for penetrating into the ten importantChakras In the course of Chan meditation practitionersmust switch their normal chest breathing to the Navel-Chakra breathing (also called ldquofetal breathingrdquo) that is thebreathing scheme for entering into deep meditation Amongthe ten Chakras Chan Chakra locating inside the thirdventricle is the Buddhist paradise implemented in our bodyFigure 10(a) illustrates the location of Chan Chakra
The cun-measurand system is normally used to measureand locate the acupoints To determine the locations ofacupoints DU20 DU21 and DU22 on Governor Vesselmeridian (DU meridian) we first measure the scalp-midlinelength between anterior hairline and posterior hairline thatis divided into 12 cuns The locations are defined as follows
DU20 7 cuns above the posterior hairline and 5 cunsabove the anterior hairlineDU21 35 cuns directly above the anterior hairline or15 cuns anterior to DU20DU22 2 cuns posterior to the anterior hairline or3 cuns anterior to DU20
Acknowledgments
The authors would like to thank Shung-Yu Yo for his assis-tance in data analysis Chan-meditation practitioners of theShakyamuni Buddhist Foundation are gratefully acknowl-edged for their enthusiastic participation in this research asvolunteers This research was supported by the grants fromthe National Science Council of Taiwan (Grant no NSC 100-2221-E-009-006-MY2)
References
[1] T YuH L Tsai andM LHwang ldquoSuppressing tumor progres-sion of in vitro prostate cancer cells by emitted psychosomaticpower through Zen meditationrdquo American Journal of ChineseMedicine vol 31 no 3 pp 499ndash507 2003
[2] K H Coker ldquoMeditation and prostate cancer integrating amindbody interventionwith traditional therapiesrdquo Seminars inUrologic Oncology vol 17 no 2 pp 111ndash118 1999
[3] D Lester ldquoZen and happinessrdquo Psychological Reports vol 84no 2 pp 650ndash651 1999
[4] C R K MacLean K G Walton S R Wenneberg et alldquoEffects of the transcendental meditation program on adaptivemechanisms changes in hormone levels and responses to stressafter 4 months of practicerdquo Psychoneuroendocrinology vol 22no 4 pp 277ndash295 1997
[5] GA Tooley SMArmstrong T RNorman andA Sali ldquoAcuteincreases in night-time plasma melatonin levels following aperiod of meditationrdquo Biological Psychology vol 53 no 1 pp69ndash78 2000
[6] Y-Y Tang Y Ma Y Fan et al ldquoCentral and autonomicnervous system interaction is altered by short-termmeditationrdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 106 no 22 pp 8865ndash8870 2009
[7] A Lutz H A Slagter N B Rawlings A D Francis LL Greischar and R J Davidson ldquoMental training enhancesattentional stability neural and behavioral evidencerdquo Journal ofNeuroscience vol 29 no 42 pp 13418ndash13427 2009
[8] S M Bertisch C C Wee R S Phillips and E P McCarthyldquoAlternative mind-body therapies used by adults with medicalconditionsrdquo Journal of Psychosomatic Research vol 66 no 6 pp511ndash519 2009
[9] W R Marchand ldquoMindfulness-based stress reductionmindfulness-based cognitive therapy and zen meditation fordepression anxiety pain and psychological distressrdquo Journalof Psychiatric Practice vol 18 no 4 pp 233ndash2252 2012
[10] B R Cahn and J Polich ldquoMeditation states and traits EEG ERPand neuroimaging studiesrdquoPsychological Bulletin vol 132 no 2pp 180ndash211 2006
[11] F Travis and J Shear ldquoFocused attention open monitoring andautomatic self-transcending categories to organize meditationsfrom Vedic Buddhist and Chinese traditionsrdquo Consciousnessand Cognition vol 19 no 4 pp 1110ndash1118 2010
[12] P-C Lo M-L Huang and K-M Chang ldquoEEG alpha blockingcorrelated with perception of inner light during Zen medita-tionrdquo American Journal of Chinese Medicine vol 31 no 4 pp629ndash642 2003
[13] H C Liao and P C Lo ldquoInvestigation on spatiotemporalcharacteristics of zen-meditation EEG rhythmsrdquo Journal ofInternational Society of Life Information Science vol 25 no 1pp 63ndash71 2007
[14] H-Y Huang and P-C Lo ldquoEEG dynamics of experienced zenmeditation practitioners probed by complexity index and spec-tral measurerdquo Journal of Medical Engineering and Technologyvol 33 no 4 pp 314ndash321 2009
[15] E K St Louis and E P Lansky ldquoMeditation and epilepsy a stillhung juryrdquoMedical Hypotheses vol 67 no 2 pp 247ndash250 2006
[16] L I Aftanas and S A Golocheikine ldquoHuman anterior andfrontal midline theta and lower alpha reflect emotionallypositive state and internalized attention high-resolution EEGinvestigation of meditationrdquo Neuroscience Letters vol 310 no1 pp 57ndash60 2001
[17] K Ansari-Asl J-J Bellanger F Bartolomei F Wendung andL Senhadji ldquoTime-frequency characterization of interdepen-dencies in nonstationary signals application to epileptic EEGrdquoIEEE Transactions on Biomedical Engineering vol 52 no 7 pp1218ndash1226 2005
[18] F Gans A Y Schumann J W Kantelhardt T Penzel and IFietze ldquoCross-modulated amplitudes and frequencies charac-terize interacting components in complex systemsrdquo PhysicalReview Letters vol 102 no 9 Article ID 098701 2009
12 Evidence-Based Complementary and Alternative Medicine
[19] J Bhattacharya H Petsche and E Pereda ldquoInterdependenciesin the spontaneous EEG while listening to musicrdquo InternationalJournal of Psychophysiology vol 42 no 3 pp 287ndash301 2001
[20] C J Stam ldquoNonlinear dynamical analysis of EEG and MEGreview of an emerging fieldrdquo Clinical Neurophysiology vol 116no 10 pp 2266ndash2301 2005
[21] W Singer ldquoConsciousness and the binding problemrdquo Annals ofthe New York Academy of Sciences vol 929 pp 123ndash146 2001
[22] D Calitoiu B J Oommen and D Nussbaum ldquoLarge-scaleneuro-modeling for understanding and explaining some brain-related chaotic behaviorrdquo Simulation-Transactions of the Societyfor Modeling and Simulation International vol 88 no 11 pp1316ndash1337 2012
[23] F Wendling K Ansari-Asl F Bartolomei and L SenhadjildquoFrom EEG signals to brain connectivity a model-based eval-uation of interdependence measuresrdquo Journal of NeuroscienceMethods vol 183 no 1 pp 9ndash18 2009
[24] H Y Huang and P C Lo ldquoEEG nonlinear interdependencemeasure of brain interactions under zen meditationrdquo Journalof Biomedical Engineering Research vol 29 no 4 pp 286ndash2942008
[25] M Breakspear and J R Terry ldquoDetection and description ofnon-linear interdependence in normal multichannel humanEEG datardquo Clinical Neurophysiology vol 113 no 5 pp 735ndash7532002
[26] M Breakspear and J R Terry ldquoTopographic organizationof nonlinear interdependence in multichannel human EEGrdquoNeuroImage vol 16 no 3 pp 822ndash835 2002
[27] C J Stam M Breakspear A-M van Cappellen van Walsumand B W van Dijk ldquoNonlinear synchronization in EEG andwhole-headMEG recordings of healthy subjectsrdquoHuman BrainMapping vol 19 no 2 pp 63ndash78 2003
[28] U Feldmann and J Bhattacharya ldquoPredictability improvementas an asymmetrical measure of interdependence in bivariatetime seriesrdquo International Journal of Bifurcation and Chaos vol14 no 2 pp 505ndash514 2004
[29] M Rubinov S A Knock C J Stam et al ldquoSmall-worldproperties of nonlinear brain activity in schizophreniardquoHumanBrain Mapping vol 30 no 2 pp 403ndash416 2009
[30] P Mirowski D Madhavan Y LeCun and R KuznieckyldquoClassification of patterns of EEG synchronization for seizurepredictionrdquo Clinical Neurophysiology vol 120 no 11 pp 1927ndash1940 2009
[31] S I Dimitriadis N A Laskaris Y del Rio-Portilla and G CKoudounis ldquoCharacterizing dynamic functional connectivityacross sleep stages from EEGrdquo Brain Topography vol 22 no 2pp 119ndash133 2009
[32] K Sibsambhu and R Aurobinda ldquoEffect of sleep deprivation onfunctional connectivity of EEG channelsrdquo IEEE Transcations onSystems Man and Cybernetics vol 43 no 3 pp 666ndash672 2013
[33] C M W J M Tian Chan Master Miao Tianrsquos Book of Wisdomand the Guide to Heart Chan Meditation Lulu 2010
[34] X-S Zhang R J Roy and E W Jensen ldquoEEG complexity as ameasure of depth of anesthesia for patientsrdquo IEEE Transactionson Biomedical Engineering vol 48 no 12 pp 1424ndash1433 2001
[35] I Daubechies Ten Lectures on Wavelets Society for Industrialand Applied Mathematics Philadelphia Pa USA 1992
[36] C Heil D F Walnut and I Daubechies Fundamental Papersin Wavelet Theory Princeton University Press Princeton NJUSA 2006
[37] C Y Liu and P C Lo ldquoSpatial focalization of zen-meditationbrain based on EEGrdquo Journal of Biomedical EngineeringResearch vol 29 pp 17ndash24 2008
[38] H Adeli Z Zhou and N Dadmehr ldquoAnalysis of EEG recordsin an epileptic patient using wavelet transformrdquo Journal ofNeuroscience Methods vol 123 no 1 pp 69ndash87 2003
[39] F Takens ldquoDetecting strange attractors in turbulencerdquo inDynamical Systems and Turbulence D A Rand and L S YoungEds vol 898 of Lecture Notes in Mathematics pp 366ndash381Springer New York NY USA 1981
[40] P-C Lo and W-P Chung ldquoAn approach to quantifying themulti-channel EEG spatial-temporal featurerdquo Biometrical Jour-nal vol 42 no 7 pp 901ndash916 2000
[41] W S Pritchard and D W Duke ldquoDimensional analysis of no-task human EEG using the Grassberger-Procaccia methodrdquoPsychophysiology vol 29 no 2 pp 182ndash192 1992
[42] R Q Quiroga A Kraskov T Kreuz and P GrassbergerldquoPerformance of different synchronization measures in realdata a case study on electroencephalographic signalsrdquo PhysicalReview E vol 65 no 4 Article ID 041903 14 pages 2002
2 Evidence-Based Complementary and Alternative Medicine
benefits further draw attention of researchers to the assess-ment of meditation in different indications The research forphysical and psychological correlation ofmeditation has beenconcentrated mostly on Yoga and transcendental meditation(TM) from India Japanese Zen and Tibetan Buddhism[10 11] Up to the present little has yet been disclosedregarding the phenomena of Chan-Buddhist meditation (orsimply ldquoChan meditationrdquo) In the past decade orthodoxChan meditation as an unconventional therapy has provedto be efficacious for many chronic diseases infections andeven some malignant tumors Consequently more peoplebegan to practice orthodox Chan meditation in TaiwanAccumulation of the effective evidences and health benefitsof Chanmeditation aroused our attention to the physiologicalinvestigation on the Chan-Buddhist disciples
Since meditation process involves different states ofmental activities and consciousness EEG (electroencephalo-graph) thus became ourmajor focus for exploring the humanlife system under Chan meditation EEG applications inclinic and medical centers have become favorable since the1970s because of its advantages of economy safety andconvenience Most of all more scientific evidences of EEGvariations have been disclosed in a number of differentphysiological pathological conscious and mental states inaccordance with the various temporal spectral and spectralEEG characteristics Although with the rapid progress insophisticated medical imaging technologies EEG still playsan important and irreplaceable role in long-term monitor-ing of brain functions exhibited as the lump variations ofelectrical activities New findings have been continuouslyobserved and reported [12ndash15] As normally characterizedby frequency the EEG patterns are conveniently classifiedinto five frequency ranges including delta (Δ below 4Hz)theta (120579 4ndash8Hz) alpha (120572 8ndash13Hz) beta (120573 13ndash30Hz)and gamma (120574 30ndash70Hz) Earlier paper [16] based onEEG spectral power and coherence estimates reported thebrain regions involved in meditative states as the selectiveassociations of theta and alpha oscillating networks activitywith states of internalized attention and positive emotionalexperience According to our preliminary results differen-tiation in frontaloccipital alpha activities plays a key rolein comparing EEG between Chan-meditation practitioners(Appendix) and normal healthy non-meditating subjects
To explore the spatial interactions among brain localneural networks under alpha-rhythmic oscillation methodsdeveloped in nonlinear dynamical theory become moreversatile and favorable [17 18] The interactions amongseparate brain regions play a significant role in understandingthe neurophysiological behavior of human brain Accord-ingly multivariate time series analysis based on nonlineardynamical modeling becomes much appealing to investigatethe important mechanism by which specialized cortical andsubcortical regions integrate their activities into differentfunctions and different spatial scales [19ndash23] In recentstudies brain dynamics can be conceived as a large ensembleof coupled nonlinear dynamical subsystemsWe have focusedon investigating the nonlinear chaotic characteristics ofChan-meditation EEG during the past decade based onnonlinear deterministic modeling of brain dynamics [14
24] Significant nonlinear synchronization has been detectedbetween the macroscopic scale of EEG channels Thus vari-ous types of synchronization based on the concepts of nonlin-ear dynamical systems theory have previously been proposedas a more powerful mechanism than narrow band frequencysynchronization (eg coherence function) for achieving inte-grative neural processing This type of ldquononlinear couplingrdquoallows studying nonlinear interdependence between multi-channel recording sites and represents an alternative to thecoherence function which addresses all of these limitationssimultaneously [24ndash32] As a consequence this study aims toprobe into the 120572-wave nonlinear interdependence behaviorsamong multichannel electroencephalograph (EEG) signalscollected from the orthodox Chan-Buddhist practitioners(experimental group) and normal healthy subjects (controlgroup)
2 Material and Methods
21 Voluntary Subjects and Procedures This study involvedtwo groups of subjects the experimental group including 10volunteers with an average of 58-year Heart-Sealing Chan-meditation experience and the control group including 10volunteers without any meditation experience Seven menand three women were in either group In the experimentalgroup the average age was 28 years while in the controlgroup the average age was 23 years Heart-Sealing Chan-meditation practitioners participated in one 90-minute groupmeditation session every week and practiced approximately30-minute individual meditation on a daily basis Heart-Sealing Chan meditation has been the only orthodox wayof inheriting the lineage of Chan sect The core essenceof orthodox Chan-meditation practice is to transcend thephysiological (fifth) mental (sixth) subconscious (seventh)and Alaya (eighth) states of consciousness and finally attainthe realm of true self characterized by the pure golden lightwith eternal wisdom (Appendix) All the consciousness-transcending preprocesses inside can be completed for a wellexperienced orthodoxChan-meditation practitionerwho hasbeen able to spontaneously activate ten Chakras in ourbody [33] These ten Chakras are important energy spots foraltering states of consciousness by converting our physicallyand mentally dominant characteristics to a particular stateof detachment Accordingly novice practitioners put lotsof effort into the practice from Chakra focusing Chakraperception up to Chakra sealing In the beginning stageof Chakra focusing practitioners may practice the specialbrain-drilling technique to reduce all the wandering thoughtsabiding in the brain The brain-drilling technique involvesfirstly focusing alternately on frontal and posterior regionsof the brain with mindfulness attention and next focusingalternately on left and right regions and perceiving theinterconnections between two regions
In the experiment we conducted overall 50-minuterecording of EEG signals for both groups The EEG signalswere recorded by the 30-channel common-reference (linked-mastoid MS1-MS2) electrode montage based on the interna-tional 10ndash20 system Figure 1 illustrates the EEG recordingmontage of the 30 electrode locations The protocol designed
Evidence-Based Complementary and Alternative Medicine 3
FP1 FP2
F7 F3 Fz F4 F8
FT7 FC3 FCz FC4 FT8
T7 C3 Cz C4 T8
TP7 CP3 CPz CP4 TP8
P7 P3 Pz P4 P8
O1 Oz O2
Figure 1 EEG electrode locations of the 30-channel recordingmontage
for the experimental group involved three sessions 5-minute premeditation relaxation (stage R) 40-minute Chan-meditation practice (stageM) and 5-minute Chakra focusing(stage C) In stage C practitioners focused their mind andperception on a particular chakra named Chan Chakra (thethird ventricle inside the brain as illustrated in Appendix)No particular intervention was applied to the control groupduring the 50-minute EEG recording The control subjectsonly sat in a relaxing position with eyes being closed yet inthe awake state
22 Signal Acquisition and Preprocessing The EEG signalswere originally sampled at 1000Hz after being filtered by theanalog instrumentational band-pass filter with a passbandof 05ndash50Hz The band-pass filter setting was selected toeliminate the 60Hz interference by the power lines A highsampling rate of 1000Hz was adopted to preserve the wave-form quality of gamma rhythms (gt25Hz) often observed inChan-meditation EEG that had been investigated in the otherstudy of our research group In this study we downsampledthe EEG with a sampling rate of 200Hz since the majorfocus of this study is the alpha-dominated EEG epochs Thesegments contaminated by such artifacts as eye blinkingeyeball movement and muscle activities were prescreened inthe preprocessing stage
Wavelet decomposition provides an effective tool toextract the particular EEG rhythm of interest [34ndash36] Inaddition wavelet transform (WT) possesses such appealingproperties as time-frequency localization and multirate fil-tering Specific EEG rhythmmay be extracted by dedicatedlydesigning the WT parameters Wavelet transform can beimplemented either in continuous configuration (CWT) orin discrete form (DWT) Due to the problem of extremelynarrow-band EEG rhythmic pattern CWT (continuous-time
wavelet transform) was implemented in our study to reliablylocalize the correct spectral components of alpha rhythm
In CWT the signal to be analyzed is matched andconvolved with the continuous wavelet basis function withthe continuous time and frequency The original signal isexpressed as a weighted sum of the continuous basis waveletfunction digitized by the sampling rate of the correspondingscale The basis for wavelet transform is called the motherwavelet prototypeWavelet functions are families of functionssatisfying prescribed conditions such as continuity zero-mean amplitude and finite or near finite duration Somecategories of wavelet functions may involve such propertieslike orthogonality and biorthogonality regularity and soforth [35ndash37]
Mother wavelet prototype needs to be appropriatelyselected according to the properties of the particular signalunder investigationAdeli et al [38] successfully captured andlocalized the 3Hz spike andwave complex in the epileptiformEEG by applying wavelet decomposition with Daubechieswavelets Our previous study has corroborated the feasibilityof adopting Daubechies 6 (DB6) wavelet as the motherwavelet in EEG rhythmic analysis [37]
The family of Daubechies wavelets is known for itsorthogonal property and efficient implementation Thelower-order Daubechies wavelets are too coarse to properlyrepresent EEG sharp transients The higher-order ones withextra oscillations are beyond the requirements for analyz-ing the low-frequency EEG rhythms Particularly order 6Daubechies wavelet becomes most appealing in our studybecause its waveform pattern appears to mimic the neuronalaction potentials
23 Nonlinear Interdependence Measure The scheme forevaluating the nonlinear interdependence was based on themodified algorithm employed in computing the similarityindex S(X|Y) [24] Major tasks involved in the algorithm arereconstruction of the 119898-dimensional phase-space trajectoryand computation of the average cloud radius centered at agiven state point
231 Reconstruction of 119898-Dimensional Trajectory Considerthe brain as a nonlinear dynamical system The nonlinearinteractions of the local neuronal networks can be assessed bythe analysis of the collective dynamics underlying EEG timeseries simultaneously recorded from different brain regionsThe first step is to reconstruct the multidimensional phase-space portrait of the system dynamics X and Y respectivelyfrom EEG time series 119909[119894] and 119910[119894] According to the Takensembedding theory [39] a smooth map from the EEG timeseries 119909[119894] | 119894 = 1 119873+(119898minus1)120591 to the phase-space trajec-tory X = 119883
preserves some important topological invariants of the orig-inal system The reconstruction assumes a total number of119873 system-state points in the 119898-dimensional phase-spacetrajectory utilizing a rational time delay 120591 (in sample point)[40 41]The dimension119898 indicates the number of degrees offreedom of the nonlinear system and accordingly reflects thecomplexity of the system dynamics
4 Evidence-Based Complementary and Alternative Medicine
232 Computation of the Average Cloud Radius Considera state point 119883
119894on the 119898-dimensional phase trajectory As
illustrated in Figure 2 a119870NNhypersphere formed by the119870rsquosnearest neighboring (119870NN) points ofX
119894 is a cloud composed
of 119870119898-dimensional neighboring points around 119883119894 Let 119903
119894119895
and 119904119894119895 119895 = 1 119870 denote the time indices of the 119870NN
points of119883119894and119884119894 respectivelyThen the set of state points in
the 119870NN hypersphere centered at 119883119894is 119883119903119894119895
| 119895 = 1 119870The average square Euclidean distance from 119883
119894to its 119870NN
neighbors (or the average square radius of the cloud centeredat119883119894) is defined as
Then for two strongly synchronized systems both self andmutual neighborsmostly coincide so that119877(119870)
119894(119883) asymp 119877
(119870)
119894(119883 |
119884) ≪ 119877119894(119883) whereas for independent systems mutual
neighbors aremore scattered that leads to119877(119870)119894(Χ) ≪ 119877
(119870)
119894(Χ |
119884) asymp 119877119894(119883) Accordingly the degree of interdependence
of these two systems is reflected by the similarities (ordissimilarities) between these two cloud patterns formed byself andmutual neighborsThe strength of similarity betweenthese two point clouds is termed as similarity index 119878 [24 37]and is defined as follows
119878(119870)
(119883 | 119884) =1
119873
119873
sum119894=1
119877(119870)
119894(119883)
119877(119870)
119894(119883 | 119884)
(4)
119878(119870)(119883 | 119884) assesses the statistical dependence of the
state-space structure ofX on that ofY in the sense of testifyingwhether closeness in X implies closeness in Y and vice versaTwo identical systems with the same sets of self and mutualneighbors result in the maximum similarity index (119878 =
1) whereas the index is close to zero (119878 asymp 0) for com-pletely independent systems The opposite interdependence(119878(119870)(119884 | 119883)) can be computed analogically Notice that
similarity indexes are in general asymmetric that is 119878(119870)(119884 |
119883) = 119878(119870)(119883 | 119884) 119878(119870)(119883 | 119884) evaluates the effect of system Y
on system X From the point of view of the system theory
signal Y is regarded as the source or the active role in theinteraction while signal X plays a passive role (a sink) Onthe other hand 119878(119870)(119884 | 119883) analysis considers Y as the sinkthat plays the passive role [24 37]
The asymmetry of 119878 is one of the main advantagesover the other nonlinear measures such as the mutualinformation and the phase synchronizations The fact that119878 is asymmetric allows us to study not only topographicpatterns but also functional properties By considering eachEEG electrode either as a sink or as a source in the nonlinear-interdependence interaction we may thereby further explorethe brain functional topological profile and the direction ofinteraction among local neuronal networks [19] For examplethe condition of 119878(119884 | 119883) gt 119878(119883 | 119884) indicates thatY depends more on X than vice versa In other words Xhas a greater influence on Y than vice versa In such acase X is said to be more active and Y is more passive Byconsidering each electrode either as a sink or as a source inthe nonlinear dynamical interaction we may thereby explorethe spatial direction of the interaction and the dominance oflocal neuronal networks under Chan meditation [42]
In order to maximize the sensitivity to the underlyingsynchronization and gain the robustness against noise weproposed a modified version of 119878measure with an adjustablerange of 119870NN Following our previous study of dimensionalcomplexity index [27 28] a reliable estimate of dimen-sional complexity of a system was obtained by averagingthe complexity indexes over a moderate range of 119870rsquos Asmall 119870 causes superimposed noise while a large 119870 resultsin a measurement involving multimodal effects [27] Todetermine a robust measure against noise it follows that thefinal estimate of nonlinear interdependence is the average119878(119870)(119883 | 119884) over an appropriate range of 119870rsquos and is denoted
by 119878(119883 | 119884)In the practical implementation previous studies of
dimensional complexity for meditation EEG have establisheda moderate choice of parameters The time delay 120591 can bedetermined by the first zero-crossing of the correspondingautocorrelation function Embedding dimension 119898 can bedetermined by the convergent estimate of dimensionalityThewindow length 119873 is selected to encompass the stabilizationof dynamical behavior in the phase space in the sense ofthe convergent estimate of quantitative nonlinear dynami-cal property of reconstructed EEG trajectory for examplecorrelation dimension As a consequence the implementingparameters were selected to be 120591 = 5 (sample points)119898 = 10andwindow length119873 = 1 000 sample points (5 seconds) thatensure convergent and reliable estimates [24 27 28]The finalestimate 119878(119883 | 119884) was obtained by averaging the 119878(119870)(119883 | 119884)
for119870 ranging from 20 to 35
233 Outline of the Scheme The entire scheme employed inthis study is illustrated in Figure 3 that integrates differenttheories and methods to evaluate the nonlinear interdepen-dence for multichannel EEG
To investigate the nonlinear-interdependent behaviorsof alpha activities CWT is employed to identify alpha-dominated epochs in the entire EEG record AnEEG segment
Evidence-Based Complementary and Alternative Medicine 5
X
1 2
3
4
567
8 9
1011
1213
14
15
16
17
18
19
20
2122
r2j = 1 3 4 5 6 7 15 16 17 18
(a)
Y
12
34
5
6
7
8
9
10
11
12
13
1415
1617
18
19
20
21
22
(b)
X
1 2
3
4
56
7
8 9
10
11
12
13
14
15
16
17
18
19
20
2122
(c)
Y
1
2
34
5
6
7
8
9
10
11
12
13
14
15
1617
18
19
20
21
22
s2j = 1 3 5 11 12 13 14 15 21 22
(d)
Figure 2 Illustration for (a) self neighbors 1198831199032119895
( ⃝) (b) state points in 119884 and (c) mutual neighbors 1198831199042119895
() where the indexes 1199042119895
aredetermined from the indexes of (d)119870NN of 119884
Figure 3 Scheme for evaluating nonlinear interdependence ofmultichannel EEG
is identified to be alpha dominant if the percentage of120572 powerto the total power is at least 50 in more than 15 channels(one half of the total channels) Figure 4 displays the resultsof interpreting the 5-second EEG recorded from channels OzCz and Fz The alpha-power percentage (denoted as 120588) foreach one-second epoch is listed beneath the EEG tracingThe5-second EEG tracing is plotted with the amplitude rangingfrom minus50120583V to 50120583V Parameter 120588 evaluated for differentchannels may reflect the focalized behavior of alpha activity
To extend the capacity of assessing the neural-networkinteraction the source119883
119895can be generalized as an integrated
local network involving 119871 active electrode sites so that 119878119901(119883119894)
becomes the average of 119871rsquos 119878(119883119894| 119883119895) assuming119883
119895= 119883119894
119878119901(119883119894) =
1
119871sum119895
119878 (119883119894| 119883119895) (5)
Equation (5) then evaluates the integrative effects of 119871 activeelectrodes on119883
119894 On the other hand the influence of an active
6 Evidence-Based Complementary and Alternative Medicine
50
0
minus500 05 1 15 2 25 3 35 4 45 5
Time (s)120588 58 59 52 55 60
(a) Oz
50
0
minus500 05 1 15 2 25 3 35 4 45 5
Time (s)120588 56 60 50 51 60
(b) Cz
50
0
minus500 05 1 15 2 25 3 35 4 45 5
Time (s)120588 62 61 51 59 60
(c) Fz
Figure 4 Percentage of alpha power to total power for each one-second epoch of the five-second EEG segments (amplitude in 120583V)recorded from (a) Oz (b) Cz and (c) Fz
electrode119883119895on the integrative neural network encompassed
by 119871 passive electrodes (119883119894) can be evaluated by
119878119886(119883119895) =
1
119871sum119894
119878 (119883119894| 119883119895) (6)
assuming119883119894= 119883119895 Both 119878
119901(119883119894) and 119878
119886(119883119895) are called regional
interdependence index (RII)In Chan-meditation practice practitioners often focus on
five regions alternately frontal posterior left right and cen-tral regions after activating the Chan Chakra inside the thirdventricle The purpose is to eliminate the stream of jumbledthoughts and produce a tranquil mind To investigate theeffect of such regional focusing we accordingly divided 30EEG recording sites into five regions
frontal (F) Fp1 Fp2 F7 F3 Fz F4 and F8posterior (P Parietal + Occipital) O1 Oz O2 P7 P3Pz P4 and P8central (C) FCz Cz and CPzleft Temporal (LT) FC3 FT7 T7 C3 TP7 and CP3right Temporal (RT) FC4 FT8 T8C4 TP8 andCP4
3 Results and Discussion
31 Interdependence Matrix of Chan-Meditation EEG Con-sider a given source signal Y The influence of source signalY on sink signal X 119878(X | Y) can be expressed as a 30 times
30 interdependence matrix with the element 119878119894119895= 119878(119883
119894| 119884119895)
denoting the coupling strength of interaction of the source119884119895affecting the sink 119883
119894 The similarity index (SI) was
calculated for 870 (30 times 29) electrode pairs As displayed inFigure 5(a) the color image encoded the quantities in the 30times 30 interdependence matrix S The right-side color chartencodes the strength level of 119878
119894119895 from blue to red indicating
the range of 119878 from the smallest to the largest value EEGchannels are in the order of (from topleft) O2 Oz O1 P7P3 Pz P4 P8 TP8 CP4 CPz CP3 TP7 T7 C3 Cz C4 T8FT8 FC4 FCz FC3 FT7 F7 F3 Fz F4 F8 Fp2 and Fp1 Forexample the box at the lower-left corner characterizes theeffect of O2 channel on Fp1 channel as denoted by 119878(Fp1 |
O2) Accordingly the first row reveals the effect of sourceO2Oz and Fp1 respectively on sink O2 On the other handthe first column indicates how source O2 affects sink O2 Oz and Fp1 respectivelyThe dark red along the diagonal lineindicates the highest similarity index 119878 = 1 when the sourceand sink signals are identical
This figure exhibits some typical behavior in the 119878matrixthat is stronger interdependence occurs in the pairs ofnearby EEG channels On the other hand weaker interactionis measured as two channels are much apart Moreoverbox (119894 119895) does not equal its transposed partner box (119895 119894)indicating the asymmetry of 119878 matrix Figures 5(b)ndash5(d)display the top viewof brain topographicmapping of 119878
119886(FP1)
119878119886(FP2) and 119878
119886(Oz) extracted respectively from the 30th
29th and 2nd columns of Figure 5(a) The topographicmapping was plotted by the function topoplotm providedby EEGLab The mappings exhibit the efficacy of the givenchannel acting as the source role The results in Figures 5(b)to 5(d) reveal the right-frontal dominance The occipitalchannels are comparably less active with respect to the frontalneuronal networks Such weaker influence of occipital andposterior regions on the other regions can be clearly observedfrom the blue color dominating in the left three columns of Smatrix (Figure 5(a)) corresponding to the source at O2 Ozand O1
32 Inter-Region Interdependence AnalysismdashExperimentalGroup Inter-regional nonlinear interdependence was ana-lyzed for EEG recorded in three different sessions (stage RM and C) Due to the premeditation brain-drilling practicedescribed in previous section we particularly focused onthe left-right temporal (LT-RT) and frontal-posterior (F-P)neural-network interactions For example 119878(F rarr P) iscomputed by averaging all 119878
119886(119883119895) in (6) for all 119883
119895isin F and
119883119894isin P to assess the integrative source effect of all electrodes
in frontal region driving the posterior region On the otherhand 119878(P rarr F) is computed by averaging all 119878
119886(119883119895) in
(6) for all 119883119895isin P and 119883
119894isin F when all the electrodes in
the posterior region play the source role to drive the frontalregion
Table 1 lists the group averages and standard deviationsof 119878(F rarr P) 119878(P rarr F) 119878(LT rarr RT) and 119878(RT rarr
LT) at three experimental stages (R M and C) Evidently119878(F rarr P) is consistently greater than 119878(P rarr F) for all threestages The 119875 values (00055 00031 and 00302) of pairedsample 119905-test are all smaller than 005 that demonstrates the
Evidence-Based Complementary and Alternative Medicine 7
Figure 5 SI analysis for experienced practitioner during Chanmeditation (StageM) (a) 30 times 30 Smatrix and brain topographical mappings(top view) of (b) 119878
119886(FP1) (c) 119878
119886(FP2) and (d) 119878
119886(Oz) indicating the average driving strength of the EEG sites FP1 FP2 and Oz
070
065
060
055
050
045
040
Source
Stage RStage MStage C
F P C LT RT
(a)
Sink070
065
060
055
050
045
040
Stage RStage MStage C
F P C LT RT
(b)
Figure 6 Average effectiveness of each region playing the role of a source (a) and sink (b) Three bars in each RII cluster correspond to threeexperimental stages
statistical significance of frontal-alpha dominance at all threestages On the other hand results of the left-right temporalanalysis of nonlinear interdependence reveal no distinctlydominant role of the laterally neural-network operation thatis 119878(LT rarr RT) asymp 119878(RT rarr LT) The higher 119875 values forthe 119878(LT rarr RT)-119878(RT rarr LT) paired 119905-test indicate nostatistically significant difference between two sets of resultsWe may further infer the balancing operations between theleft-brain and right-brain hemispheres
Our results demonstrate that interactions between leftand right hemispheres are much more intensive than theinteractions between frontal and posterior regions with 119875 =
00016 considering all the experimental subjects at all threestages
Figure 6 provides an alternative viewpoint for exploringhow a given region of interest ROI (F P C LT or RT)influences or is influenced by the other regions In Figure 6left (right) group of five 3-bar clusters corresponds to theaverage effectiveness of each region playing the active (pas-sive) role at three stages For example the leftmost barindicates the average of 119878(F rarr P) 119878(F rarr LT) 119878(F rarr
RT) and 119878(F rarr C) for stage R while the rightmostbar indicates the average of 119878(F rarr RT) 119878(P rarr RT)119878(C rarr RT) and 119878(LT rarr RT) for stage C Among allfive regions posterior region as either the source or sinkapparently exhibits the weakest link to the other regions Inaddition the effectiveness of active role of posterior regionis weaker than that of passive role The results strongly
8 Evidence-Based Complementary and Alternative Medicine
Table 1 Group averages and standard deviations of 119878(FrarrP) 119878(Prarr F) 119878(LTrarrRT) and 119878(RTrarr LT) at three experimental stages (R Mand C) including the 119875 values of student 119905-test for 119878(FrarrP)-119878(Prarr F) and 119878(LTrarrRT)-119878(RTrarr LT) pairs
Group average 056 051 060 061Group std 005 005 007 005119875 value 00055 03476
MGroup average 056 050 060 061Group std 003 006 006 004119875 value 00031 01987
CGroup average 055 049 061 061Group std 007 006 006 006119875 value 00302 03953
suggest the inactive behaviors of parietal-occipital lobes sinceregion P encompasses the EEG-electrode sites of parietal andoccipital lobesThe parietal lobe is responsible for integratingsensory information from various parts of the body withthe particular functions of determining spatial sense andnavigation Functions of occipital lobe mainly include visualreception visual-spatial processing and color recognitionAs described previously the core essence of orthodox Chan-meditation practice is to transcend physiological mental andall states of consciousness to prove the existence of true beingThe inactive posterior regions may provide the evidence ofbrain rewiring in preparation for such transcendence
Region C encompasses three midline electrodes locatingfrom precentral to postcentral cortex Region C as the sourceapparently dominates over the other four regions regardlessof the stages On the other hand region C as the passive role isaffected mostly among the five regions Region C constantlyexhibits the largest RII at all stages
Wemay draw a tentative hypothesis from the mechanismof Chan-meditation practice Practitioners are required tokeep Chan Chakra active at any moment that results inthe formation of an energy pathway between Chan Chakraand Qian-Ding acupoint on scalp (Figure 10(b)) Does suchphysiological reformation correlate to the significant effec-tiveness of region C It leaves an open question for futureinvestigation
RII characterizing the regional interdependence behavesdifferently for each region when the experimental subjectsswitch their mental states from R (resting) to M (medita-tion) or from R to C (Chakra focusing) To investigate theeffect of different experimental sessions the RII percentageincreasedecrease from stage R to M and from stage R to Cwere computed for each of the five regions (F P C LT andRT)acting as either the active or the passive role In comparisonof RII between stage M and stage R the percentage largerthan 1 was observed in the regions of LTactive(minus124)RTactive (125) and Cpassive (minus107) On the other handthe regions of significant change in RII when comparingstage C with R include Factive (minus184) Pactive (minus178) andCactive (239) On the basis of RII of stage R for each
individual region we summarize the changes of RII at stagesM and C as follows
(1) In the active-role analysis region LT becomes moredeactivated at stage M while region RT becomesmore activatedWhenmeditation subjects focused onChan Chakra the active driving strength of regionC increases significantly (239) On the other handsuppression of the source activity occurs to bothregions F and P (the regions anterior to and posteriorto region C)
(2) In the passive-role analysis only region C becomesnotably deactivated at stage M (free meditation) Ingeneral differences are trivial in comparison of119877119868119868passive between stages M and R
(3) Chan meditation deactivates the left brain hemi-sphere whereas it inactivates the right brain hemi-sphere
Except for region P the active-role effectiveness of a givenregion is better than its passive-role effectiveness
33 Inter-Region Interdependence AnalysismdashControl GroupIn control group the group average and standard deviationof 119878(F rarr P) 119878(P rarr F) 119878(LT rarr RT) and 119878(RT rarr LT) atstage R are respectively 055 plusmn 004 051 plusmn 004 059 plusmn 003and 058 plusmn 004 The 119875 values of student 119905-test for 119878(F rarr
P)-119878(P rarr F) and 119878(LT rarr RT)-119878(RT rarr LT) pairs are0002 and 0457The results also reveal the frontal dominanceand left-right lateral balance for the control group at rest Yetcompared with the Chan-meditation practitioners controlgroup exhibits weaker strength of effectiveness no matter ifthe region plays an active or a passive role
To explore the average effectiveness of a given ROI weaveraged the RIIs for the region in connection with the otherfour regions Figure 7 displays how a given ROI (F P C LT orRT) influences (active) or is influenced (passive) by the otherregions Similar to the results of experimental group regionP as either the active or passive role exhibits the weakest linksto the other regions
Evidence-Based Complementary and Alternative Medicine 9
Sink
Source
070
065
060
055
050
045
040F P C LT RT
Figure 7 Average effectiveness of each region playing either theactive or passive role
Comparing the efficacy of two counteractive roles playedby the same region we observe that the source-role effective-ness of a given ROI is higher than its sink-role effectivenessexcept region P
34 Comparison between Experimental and Control GroupsFigure 8 illustrates the group averages of RIIs including119878(F rarr P) 119878(P rarr F) 119878(LT rarr RT) and 119878(RT rarr LT)for the experimental group at three stages (R M and C)and for the control group at rest Experimental group revealsmuch more intensive lateral (LT larrrarr RT) interactions thancontrol group The differences are statistically significant forexperimental group at stage M (119875 = 00336) and at stage C(119875 = 00411) On the other hand region P responsible forspatial sense and navigation becomes comparatively inactivefor Chan-meditation practitioners at stage C
The assembling illustration in Figure 9 is used to comparethe average effectiveness of each region between two groupsExperimental group playing either a source role or a sinkrole apparently exhibits higher average effectiveness in allfive regions The extraordinarily large RIIs for region Cparticularly acting the source role may be assumed to becorrelated with the strengthening of neural networks ofregion C dominating over the other regions through thespiritual focusing on Chan Chakra According to the post-experimental interview with Chan-meditation practitionerssuch central (FCz-Cz-CPz) dominating behavior could belinked to theChan-Chakra activation that further induces theperception of grand solemn energy flow in and out throughthe cortical regions defined by acupoints DU20 (Baihui)DU21 (Qianding) and DU22 (Xinhui) in TCM (traditionalChinese Medicine) Figure 10(b) (Appendix) illustrates thelocations of these three acupoints
4 Conclusion
The time-transcending nonmaterial sacred spiritual experi-ences of Chan-meditation practitioners bring our attention tothe study of the unique interactions among regional neuralnetworks in the brain Scientific approach to the scope of
Exp (stage R)Exp (stage M)
Exp (stage C)Control
065
060
055
050
045F rarr P P rarr F LT rarr RT RT rarr LT
Figure 8 Group averages of RIIs (119878(F rarr P) 119878(P rarr F) 119878(LT rarr
RT) and 119878(RT rarr LT)) for experimental group at three stages andfor control group at rest
Chan meditation provides insight into the mechanism inaddition to the vague sketch of meditation sensation and itsmultiform benefits to human beings This paper presents ourpreliminary results based on nonlinear dynamical theory ofexploring the spatial interactions among brain local neuralnetworks under alpha-rhythmic oscillationQuantification ofnonlinear interdependence based on similarity index revealssignificant intergroup difference Significant higher lateralinteractions between left and right temporal regions wereobserved in Chan-meditation practitioners at the stages ofChan meditation and Chakra-focusing practice In Chanpractice practitioners follow the doctrine that the mind canbe enlightened only if it surrenders its leadership power tothe ldquoheartrdquo (Bodhi the true self with eternal wisdom) Theyaccordingly can experience better balance and integrationof the brain hemispheres through years of Chan-meditationpractice
Chan-Chakra spiritual focusing (at stage C) remarkablystrengthens the central neural-network dominance over theother regions On the other hand suppression of the sourceactivity in regions F and P at stage C appears to reveal themeditation state of transcending the realm of physical bodyand mind The particular central (FCz-Cz-CPz) dominatingphenomenon is reflected in long-term Chan practitioners asone of the metamorphosing processes that opens the energypathway between Chan Chakra and the central-line scalpfrom acupoint DU20 to DU22 (Figure 10(b) in Appendix)In the case practitioners experience tranquil brain and calmmind in every moment Chan-meditation practice is to real-ize a Chan-style brain and Chan-style physical body insteadof merely sitting still for one hour to pursue temporary peaceof mind and relief of body
Appendix
Chan meditation originating more than 2500 years ago hasbeen proved to benefit the health while on the way toward theultimate Buddhahood state Buddha Shakyamuni disclosedthe eternal truth the supreme wisdom the noumenal energy
10 Evidence-Based Complementary and Alternative Medicine
Source070
065
060
055
050
F P C LT RT
Exp (R)Exp (M)
Exp (C)Control
(a)
Sink070
065
060
055
050
F P C LT RT
Exp (R)Exp (M)
Exp (C)Control
(b)
Figure 9 Comparison of average effectiveness of each region as a source (a) or a sink (b) between experimental and control groups
Chan Chakra
(a)
DU20
DU21DU22
Anteriorhairline
Posteriorhairline
(b)
Figure 10 (a) Location of the Chan Chakra (inside the third ventricle) (b) Illustration of acupoints DU20 (Baihui) DU21 (Qianding) andDU22 (Xinhui) on DU meridian
and the natural powers of the universe in Chan meditationunder a linden tree The orthodox Chan Buddhism wasoriginated by such an exceptional affair that Buddha Shakya-muni transmitted this light of supreme wisdom to the GreatKashiyapa The same path towards perfect enlightenment(Buddhahood) was promulgated in mainland China in 527
by Bodhidharma the 28th patriarch The current patriarchis Chan master Wu Jue Miao Tian the 85th patriarch of theorthodox Chan-Buddhism Sect since the Great KashiyapaIn orthodox Chan-Buddhist practice very few disciples wereable to catch the quintessence since it cannot be taught inany form of lectures Written material and spoken words
Evidence-Based Complementary and Alternative Medicine 11
cannot promulgate the true wisdom of Chan which can onlybe conveyed by the Buddhist Heart-seal Imprint from a truemaster
In Chan meditation practitioners aim to attain the trueself (Buddha nature) with eternal wisdom (Bodhi) throughbody-mind-soul purification Substantially speaking suchpurification procedure involves the journal of transcendingthe physiological state (five sensory organs) themental activ-ities and normal consciousness the subliminal (the manas)consciousness and the Alaya state at which practitioners areable to perceive the sacred light emitted from Buddha natureBuddhist Heart-seal Imprint from the Chan Patriarch is amust to assist in the purification and accomplishment Toprepare for attaining such realm practitioners meditate withfull-lotus half-lotus or leg-crossing posture and sit still tocultivate spiritual Reiki for penetrating into the ten importantChakras In the course of Chan meditation practitionersmust switch their normal chest breathing to the Navel-Chakra breathing (also called ldquofetal breathingrdquo) that is thebreathing scheme for entering into deep meditation Amongthe ten Chakras Chan Chakra locating inside the thirdventricle is the Buddhist paradise implemented in our bodyFigure 10(a) illustrates the location of Chan Chakra
The cun-measurand system is normally used to measureand locate the acupoints To determine the locations ofacupoints DU20 DU21 and DU22 on Governor Vesselmeridian (DU meridian) we first measure the scalp-midlinelength between anterior hairline and posterior hairline thatis divided into 12 cuns The locations are defined as follows
DU20 7 cuns above the posterior hairline and 5 cunsabove the anterior hairlineDU21 35 cuns directly above the anterior hairline or15 cuns anterior to DU20DU22 2 cuns posterior to the anterior hairline or3 cuns anterior to DU20
Acknowledgments
The authors would like to thank Shung-Yu Yo for his assis-tance in data analysis Chan-meditation practitioners of theShakyamuni Buddhist Foundation are gratefully acknowl-edged for their enthusiastic participation in this research asvolunteers This research was supported by the grants fromthe National Science Council of Taiwan (Grant no NSC 100-2221-E-009-006-MY2)
References
[1] T YuH L Tsai andM LHwang ldquoSuppressing tumor progres-sion of in vitro prostate cancer cells by emitted psychosomaticpower through Zen meditationrdquo American Journal of ChineseMedicine vol 31 no 3 pp 499ndash507 2003
[2] K H Coker ldquoMeditation and prostate cancer integrating amindbody interventionwith traditional therapiesrdquo Seminars inUrologic Oncology vol 17 no 2 pp 111ndash118 1999
[3] D Lester ldquoZen and happinessrdquo Psychological Reports vol 84no 2 pp 650ndash651 1999
[4] C R K MacLean K G Walton S R Wenneberg et alldquoEffects of the transcendental meditation program on adaptivemechanisms changes in hormone levels and responses to stressafter 4 months of practicerdquo Psychoneuroendocrinology vol 22no 4 pp 277ndash295 1997
[5] GA Tooley SMArmstrong T RNorman andA Sali ldquoAcuteincreases in night-time plasma melatonin levels following aperiod of meditationrdquo Biological Psychology vol 53 no 1 pp69ndash78 2000
[6] Y-Y Tang Y Ma Y Fan et al ldquoCentral and autonomicnervous system interaction is altered by short-termmeditationrdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 106 no 22 pp 8865ndash8870 2009
[7] A Lutz H A Slagter N B Rawlings A D Francis LL Greischar and R J Davidson ldquoMental training enhancesattentional stability neural and behavioral evidencerdquo Journal ofNeuroscience vol 29 no 42 pp 13418ndash13427 2009
[8] S M Bertisch C C Wee R S Phillips and E P McCarthyldquoAlternative mind-body therapies used by adults with medicalconditionsrdquo Journal of Psychosomatic Research vol 66 no 6 pp511ndash519 2009
[9] W R Marchand ldquoMindfulness-based stress reductionmindfulness-based cognitive therapy and zen meditation fordepression anxiety pain and psychological distressrdquo Journalof Psychiatric Practice vol 18 no 4 pp 233ndash2252 2012
[10] B R Cahn and J Polich ldquoMeditation states and traits EEG ERPand neuroimaging studiesrdquoPsychological Bulletin vol 132 no 2pp 180ndash211 2006
[11] F Travis and J Shear ldquoFocused attention open monitoring andautomatic self-transcending categories to organize meditationsfrom Vedic Buddhist and Chinese traditionsrdquo Consciousnessand Cognition vol 19 no 4 pp 1110ndash1118 2010
[12] P-C Lo M-L Huang and K-M Chang ldquoEEG alpha blockingcorrelated with perception of inner light during Zen medita-tionrdquo American Journal of Chinese Medicine vol 31 no 4 pp629ndash642 2003
[13] H C Liao and P C Lo ldquoInvestigation on spatiotemporalcharacteristics of zen-meditation EEG rhythmsrdquo Journal ofInternational Society of Life Information Science vol 25 no 1pp 63ndash71 2007
[14] H-Y Huang and P-C Lo ldquoEEG dynamics of experienced zenmeditation practitioners probed by complexity index and spec-tral measurerdquo Journal of Medical Engineering and Technologyvol 33 no 4 pp 314ndash321 2009
[15] E K St Louis and E P Lansky ldquoMeditation and epilepsy a stillhung juryrdquoMedical Hypotheses vol 67 no 2 pp 247ndash250 2006
[16] L I Aftanas and S A Golocheikine ldquoHuman anterior andfrontal midline theta and lower alpha reflect emotionallypositive state and internalized attention high-resolution EEGinvestigation of meditationrdquo Neuroscience Letters vol 310 no1 pp 57ndash60 2001
[17] K Ansari-Asl J-J Bellanger F Bartolomei F Wendung andL Senhadji ldquoTime-frequency characterization of interdepen-dencies in nonstationary signals application to epileptic EEGrdquoIEEE Transactions on Biomedical Engineering vol 52 no 7 pp1218ndash1226 2005
[18] F Gans A Y Schumann J W Kantelhardt T Penzel and IFietze ldquoCross-modulated amplitudes and frequencies charac-terize interacting components in complex systemsrdquo PhysicalReview Letters vol 102 no 9 Article ID 098701 2009
12 Evidence-Based Complementary and Alternative Medicine
[19] J Bhattacharya H Petsche and E Pereda ldquoInterdependenciesin the spontaneous EEG while listening to musicrdquo InternationalJournal of Psychophysiology vol 42 no 3 pp 287ndash301 2001
[20] C J Stam ldquoNonlinear dynamical analysis of EEG and MEGreview of an emerging fieldrdquo Clinical Neurophysiology vol 116no 10 pp 2266ndash2301 2005
[21] W Singer ldquoConsciousness and the binding problemrdquo Annals ofthe New York Academy of Sciences vol 929 pp 123ndash146 2001
[22] D Calitoiu B J Oommen and D Nussbaum ldquoLarge-scaleneuro-modeling for understanding and explaining some brain-related chaotic behaviorrdquo Simulation-Transactions of the Societyfor Modeling and Simulation International vol 88 no 11 pp1316ndash1337 2012
[23] F Wendling K Ansari-Asl F Bartolomei and L SenhadjildquoFrom EEG signals to brain connectivity a model-based eval-uation of interdependence measuresrdquo Journal of NeuroscienceMethods vol 183 no 1 pp 9ndash18 2009
[24] H Y Huang and P C Lo ldquoEEG nonlinear interdependencemeasure of brain interactions under zen meditationrdquo Journalof Biomedical Engineering Research vol 29 no 4 pp 286ndash2942008
[25] M Breakspear and J R Terry ldquoDetection and description ofnon-linear interdependence in normal multichannel humanEEG datardquo Clinical Neurophysiology vol 113 no 5 pp 735ndash7532002
[26] M Breakspear and J R Terry ldquoTopographic organizationof nonlinear interdependence in multichannel human EEGrdquoNeuroImage vol 16 no 3 pp 822ndash835 2002
[27] C J Stam M Breakspear A-M van Cappellen van Walsumand B W van Dijk ldquoNonlinear synchronization in EEG andwhole-headMEG recordings of healthy subjectsrdquoHuman BrainMapping vol 19 no 2 pp 63ndash78 2003
[28] U Feldmann and J Bhattacharya ldquoPredictability improvementas an asymmetrical measure of interdependence in bivariatetime seriesrdquo International Journal of Bifurcation and Chaos vol14 no 2 pp 505ndash514 2004
[29] M Rubinov S A Knock C J Stam et al ldquoSmall-worldproperties of nonlinear brain activity in schizophreniardquoHumanBrain Mapping vol 30 no 2 pp 403ndash416 2009
[30] P Mirowski D Madhavan Y LeCun and R KuznieckyldquoClassification of patterns of EEG synchronization for seizurepredictionrdquo Clinical Neurophysiology vol 120 no 11 pp 1927ndash1940 2009
[31] S I Dimitriadis N A Laskaris Y del Rio-Portilla and G CKoudounis ldquoCharacterizing dynamic functional connectivityacross sleep stages from EEGrdquo Brain Topography vol 22 no 2pp 119ndash133 2009
[32] K Sibsambhu and R Aurobinda ldquoEffect of sleep deprivation onfunctional connectivity of EEG channelsrdquo IEEE Transcations onSystems Man and Cybernetics vol 43 no 3 pp 666ndash672 2013
[33] C M W J M Tian Chan Master Miao Tianrsquos Book of Wisdomand the Guide to Heart Chan Meditation Lulu 2010
[34] X-S Zhang R J Roy and E W Jensen ldquoEEG complexity as ameasure of depth of anesthesia for patientsrdquo IEEE Transactionson Biomedical Engineering vol 48 no 12 pp 1424ndash1433 2001
[35] I Daubechies Ten Lectures on Wavelets Society for Industrialand Applied Mathematics Philadelphia Pa USA 1992
[36] C Heil D F Walnut and I Daubechies Fundamental Papersin Wavelet Theory Princeton University Press Princeton NJUSA 2006
[37] C Y Liu and P C Lo ldquoSpatial focalization of zen-meditationbrain based on EEGrdquo Journal of Biomedical EngineeringResearch vol 29 pp 17ndash24 2008
[38] H Adeli Z Zhou and N Dadmehr ldquoAnalysis of EEG recordsin an epileptic patient using wavelet transformrdquo Journal ofNeuroscience Methods vol 123 no 1 pp 69ndash87 2003
[39] F Takens ldquoDetecting strange attractors in turbulencerdquo inDynamical Systems and Turbulence D A Rand and L S YoungEds vol 898 of Lecture Notes in Mathematics pp 366ndash381Springer New York NY USA 1981
[40] P-C Lo and W-P Chung ldquoAn approach to quantifying themulti-channel EEG spatial-temporal featurerdquo Biometrical Jour-nal vol 42 no 7 pp 901ndash916 2000
[41] W S Pritchard and D W Duke ldquoDimensional analysis of no-task human EEG using the Grassberger-Procaccia methodrdquoPsychophysiology vol 29 no 2 pp 182ndash192 1992
[42] R Q Quiroga A Kraskov T Kreuz and P GrassbergerldquoPerformance of different synchronization measures in realdata a case study on electroencephalographic signalsrdquo PhysicalReview E vol 65 no 4 Article ID 041903 14 pages 2002
Evidence-Based Complementary and Alternative Medicine 3
FP1 FP2
F7 F3 Fz F4 F8
FT7 FC3 FCz FC4 FT8
T7 C3 Cz C4 T8
TP7 CP3 CPz CP4 TP8
P7 P3 Pz P4 P8
O1 Oz O2
Figure 1 EEG electrode locations of the 30-channel recordingmontage
for the experimental group involved three sessions 5-minute premeditation relaxation (stage R) 40-minute Chan-meditation practice (stageM) and 5-minute Chakra focusing(stage C) In stage C practitioners focused their mind andperception on a particular chakra named Chan Chakra (thethird ventricle inside the brain as illustrated in Appendix)No particular intervention was applied to the control groupduring the 50-minute EEG recording The control subjectsonly sat in a relaxing position with eyes being closed yet inthe awake state
22 Signal Acquisition and Preprocessing The EEG signalswere originally sampled at 1000Hz after being filtered by theanalog instrumentational band-pass filter with a passbandof 05ndash50Hz The band-pass filter setting was selected toeliminate the 60Hz interference by the power lines A highsampling rate of 1000Hz was adopted to preserve the wave-form quality of gamma rhythms (gt25Hz) often observed inChan-meditation EEG that had been investigated in the otherstudy of our research group In this study we downsampledthe EEG with a sampling rate of 200Hz since the majorfocus of this study is the alpha-dominated EEG epochs Thesegments contaminated by such artifacts as eye blinkingeyeball movement and muscle activities were prescreened inthe preprocessing stage
Wavelet decomposition provides an effective tool toextract the particular EEG rhythm of interest [34ndash36] Inaddition wavelet transform (WT) possesses such appealingproperties as time-frequency localization and multirate fil-tering Specific EEG rhythmmay be extracted by dedicatedlydesigning the WT parameters Wavelet transform can beimplemented either in continuous configuration (CWT) orin discrete form (DWT) Due to the problem of extremelynarrow-band EEG rhythmic pattern CWT (continuous-time
wavelet transform) was implemented in our study to reliablylocalize the correct spectral components of alpha rhythm
In CWT the signal to be analyzed is matched andconvolved with the continuous wavelet basis function withthe continuous time and frequency The original signal isexpressed as a weighted sum of the continuous basis waveletfunction digitized by the sampling rate of the correspondingscale The basis for wavelet transform is called the motherwavelet prototypeWavelet functions are families of functionssatisfying prescribed conditions such as continuity zero-mean amplitude and finite or near finite duration Somecategories of wavelet functions may involve such propertieslike orthogonality and biorthogonality regularity and soforth [35ndash37]
Mother wavelet prototype needs to be appropriatelyselected according to the properties of the particular signalunder investigationAdeli et al [38] successfully captured andlocalized the 3Hz spike andwave complex in the epileptiformEEG by applying wavelet decomposition with Daubechieswavelets Our previous study has corroborated the feasibilityof adopting Daubechies 6 (DB6) wavelet as the motherwavelet in EEG rhythmic analysis [37]
The family of Daubechies wavelets is known for itsorthogonal property and efficient implementation Thelower-order Daubechies wavelets are too coarse to properlyrepresent EEG sharp transients The higher-order ones withextra oscillations are beyond the requirements for analyz-ing the low-frequency EEG rhythms Particularly order 6Daubechies wavelet becomes most appealing in our studybecause its waveform pattern appears to mimic the neuronalaction potentials
23 Nonlinear Interdependence Measure The scheme forevaluating the nonlinear interdependence was based on themodified algorithm employed in computing the similarityindex S(X|Y) [24] Major tasks involved in the algorithm arereconstruction of the 119898-dimensional phase-space trajectoryand computation of the average cloud radius centered at agiven state point
231 Reconstruction of 119898-Dimensional Trajectory Considerthe brain as a nonlinear dynamical system The nonlinearinteractions of the local neuronal networks can be assessed bythe analysis of the collective dynamics underlying EEG timeseries simultaneously recorded from different brain regionsThe first step is to reconstruct the multidimensional phase-space portrait of the system dynamics X and Y respectivelyfrom EEG time series 119909[119894] and 119910[119894] According to the Takensembedding theory [39] a smooth map from the EEG timeseries 119909[119894] | 119894 = 1 119873+(119898minus1)120591 to the phase-space trajec-tory X = 119883
preserves some important topological invariants of the orig-inal system The reconstruction assumes a total number of119873 system-state points in the 119898-dimensional phase-spacetrajectory utilizing a rational time delay 120591 (in sample point)[40 41]The dimension119898 indicates the number of degrees offreedom of the nonlinear system and accordingly reflects thecomplexity of the system dynamics
4 Evidence-Based Complementary and Alternative Medicine
232 Computation of the Average Cloud Radius Considera state point 119883
119894on the 119898-dimensional phase trajectory As
illustrated in Figure 2 a119870NNhypersphere formed by the119870rsquosnearest neighboring (119870NN) points ofX
119894 is a cloud composed
of 119870119898-dimensional neighboring points around 119883119894 Let 119903
119894119895
and 119904119894119895 119895 = 1 119870 denote the time indices of the 119870NN
points of119883119894and119884119894 respectivelyThen the set of state points in
the 119870NN hypersphere centered at 119883119894is 119883119903119894119895
| 119895 = 1 119870The average square Euclidean distance from 119883
119894to its 119870NN
neighbors (or the average square radius of the cloud centeredat119883119894) is defined as
Then for two strongly synchronized systems both self andmutual neighborsmostly coincide so that119877(119870)
119894(119883) asymp 119877
(119870)
119894(119883 |
119884) ≪ 119877119894(119883) whereas for independent systems mutual
neighbors aremore scattered that leads to119877(119870)119894(Χ) ≪ 119877
(119870)
119894(Χ |
119884) asymp 119877119894(119883) Accordingly the degree of interdependence
of these two systems is reflected by the similarities (ordissimilarities) between these two cloud patterns formed byself andmutual neighborsThe strength of similarity betweenthese two point clouds is termed as similarity index 119878 [24 37]and is defined as follows
119878(119870)
(119883 | 119884) =1
119873
119873
sum119894=1
119877(119870)
119894(119883)
119877(119870)
119894(119883 | 119884)
(4)
119878(119870)(119883 | 119884) assesses the statistical dependence of the
state-space structure ofX on that ofY in the sense of testifyingwhether closeness in X implies closeness in Y and vice versaTwo identical systems with the same sets of self and mutualneighbors result in the maximum similarity index (119878 =
1) whereas the index is close to zero (119878 asymp 0) for com-pletely independent systems The opposite interdependence(119878(119870)(119884 | 119883)) can be computed analogically Notice that
similarity indexes are in general asymmetric that is 119878(119870)(119884 |
119883) = 119878(119870)(119883 | 119884) 119878(119870)(119883 | 119884) evaluates the effect of system Y
on system X From the point of view of the system theory
signal Y is regarded as the source or the active role in theinteraction while signal X plays a passive role (a sink) Onthe other hand 119878(119870)(119884 | 119883) analysis considers Y as the sinkthat plays the passive role [24 37]
The asymmetry of 119878 is one of the main advantagesover the other nonlinear measures such as the mutualinformation and the phase synchronizations The fact that119878 is asymmetric allows us to study not only topographicpatterns but also functional properties By considering eachEEG electrode either as a sink or as a source in the nonlinear-interdependence interaction we may thereby further explorethe brain functional topological profile and the direction ofinteraction among local neuronal networks [19] For examplethe condition of 119878(119884 | 119883) gt 119878(119883 | 119884) indicates thatY depends more on X than vice versa In other words Xhas a greater influence on Y than vice versa In such acase X is said to be more active and Y is more passive Byconsidering each electrode either as a sink or as a source inthe nonlinear dynamical interaction we may thereby explorethe spatial direction of the interaction and the dominance oflocal neuronal networks under Chan meditation [42]
In order to maximize the sensitivity to the underlyingsynchronization and gain the robustness against noise weproposed a modified version of 119878measure with an adjustablerange of 119870NN Following our previous study of dimensionalcomplexity index [27 28] a reliable estimate of dimen-sional complexity of a system was obtained by averagingthe complexity indexes over a moderate range of 119870rsquos Asmall 119870 causes superimposed noise while a large 119870 resultsin a measurement involving multimodal effects [27] Todetermine a robust measure against noise it follows that thefinal estimate of nonlinear interdependence is the average119878(119870)(119883 | 119884) over an appropriate range of 119870rsquos and is denoted
by 119878(119883 | 119884)In the practical implementation previous studies of
dimensional complexity for meditation EEG have establisheda moderate choice of parameters The time delay 120591 can bedetermined by the first zero-crossing of the correspondingautocorrelation function Embedding dimension 119898 can bedetermined by the convergent estimate of dimensionalityThewindow length 119873 is selected to encompass the stabilizationof dynamical behavior in the phase space in the sense ofthe convergent estimate of quantitative nonlinear dynami-cal property of reconstructed EEG trajectory for examplecorrelation dimension As a consequence the implementingparameters were selected to be 120591 = 5 (sample points)119898 = 10andwindow length119873 = 1 000 sample points (5 seconds) thatensure convergent and reliable estimates [24 27 28]The finalestimate 119878(119883 | 119884) was obtained by averaging the 119878(119870)(119883 | 119884)
for119870 ranging from 20 to 35
233 Outline of the Scheme The entire scheme employed inthis study is illustrated in Figure 3 that integrates differenttheories and methods to evaluate the nonlinear interdepen-dence for multichannel EEG
To investigate the nonlinear-interdependent behaviorsof alpha activities CWT is employed to identify alpha-dominated epochs in the entire EEG record AnEEG segment
Evidence-Based Complementary and Alternative Medicine 5
X
1 2
3
4
567
8 9
1011
1213
14
15
16
17
18
19
20
2122
r2j = 1 3 4 5 6 7 15 16 17 18
(a)
Y
12
34
5
6
7
8
9
10
11
12
13
1415
1617
18
19
20
21
22
(b)
X
1 2
3
4
56
7
8 9
10
11
12
13
14
15
16
17
18
19
20
2122
(c)
Y
1
2
34
5
6
7
8
9
10
11
12
13
14
15
1617
18
19
20
21
22
s2j = 1 3 5 11 12 13 14 15 21 22
(d)
Figure 2 Illustration for (a) self neighbors 1198831199032119895
( ⃝) (b) state points in 119884 and (c) mutual neighbors 1198831199042119895
() where the indexes 1199042119895
aredetermined from the indexes of (d)119870NN of 119884
Figure 3 Scheme for evaluating nonlinear interdependence ofmultichannel EEG
is identified to be alpha dominant if the percentage of120572 powerto the total power is at least 50 in more than 15 channels(one half of the total channels) Figure 4 displays the resultsof interpreting the 5-second EEG recorded from channels OzCz and Fz The alpha-power percentage (denoted as 120588) foreach one-second epoch is listed beneath the EEG tracingThe5-second EEG tracing is plotted with the amplitude rangingfrom minus50120583V to 50120583V Parameter 120588 evaluated for differentchannels may reflect the focalized behavior of alpha activity
To extend the capacity of assessing the neural-networkinteraction the source119883
119895can be generalized as an integrated
local network involving 119871 active electrode sites so that 119878119901(119883119894)
becomes the average of 119871rsquos 119878(119883119894| 119883119895) assuming119883
119895= 119883119894
119878119901(119883119894) =
1
119871sum119895
119878 (119883119894| 119883119895) (5)
Equation (5) then evaluates the integrative effects of 119871 activeelectrodes on119883
119894 On the other hand the influence of an active
6 Evidence-Based Complementary and Alternative Medicine
50
0
minus500 05 1 15 2 25 3 35 4 45 5
Time (s)120588 58 59 52 55 60
(a) Oz
50
0
minus500 05 1 15 2 25 3 35 4 45 5
Time (s)120588 56 60 50 51 60
(b) Cz
50
0
minus500 05 1 15 2 25 3 35 4 45 5
Time (s)120588 62 61 51 59 60
(c) Fz
Figure 4 Percentage of alpha power to total power for each one-second epoch of the five-second EEG segments (amplitude in 120583V)recorded from (a) Oz (b) Cz and (c) Fz
electrode119883119895on the integrative neural network encompassed
by 119871 passive electrodes (119883119894) can be evaluated by
119878119886(119883119895) =
1
119871sum119894
119878 (119883119894| 119883119895) (6)
assuming119883119894= 119883119895 Both 119878
119901(119883119894) and 119878
119886(119883119895) are called regional
interdependence index (RII)In Chan-meditation practice practitioners often focus on
five regions alternately frontal posterior left right and cen-tral regions after activating the Chan Chakra inside the thirdventricle The purpose is to eliminate the stream of jumbledthoughts and produce a tranquil mind To investigate theeffect of such regional focusing we accordingly divided 30EEG recording sites into five regions
frontal (F) Fp1 Fp2 F7 F3 Fz F4 and F8posterior (P Parietal + Occipital) O1 Oz O2 P7 P3Pz P4 and P8central (C) FCz Cz and CPzleft Temporal (LT) FC3 FT7 T7 C3 TP7 and CP3right Temporal (RT) FC4 FT8 T8C4 TP8 andCP4
3 Results and Discussion
31 Interdependence Matrix of Chan-Meditation EEG Con-sider a given source signal Y The influence of source signalY on sink signal X 119878(X | Y) can be expressed as a 30 times
30 interdependence matrix with the element 119878119894119895= 119878(119883
119894| 119884119895)
denoting the coupling strength of interaction of the source119884119895affecting the sink 119883
119894 The similarity index (SI) was
calculated for 870 (30 times 29) electrode pairs As displayed inFigure 5(a) the color image encoded the quantities in the 30times 30 interdependence matrix S The right-side color chartencodes the strength level of 119878
119894119895 from blue to red indicating
the range of 119878 from the smallest to the largest value EEGchannels are in the order of (from topleft) O2 Oz O1 P7P3 Pz P4 P8 TP8 CP4 CPz CP3 TP7 T7 C3 Cz C4 T8FT8 FC4 FCz FC3 FT7 F7 F3 Fz F4 F8 Fp2 and Fp1 Forexample the box at the lower-left corner characterizes theeffect of O2 channel on Fp1 channel as denoted by 119878(Fp1 |
O2) Accordingly the first row reveals the effect of sourceO2Oz and Fp1 respectively on sink O2 On the other handthe first column indicates how source O2 affects sink O2 Oz and Fp1 respectivelyThe dark red along the diagonal lineindicates the highest similarity index 119878 = 1 when the sourceand sink signals are identical
This figure exhibits some typical behavior in the 119878matrixthat is stronger interdependence occurs in the pairs ofnearby EEG channels On the other hand weaker interactionis measured as two channels are much apart Moreoverbox (119894 119895) does not equal its transposed partner box (119895 119894)indicating the asymmetry of 119878 matrix Figures 5(b)ndash5(d)display the top viewof brain topographicmapping of 119878
119886(FP1)
119878119886(FP2) and 119878
119886(Oz) extracted respectively from the 30th
29th and 2nd columns of Figure 5(a) The topographicmapping was plotted by the function topoplotm providedby EEGLab The mappings exhibit the efficacy of the givenchannel acting as the source role The results in Figures 5(b)to 5(d) reveal the right-frontal dominance The occipitalchannels are comparably less active with respect to the frontalneuronal networks Such weaker influence of occipital andposterior regions on the other regions can be clearly observedfrom the blue color dominating in the left three columns of Smatrix (Figure 5(a)) corresponding to the source at O2 Ozand O1
32 Inter-Region Interdependence AnalysismdashExperimentalGroup Inter-regional nonlinear interdependence was ana-lyzed for EEG recorded in three different sessions (stage RM and C) Due to the premeditation brain-drilling practicedescribed in previous section we particularly focused onthe left-right temporal (LT-RT) and frontal-posterior (F-P)neural-network interactions For example 119878(F rarr P) iscomputed by averaging all 119878
119886(119883119895) in (6) for all 119883
119895isin F and
119883119894isin P to assess the integrative source effect of all electrodes
in frontal region driving the posterior region On the otherhand 119878(P rarr F) is computed by averaging all 119878
119886(119883119895) in
(6) for all 119883119895isin P and 119883
119894isin F when all the electrodes in
the posterior region play the source role to drive the frontalregion
Table 1 lists the group averages and standard deviationsof 119878(F rarr P) 119878(P rarr F) 119878(LT rarr RT) and 119878(RT rarr
LT) at three experimental stages (R M and C) Evidently119878(F rarr P) is consistently greater than 119878(P rarr F) for all threestages The 119875 values (00055 00031 and 00302) of pairedsample 119905-test are all smaller than 005 that demonstrates the
Evidence-Based Complementary and Alternative Medicine 7
Figure 5 SI analysis for experienced practitioner during Chanmeditation (StageM) (a) 30 times 30 Smatrix and brain topographical mappings(top view) of (b) 119878
119886(FP1) (c) 119878
119886(FP2) and (d) 119878
119886(Oz) indicating the average driving strength of the EEG sites FP1 FP2 and Oz
070
065
060
055
050
045
040
Source
Stage RStage MStage C
F P C LT RT
(a)
Sink070
065
060
055
050
045
040
Stage RStage MStage C
F P C LT RT
(b)
Figure 6 Average effectiveness of each region playing the role of a source (a) and sink (b) Three bars in each RII cluster correspond to threeexperimental stages
statistical significance of frontal-alpha dominance at all threestages On the other hand results of the left-right temporalanalysis of nonlinear interdependence reveal no distinctlydominant role of the laterally neural-network operation thatis 119878(LT rarr RT) asymp 119878(RT rarr LT) The higher 119875 values forthe 119878(LT rarr RT)-119878(RT rarr LT) paired 119905-test indicate nostatistically significant difference between two sets of resultsWe may further infer the balancing operations between theleft-brain and right-brain hemispheres
Our results demonstrate that interactions between leftand right hemispheres are much more intensive than theinteractions between frontal and posterior regions with 119875 =
00016 considering all the experimental subjects at all threestages
Figure 6 provides an alternative viewpoint for exploringhow a given region of interest ROI (F P C LT or RT)influences or is influenced by the other regions In Figure 6left (right) group of five 3-bar clusters corresponds to theaverage effectiveness of each region playing the active (pas-sive) role at three stages For example the leftmost barindicates the average of 119878(F rarr P) 119878(F rarr LT) 119878(F rarr
RT) and 119878(F rarr C) for stage R while the rightmostbar indicates the average of 119878(F rarr RT) 119878(P rarr RT)119878(C rarr RT) and 119878(LT rarr RT) for stage C Among allfive regions posterior region as either the source or sinkapparently exhibits the weakest link to the other regions Inaddition the effectiveness of active role of posterior regionis weaker than that of passive role The results strongly
8 Evidence-Based Complementary and Alternative Medicine
Table 1 Group averages and standard deviations of 119878(FrarrP) 119878(Prarr F) 119878(LTrarrRT) and 119878(RTrarr LT) at three experimental stages (R Mand C) including the 119875 values of student 119905-test for 119878(FrarrP)-119878(Prarr F) and 119878(LTrarrRT)-119878(RTrarr LT) pairs
Group average 056 051 060 061Group std 005 005 007 005119875 value 00055 03476
MGroup average 056 050 060 061Group std 003 006 006 004119875 value 00031 01987
CGroup average 055 049 061 061Group std 007 006 006 006119875 value 00302 03953
suggest the inactive behaviors of parietal-occipital lobes sinceregion P encompasses the EEG-electrode sites of parietal andoccipital lobesThe parietal lobe is responsible for integratingsensory information from various parts of the body withthe particular functions of determining spatial sense andnavigation Functions of occipital lobe mainly include visualreception visual-spatial processing and color recognitionAs described previously the core essence of orthodox Chan-meditation practice is to transcend physiological mental andall states of consciousness to prove the existence of true beingThe inactive posterior regions may provide the evidence ofbrain rewiring in preparation for such transcendence
Region C encompasses three midline electrodes locatingfrom precentral to postcentral cortex Region C as the sourceapparently dominates over the other four regions regardlessof the stages On the other hand region C as the passive role isaffected mostly among the five regions Region C constantlyexhibits the largest RII at all stages
Wemay draw a tentative hypothesis from the mechanismof Chan-meditation practice Practitioners are required tokeep Chan Chakra active at any moment that results inthe formation of an energy pathway between Chan Chakraand Qian-Ding acupoint on scalp (Figure 10(b)) Does suchphysiological reformation correlate to the significant effec-tiveness of region C It leaves an open question for futureinvestigation
RII characterizing the regional interdependence behavesdifferently for each region when the experimental subjectsswitch their mental states from R (resting) to M (medita-tion) or from R to C (Chakra focusing) To investigate theeffect of different experimental sessions the RII percentageincreasedecrease from stage R to M and from stage R to Cwere computed for each of the five regions (F P C LT andRT)acting as either the active or the passive role In comparisonof RII between stage M and stage R the percentage largerthan 1 was observed in the regions of LTactive(minus124)RTactive (125) and Cpassive (minus107) On the other handthe regions of significant change in RII when comparingstage C with R include Factive (minus184) Pactive (minus178) andCactive (239) On the basis of RII of stage R for each
individual region we summarize the changes of RII at stagesM and C as follows
(1) In the active-role analysis region LT becomes moredeactivated at stage M while region RT becomesmore activatedWhenmeditation subjects focused onChan Chakra the active driving strength of regionC increases significantly (239) On the other handsuppression of the source activity occurs to bothregions F and P (the regions anterior to and posteriorto region C)
(2) In the passive-role analysis only region C becomesnotably deactivated at stage M (free meditation) Ingeneral differences are trivial in comparison of119877119868119868passive between stages M and R
(3) Chan meditation deactivates the left brain hemi-sphere whereas it inactivates the right brain hemi-sphere
Except for region P the active-role effectiveness of a givenregion is better than its passive-role effectiveness
33 Inter-Region Interdependence AnalysismdashControl GroupIn control group the group average and standard deviationof 119878(F rarr P) 119878(P rarr F) 119878(LT rarr RT) and 119878(RT rarr LT) atstage R are respectively 055 plusmn 004 051 plusmn 004 059 plusmn 003and 058 plusmn 004 The 119875 values of student 119905-test for 119878(F rarr
P)-119878(P rarr F) and 119878(LT rarr RT)-119878(RT rarr LT) pairs are0002 and 0457The results also reveal the frontal dominanceand left-right lateral balance for the control group at rest Yetcompared with the Chan-meditation practitioners controlgroup exhibits weaker strength of effectiveness no matter ifthe region plays an active or a passive role
To explore the average effectiveness of a given ROI weaveraged the RIIs for the region in connection with the otherfour regions Figure 7 displays how a given ROI (F P C LT orRT) influences (active) or is influenced (passive) by the otherregions Similar to the results of experimental group regionP as either the active or passive role exhibits the weakest linksto the other regions
Evidence-Based Complementary and Alternative Medicine 9
Sink
Source
070
065
060
055
050
045
040F P C LT RT
Figure 7 Average effectiveness of each region playing either theactive or passive role
Comparing the efficacy of two counteractive roles playedby the same region we observe that the source-role effective-ness of a given ROI is higher than its sink-role effectivenessexcept region P
34 Comparison between Experimental and Control GroupsFigure 8 illustrates the group averages of RIIs including119878(F rarr P) 119878(P rarr F) 119878(LT rarr RT) and 119878(RT rarr LT)for the experimental group at three stages (R M and C)and for the control group at rest Experimental group revealsmuch more intensive lateral (LT larrrarr RT) interactions thancontrol group The differences are statistically significant forexperimental group at stage M (119875 = 00336) and at stage C(119875 = 00411) On the other hand region P responsible forspatial sense and navigation becomes comparatively inactivefor Chan-meditation practitioners at stage C
The assembling illustration in Figure 9 is used to comparethe average effectiveness of each region between two groupsExperimental group playing either a source role or a sinkrole apparently exhibits higher average effectiveness in allfive regions The extraordinarily large RIIs for region Cparticularly acting the source role may be assumed to becorrelated with the strengthening of neural networks ofregion C dominating over the other regions through thespiritual focusing on Chan Chakra According to the post-experimental interview with Chan-meditation practitionerssuch central (FCz-Cz-CPz) dominating behavior could belinked to theChan-Chakra activation that further induces theperception of grand solemn energy flow in and out throughthe cortical regions defined by acupoints DU20 (Baihui)DU21 (Qianding) and DU22 (Xinhui) in TCM (traditionalChinese Medicine) Figure 10(b) (Appendix) illustrates thelocations of these three acupoints
4 Conclusion
The time-transcending nonmaterial sacred spiritual experi-ences of Chan-meditation practitioners bring our attention tothe study of the unique interactions among regional neuralnetworks in the brain Scientific approach to the scope of
Exp (stage R)Exp (stage M)
Exp (stage C)Control
065
060
055
050
045F rarr P P rarr F LT rarr RT RT rarr LT
Figure 8 Group averages of RIIs (119878(F rarr P) 119878(P rarr F) 119878(LT rarr
RT) and 119878(RT rarr LT)) for experimental group at three stages andfor control group at rest
Chan meditation provides insight into the mechanism inaddition to the vague sketch of meditation sensation and itsmultiform benefits to human beings This paper presents ourpreliminary results based on nonlinear dynamical theory ofexploring the spatial interactions among brain local neuralnetworks under alpha-rhythmic oscillationQuantification ofnonlinear interdependence based on similarity index revealssignificant intergroup difference Significant higher lateralinteractions between left and right temporal regions wereobserved in Chan-meditation practitioners at the stages ofChan meditation and Chakra-focusing practice In Chanpractice practitioners follow the doctrine that the mind canbe enlightened only if it surrenders its leadership power tothe ldquoheartrdquo (Bodhi the true self with eternal wisdom) Theyaccordingly can experience better balance and integrationof the brain hemispheres through years of Chan-meditationpractice
Chan-Chakra spiritual focusing (at stage C) remarkablystrengthens the central neural-network dominance over theother regions On the other hand suppression of the sourceactivity in regions F and P at stage C appears to reveal themeditation state of transcending the realm of physical bodyand mind The particular central (FCz-Cz-CPz) dominatingphenomenon is reflected in long-term Chan practitioners asone of the metamorphosing processes that opens the energypathway between Chan Chakra and the central-line scalpfrom acupoint DU20 to DU22 (Figure 10(b) in Appendix)In the case practitioners experience tranquil brain and calmmind in every moment Chan-meditation practice is to real-ize a Chan-style brain and Chan-style physical body insteadof merely sitting still for one hour to pursue temporary peaceof mind and relief of body
Appendix
Chan meditation originating more than 2500 years ago hasbeen proved to benefit the health while on the way toward theultimate Buddhahood state Buddha Shakyamuni disclosedthe eternal truth the supreme wisdom the noumenal energy
10 Evidence-Based Complementary and Alternative Medicine
Source070
065
060
055
050
F P C LT RT
Exp (R)Exp (M)
Exp (C)Control
(a)
Sink070
065
060
055
050
F P C LT RT
Exp (R)Exp (M)
Exp (C)Control
(b)
Figure 9 Comparison of average effectiveness of each region as a source (a) or a sink (b) between experimental and control groups
Chan Chakra
(a)
DU20
DU21DU22
Anteriorhairline
Posteriorhairline
(b)
Figure 10 (a) Location of the Chan Chakra (inside the third ventricle) (b) Illustration of acupoints DU20 (Baihui) DU21 (Qianding) andDU22 (Xinhui) on DU meridian
and the natural powers of the universe in Chan meditationunder a linden tree The orthodox Chan Buddhism wasoriginated by such an exceptional affair that Buddha Shakya-muni transmitted this light of supreme wisdom to the GreatKashiyapa The same path towards perfect enlightenment(Buddhahood) was promulgated in mainland China in 527
by Bodhidharma the 28th patriarch The current patriarchis Chan master Wu Jue Miao Tian the 85th patriarch of theorthodox Chan-Buddhism Sect since the Great KashiyapaIn orthodox Chan-Buddhist practice very few disciples wereable to catch the quintessence since it cannot be taught inany form of lectures Written material and spoken words
Evidence-Based Complementary and Alternative Medicine 11
cannot promulgate the true wisdom of Chan which can onlybe conveyed by the Buddhist Heart-seal Imprint from a truemaster
In Chan meditation practitioners aim to attain the trueself (Buddha nature) with eternal wisdom (Bodhi) throughbody-mind-soul purification Substantially speaking suchpurification procedure involves the journal of transcendingthe physiological state (five sensory organs) themental activ-ities and normal consciousness the subliminal (the manas)consciousness and the Alaya state at which practitioners areable to perceive the sacred light emitted from Buddha natureBuddhist Heart-seal Imprint from the Chan Patriarch is amust to assist in the purification and accomplishment Toprepare for attaining such realm practitioners meditate withfull-lotus half-lotus or leg-crossing posture and sit still tocultivate spiritual Reiki for penetrating into the ten importantChakras In the course of Chan meditation practitionersmust switch their normal chest breathing to the Navel-Chakra breathing (also called ldquofetal breathingrdquo) that is thebreathing scheme for entering into deep meditation Amongthe ten Chakras Chan Chakra locating inside the thirdventricle is the Buddhist paradise implemented in our bodyFigure 10(a) illustrates the location of Chan Chakra
The cun-measurand system is normally used to measureand locate the acupoints To determine the locations ofacupoints DU20 DU21 and DU22 on Governor Vesselmeridian (DU meridian) we first measure the scalp-midlinelength between anterior hairline and posterior hairline thatis divided into 12 cuns The locations are defined as follows
DU20 7 cuns above the posterior hairline and 5 cunsabove the anterior hairlineDU21 35 cuns directly above the anterior hairline or15 cuns anterior to DU20DU22 2 cuns posterior to the anterior hairline or3 cuns anterior to DU20
Acknowledgments
The authors would like to thank Shung-Yu Yo for his assis-tance in data analysis Chan-meditation practitioners of theShakyamuni Buddhist Foundation are gratefully acknowl-edged for their enthusiastic participation in this research asvolunteers This research was supported by the grants fromthe National Science Council of Taiwan (Grant no NSC 100-2221-E-009-006-MY2)
References
[1] T YuH L Tsai andM LHwang ldquoSuppressing tumor progres-sion of in vitro prostate cancer cells by emitted psychosomaticpower through Zen meditationrdquo American Journal of ChineseMedicine vol 31 no 3 pp 499ndash507 2003
[2] K H Coker ldquoMeditation and prostate cancer integrating amindbody interventionwith traditional therapiesrdquo Seminars inUrologic Oncology vol 17 no 2 pp 111ndash118 1999
[3] D Lester ldquoZen and happinessrdquo Psychological Reports vol 84no 2 pp 650ndash651 1999
[4] C R K MacLean K G Walton S R Wenneberg et alldquoEffects of the transcendental meditation program on adaptivemechanisms changes in hormone levels and responses to stressafter 4 months of practicerdquo Psychoneuroendocrinology vol 22no 4 pp 277ndash295 1997
[5] GA Tooley SMArmstrong T RNorman andA Sali ldquoAcuteincreases in night-time plasma melatonin levels following aperiod of meditationrdquo Biological Psychology vol 53 no 1 pp69ndash78 2000
[6] Y-Y Tang Y Ma Y Fan et al ldquoCentral and autonomicnervous system interaction is altered by short-termmeditationrdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 106 no 22 pp 8865ndash8870 2009
[7] A Lutz H A Slagter N B Rawlings A D Francis LL Greischar and R J Davidson ldquoMental training enhancesattentional stability neural and behavioral evidencerdquo Journal ofNeuroscience vol 29 no 42 pp 13418ndash13427 2009
[8] S M Bertisch C C Wee R S Phillips and E P McCarthyldquoAlternative mind-body therapies used by adults with medicalconditionsrdquo Journal of Psychosomatic Research vol 66 no 6 pp511ndash519 2009
[9] W R Marchand ldquoMindfulness-based stress reductionmindfulness-based cognitive therapy and zen meditation fordepression anxiety pain and psychological distressrdquo Journalof Psychiatric Practice vol 18 no 4 pp 233ndash2252 2012
[10] B R Cahn and J Polich ldquoMeditation states and traits EEG ERPand neuroimaging studiesrdquoPsychological Bulletin vol 132 no 2pp 180ndash211 2006
[11] F Travis and J Shear ldquoFocused attention open monitoring andautomatic self-transcending categories to organize meditationsfrom Vedic Buddhist and Chinese traditionsrdquo Consciousnessand Cognition vol 19 no 4 pp 1110ndash1118 2010
[12] P-C Lo M-L Huang and K-M Chang ldquoEEG alpha blockingcorrelated with perception of inner light during Zen medita-tionrdquo American Journal of Chinese Medicine vol 31 no 4 pp629ndash642 2003
[13] H C Liao and P C Lo ldquoInvestigation on spatiotemporalcharacteristics of zen-meditation EEG rhythmsrdquo Journal ofInternational Society of Life Information Science vol 25 no 1pp 63ndash71 2007
[14] H-Y Huang and P-C Lo ldquoEEG dynamics of experienced zenmeditation practitioners probed by complexity index and spec-tral measurerdquo Journal of Medical Engineering and Technologyvol 33 no 4 pp 314ndash321 2009
[15] E K St Louis and E P Lansky ldquoMeditation and epilepsy a stillhung juryrdquoMedical Hypotheses vol 67 no 2 pp 247ndash250 2006
[16] L I Aftanas and S A Golocheikine ldquoHuman anterior andfrontal midline theta and lower alpha reflect emotionallypositive state and internalized attention high-resolution EEGinvestigation of meditationrdquo Neuroscience Letters vol 310 no1 pp 57ndash60 2001
[17] K Ansari-Asl J-J Bellanger F Bartolomei F Wendung andL Senhadji ldquoTime-frequency characterization of interdepen-dencies in nonstationary signals application to epileptic EEGrdquoIEEE Transactions on Biomedical Engineering vol 52 no 7 pp1218ndash1226 2005
[18] F Gans A Y Schumann J W Kantelhardt T Penzel and IFietze ldquoCross-modulated amplitudes and frequencies charac-terize interacting components in complex systemsrdquo PhysicalReview Letters vol 102 no 9 Article ID 098701 2009
12 Evidence-Based Complementary and Alternative Medicine
[19] J Bhattacharya H Petsche and E Pereda ldquoInterdependenciesin the spontaneous EEG while listening to musicrdquo InternationalJournal of Psychophysiology vol 42 no 3 pp 287ndash301 2001
[20] C J Stam ldquoNonlinear dynamical analysis of EEG and MEGreview of an emerging fieldrdquo Clinical Neurophysiology vol 116no 10 pp 2266ndash2301 2005
[21] W Singer ldquoConsciousness and the binding problemrdquo Annals ofthe New York Academy of Sciences vol 929 pp 123ndash146 2001
[22] D Calitoiu B J Oommen and D Nussbaum ldquoLarge-scaleneuro-modeling for understanding and explaining some brain-related chaotic behaviorrdquo Simulation-Transactions of the Societyfor Modeling and Simulation International vol 88 no 11 pp1316ndash1337 2012
[23] F Wendling K Ansari-Asl F Bartolomei and L SenhadjildquoFrom EEG signals to brain connectivity a model-based eval-uation of interdependence measuresrdquo Journal of NeuroscienceMethods vol 183 no 1 pp 9ndash18 2009
[24] H Y Huang and P C Lo ldquoEEG nonlinear interdependencemeasure of brain interactions under zen meditationrdquo Journalof Biomedical Engineering Research vol 29 no 4 pp 286ndash2942008
[25] M Breakspear and J R Terry ldquoDetection and description ofnon-linear interdependence in normal multichannel humanEEG datardquo Clinical Neurophysiology vol 113 no 5 pp 735ndash7532002
[26] M Breakspear and J R Terry ldquoTopographic organizationof nonlinear interdependence in multichannel human EEGrdquoNeuroImage vol 16 no 3 pp 822ndash835 2002
[27] C J Stam M Breakspear A-M van Cappellen van Walsumand B W van Dijk ldquoNonlinear synchronization in EEG andwhole-headMEG recordings of healthy subjectsrdquoHuman BrainMapping vol 19 no 2 pp 63ndash78 2003
[28] U Feldmann and J Bhattacharya ldquoPredictability improvementas an asymmetrical measure of interdependence in bivariatetime seriesrdquo International Journal of Bifurcation and Chaos vol14 no 2 pp 505ndash514 2004
[29] M Rubinov S A Knock C J Stam et al ldquoSmall-worldproperties of nonlinear brain activity in schizophreniardquoHumanBrain Mapping vol 30 no 2 pp 403ndash416 2009
[30] P Mirowski D Madhavan Y LeCun and R KuznieckyldquoClassification of patterns of EEG synchronization for seizurepredictionrdquo Clinical Neurophysiology vol 120 no 11 pp 1927ndash1940 2009
[31] S I Dimitriadis N A Laskaris Y del Rio-Portilla and G CKoudounis ldquoCharacterizing dynamic functional connectivityacross sleep stages from EEGrdquo Brain Topography vol 22 no 2pp 119ndash133 2009
[32] K Sibsambhu and R Aurobinda ldquoEffect of sleep deprivation onfunctional connectivity of EEG channelsrdquo IEEE Transcations onSystems Man and Cybernetics vol 43 no 3 pp 666ndash672 2013
[33] C M W J M Tian Chan Master Miao Tianrsquos Book of Wisdomand the Guide to Heart Chan Meditation Lulu 2010
[34] X-S Zhang R J Roy and E W Jensen ldquoEEG complexity as ameasure of depth of anesthesia for patientsrdquo IEEE Transactionson Biomedical Engineering vol 48 no 12 pp 1424ndash1433 2001
[35] I Daubechies Ten Lectures on Wavelets Society for Industrialand Applied Mathematics Philadelphia Pa USA 1992
[36] C Heil D F Walnut and I Daubechies Fundamental Papersin Wavelet Theory Princeton University Press Princeton NJUSA 2006
[37] C Y Liu and P C Lo ldquoSpatial focalization of zen-meditationbrain based on EEGrdquo Journal of Biomedical EngineeringResearch vol 29 pp 17ndash24 2008
[38] H Adeli Z Zhou and N Dadmehr ldquoAnalysis of EEG recordsin an epileptic patient using wavelet transformrdquo Journal ofNeuroscience Methods vol 123 no 1 pp 69ndash87 2003
[39] F Takens ldquoDetecting strange attractors in turbulencerdquo inDynamical Systems and Turbulence D A Rand and L S YoungEds vol 898 of Lecture Notes in Mathematics pp 366ndash381Springer New York NY USA 1981
[40] P-C Lo and W-P Chung ldquoAn approach to quantifying themulti-channel EEG spatial-temporal featurerdquo Biometrical Jour-nal vol 42 no 7 pp 901ndash916 2000
[41] W S Pritchard and D W Duke ldquoDimensional analysis of no-task human EEG using the Grassberger-Procaccia methodrdquoPsychophysiology vol 29 no 2 pp 182ndash192 1992
[42] R Q Quiroga A Kraskov T Kreuz and P GrassbergerldquoPerformance of different synchronization measures in realdata a case study on electroencephalographic signalsrdquo PhysicalReview E vol 65 no 4 Article ID 041903 14 pages 2002
Then for two strongly synchronized systems both self andmutual neighborsmostly coincide so that119877(119870)
119894(119883) asymp 119877
(119870)
119894(119883 |
119884) ≪ 119877119894(119883) whereas for independent systems mutual
neighbors aremore scattered that leads to119877(119870)119894(Χ) ≪ 119877
(119870)
119894(Χ |
119884) asymp 119877119894(119883) Accordingly the degree of interdependence
of these two systems is reflected by the similarities (ordissimilarities) between these two cloud patterns formed byself andmutual neighborsThe strength of similarity betweenthese two point clouds is termed as similarity index 119878 [24 37]and is defined as follows
119878(119870)
(119883 | 119884) =1
119873
119873
sum119894=1
119877(119870)
119894(119883)
119877(119870)
119894(119883 | 119884)
(4)
119878(119870)(119883 | 119884) assesses the statistical dependence of the
state-space structure ofX on that ofY in the sense of testifyingwhether closeness in X implies closeness in Y and vice versaTwo identical systems with the same sets of self and mutualneighbors result in the maximum similarity index (119878 =
1) whereas the index is close to zero (119878 asymp 0) for com-pletely independent systems The opposite interdependence(119878(119870)(119884 | 119883)) can be computed analogically Notice that
similarity indexes are in general asymmetric that is 119878(119870)(119884 |
119883) = 119878(119870)(119883 | 119884) 119878(119870)(119883 | 119884) evaluates the effect of system Y
on system X From the point of view of the system theory
signal Y is regarded as the source or the active role in theinteraction while signal X plays a passive role (a sink) Onthe other hand 119878(119870)(119884 | 119883) analysis considers Y as the sinkthat plays the passive role [24 37]
The asymmetry of 119878 is one of the main advantagesover the other nonlinear measures such as the mutualinformation and the phase synchronizations The fact that119878 is asymmetric allows us to study not only topographicpatterns but also functional properties By considering eachEEG electrode either as a sink or as a source in the nonlinear-interdependence interaction we may thereby further explorethe brain functional topological profile and the direction ofinteraction among local neuronal networks [19] For examplethe condition of 119878(119884 | 119883) gt 119878(119883 | 119884) indicates thatY depends more on X than vice versa In other words Xhas a greater influence on Y than vice versa In such acase X is said to be more active and Y is more passive Byconsidering each electrode either as a sink or as a source inthe nonlinear dynamical interaction we may thereby explorethe spatial direction of the interaction and the dominance oflocal neuronal networks under Chan meditation [42]
In order to maximize the sensitivity to the underlyingsynchronization and gain the robustness against noise weproposed a modified version of 119878measure with an adjustablerange of 119870NN Following our previous study of dimensionalcomplexity index [27 28] a reliable estimate of dimen-sional complexity of a system was obtained by averagingthe complexity indexes over a moderate range of 119870rsquos Asmall 119870 causes superimposed noise while a large 119870 resultsin a measurement involving multimodal effects [27] Todetermine a robust measure against noise it follows that thefinal estimate of nonlinear interdependence is the average119878(119870)(119883 | 119884) over an appropriate range of 119870rsquos and is denoted
by 119878(119883 | 119884)In the practical implementation previous studies of
dimensional complexity for meditation EEG have establisheda moderate choice of parameters The time delay 120591 can bedetermined by the first zero-crossing of the correspondingautocorrelation function Embedding dimension 119898 can bedetermined by the convergent estimate of dimensionalityThewindow length 119873 is selected to encompass the stabilizationof dynamical behavior in the phase space in the sense ofthe convergent estimate of quantitative nonlinear dynami-cal property of reconstructed EEG trajectory for examplecorrelation dimension As a consequence the implementingparameters were selected to be 120591 = 5 (sample points)119898 = 10andwindow length119873 = 1 000 sample points (5 seconds) thatensure convergent and reliable estimates [24 27 28]The finalestimate 119878(119883 | 119884) was obtained by averaging the 119878(119870)(119883 | 119884)
for119870 ranging from 20 to 35
233 Outline of the Scheme The entire scheme employed inthis study is illustrated in Figure 3 that integrates differenttheories and methods to evaluate the nonlinear interdepen-dence for multichannel EEG
To investigate the nonlinear-interdependent behaviorsof alpha activities CWT is employed to identify alpha-dominated epochs in the entire EEG record AnEEG segment
Evidence-Based Complementary and Alternative Medicine 5
X
1 2
3
4
567
8 9
1011
1213
14
15
16
17
18
19
20
2122
r2j = 1 3 4 5 6 7 15 16 17 18
(a)
Y
12
34
5
6
7
8
9
10
11
12
13
1415
1617
18
19
20
21
22
(b)
X
1 2
3
4
56
7
8 9
10
11
12
13
14
15
16
17
18
19
20
2122
(c)
Y
1
2
34
5
6
7
8
9
10
11
12
13
14
15
1617
18
19
20
21
22
s2j = 1 3 5 11 12 13 14 15 21 22
(d)
Figure 2 Illustration for (a) self neighbors 1198831199032119895
( ⃝) (b) state points in 119884 and (c) mutual neighbors 1198831199042119895
() where the indexes 1199042119895
aredetermined from the indexes of (d)119870NN of 119884
Figure 3 Scheme for evaluating nonlinear interdependence ofmultichannel EEG
is identified to be alpha dominant if the percentage of120572 powerto the total power is at least 50 in more than 15 channels(one half of the total channels) Figure 4 displays the resultsof interpreting the 5-second EEG recorded from channels OzCz and Fz The alpha-power percentage (denoted as 120588) foreach one-second epoch is listed beneath the EEG tracingThe5-second EEG tracing is plotted with the amplitude rangingfrom minus50120583V to 50120583V Parameter 120588 evaluated for differentchannels may reflect the focalized behavior of alpha activity
To extend the capacity of assessing the neural-networkinteraction the source119883
119895can be generalized as an integrated
local network involving 119871 active electrode sites so that 119878119901(119883119894)
becomes the average of 119871rsquos 119878(119883119894| 119883119895) assuming119883
119895= 119883119894
119878119901(119883119894) =
1
119871sum119895
119878 (119883119894| 119883119895) (5)
Equation (5) then evaluates the integrative effects of 119871 activeelectrodes on119883
119894 On the other hand the influence of an active
6 Evidence-Based Complementary and Alternative Medicine
50
0
minus500 05 1 15 2 25 3 35 4 45 5
Time (s)120588 58 59 52 55 60
(a) Oz
50
0
minus500 05 1 15 2 25 3 35 4 45 5
Time (s)120588 56 60 50 51 60
(b) Cz
50
0
minus500 05 1 15 2 25 3 35 4 45 5
Time (s)120588 62 61 51 59 60
(c) Fz
Figure 4 Percentage of alpha power to total power for each one-second epoch of the five-second EEG segments (amplitude in 120583V)recorded from (a) Oz (b) Cz and (c) Fz
electrode119883119895on the integrative neural network encompassed
by 119871 passive electrodes (119883119894) can be evaluated by
119878119886(119883119895) =
1
119871sum119894
119878 (119883119894| 119883119895) (6)
assuming119883119894= 119883119895 Both 119878
119901(119883119894) and 119878
119886(119883119895) are called regional
interdependence index (RII)In Chan-meditation practice practitioners often focus on
five regions alternately frontal posterior left right and cen-tral regions after activating the Chan Chakra inside the thirdventricle The purpose is to eliminate the stream of jumbledthoughts and produce a tranquil mind To investigate theeffect of such regional focusing we accordingly divided 30EEG recording sites into five regions
frontal (F) Fp1 Fp2 F7 F3 Fz F4 and F8posterior (P Parietal + Occipital) O1 Oz O2 P7 P3Pz P4 and P8central (C) FCz Cz and CPzleft Temporal (LT) FC3 FT7 T7 C3 TP7 and CP3right Temporal (RT) FC4 FT8 T8C4 TP8 andCP4
3 Results and Discussion
31 Interdependence Matrix of Chan-Meditation EEG Con-sider a given source signal Y The influence of source signalY on sink signal X 119878(X | Y) can be expressed as a 30 times
30 interdependence matrix with the element 119878119894119895= 119878(119883
119894| 119884119895)
denoting the coupling strength of interaction of the source119884119895affecting the sink 119883
119894 The similarity index (SI) was
calculated for 870 (30 times 29) electrode pairs As displayed inFigure 5(a) the color image encoded the quantities in the 30times 30 interdependence matrix S The right-side color chartencodes the strength level of 119878
119894119895 from blue to red indicating
the range of 119878 from the smallest to the largest value EEGchannels are in the order of (from topleft) O2 Oz O1 P7P3 Pz P4 P8 TP8 CP4 CPz CP3 TP7 T7 C3 Cz C4 T8FT8 FC4 FCz FC3 FT7 F7 F3 Fz F4 F8 Fp2 and Fp1 Forexample the box at the lower-left corner characterizes theeffect of O2 channel on Fp1 channel as denoted by 119878(Fp1 |
O2) Accordingly the first row reveals the effect of sourceO2Oz and Fp1 respectively on sink O2 On the other handthe first column indicates how source O2 affects sink O2 Oz and Fp1 respectivelyThe dark red along the diagonal lineindicates the highest similarity index 119878 = 1 when the sourceand sink signals are identical
This figure exhibits some typical behavior in the 119878matrixthat is stronger interdependence occurs in the pairs ofnearby EEG channels On the other hand weaker interactionis measured as two channels are much apart Moreoverbox (119894 119895) does not equal its transposed partner box (119895 119894)indicating the asymmetry of 119878 matrix Figures 5(b)ndash5(d)display the top viewof brain topographicmapping of 119878
119886(FP1)
119878119886(FP2) and 119878
119886(Oz) extracted respectively from the 30th
29th and 2nd columns of Figure 5(a) The topographicmapping was plotted by the function topoplotm providedby EEGLab The mappings exhibit the efficacy of the givenchannel acting as the source role The results in Figures 5(b)to 5(d) reveal the right-frontal dominance The occipitalchannels are comparably less active with respect to the frontalneuronal networks Such weaker influence of occipital andposterior regions on the other regions can be clearly observedfrom the blue color dominating in the left three columns of Smatrix (Figure 5(a)) corresponding to the source at O2 Ozand O1
32 Inter-Region Interdependence AnalysismdashExperimentalGroup Inter-regional nonlinear interdependence was ana-lyzed for EEG recorded in three different sessions (stage RM and C) Due to the premeditation brain-drilling practicedescribed in previous section we particularly focused onthe left-right temporal (LT-RT) and frontal-posterior (F-P)neural-network interactions For example 119878(F rarr P) iscomputed by averaging all 119878
119886(119883119895) in (6) for all 119883
119895isin F and
119883119894isin P to assess the integrative source effect of all electrodes
in frontal region driving the posterior region On the otherhand 119878(P rarr F) is computed by averaging all 119878
119886(119883119895) in
(6) for all 119883119895isin P and 119883
119894isin F when all the electrodes in
the posterior region play the source role to drive the frontalregion
Table 1 lists the group averages and standard deviationsof 119878(F rarr P) 119878(P rarr F) 119878(LT rarr RT) and 119878(RT rarr
LT) at three experimental stages (R M and C) Evidently119878(F rarr P) is consistently greater than 119878(P rarr F) for all threestages The 119875 values (00055 00031 and 00302) of pairedsample 119905-test are all smaller than 005 that demonstrates the
Evidence-Based Complementary and Alternative Medicine 7
Figure 5 SI analysis for experienced practitioner during Chanmeditation (StageM) (a) 30 times 30 Smatrix and brain topographical mappings(top view) of (b) 119878
119886(FP1) (c) 119878
119886(FP2) and (d) 119878
119886(Oz) indicating the average driving strength of the EEG sites FP1 FP2 and Oz
070
065
060
055
050
045
040
Source
Stage RStage MStage C
F P C LT RT
(a)
Sink070
065
060
055
050
045
040
Stage RStage MStage C
F P C LT RT
(b)
Figure 6 Average effectiveness of each region playing the role of a source (a) and sink (b) Three bars in each RII cluster correspond to threeexperimental stages
statistical significance of frontal-alpha dominance at all threestages On the other hand results of the left-right temporalanalysis of nonlinear interdependence reveal no distinctlydominant role of the laterally neural-network operation thatis 119878(LT rarr RT) asymp 119878(RT rarr LT) The higher 119875 values forthe 119878(LT rarr RT)-119878(RT rarr LT) paired 119905-test indicate nostatistically significant difference between two sets of resultsWe may further infer the balancing operations between theleft-brain and right-brain hemispheres
Our results demonstrate that interactions between leftand right hemispheres are much more intensive than theinteractions between frontal and posterior regions with 119875 =
00016 considering all the experimental subjects at all threestages
Figure 6 provides an alternative viewpoint for exploringhow a given region of interest ROI (F P C LT or RT)influences or is influenced by the other regions In Figure 6left (right) group of five 3-bar clusters corresponds to theaverage effectiveness of each region playing the active (pas-sive) role at three stages For example the leftmost barindicates the average of 119878(F rarr P) 119878(F rarr LT) 119878(F rarr
RT) and 119878(F rarr C) for stage R while the rightmostbar indicates the average of 119878(F rarr RT) 119878(P rarr RT)119878(C rarr RT) and 119878(LT rarr RT) for stage C Among allfive regions posterior region as either the source or sinkapparently exhibits the weakest link to the other regions Inaddition the effectiveness of active role of posterior regionis weaker than that of passive role The results strongly
8 Evidence-Based Complementary and Alternative Medicine
Table 1 Group averages and standard deviations of 119878(FrarrP) 119878(Prarr F) 119878(LTrarrRT) and 119878(RTrarr LT) at three experimental stages (R Mand C) including the 119875 values of student 119905-test for 119878(FrarrP)-119878(Prarr F) and 119878(LTrarrRT)-119878(RTrarr LT) pairs
Group average 056 051 060 061Group std 005 005 007 005119875 value 00055 03476
MGroup average 056 050 060 061Group std 003 006 006 004119875 value 00031 01987
CGroup average 055 049 061 061Group std 007 006 006 006119875 value 00302 03953
suggest the inactive behaviors of parietal-occipital lobes sinceregion P encompasses the EEG-electrode sites of parietal andoccipital lobesThe parietal lobe is responsible for integratingsensory information from various parts of the body withthe particular functions of determining spatial sense andnavigation Functions of occipital lobe mainly include visualreception visual-spatial processing and color recognitionAs described previously the core essence of orthodox Chan-meditation practice is to transcend physiological mental andall states of consciousness to prove the existence of true beingThe inactive posterior regions may provide the evidence ofbrain rewiring in preparation for such transcendence
Region C encompasses three midline electrodes locatingfrom precentral to postcentral cortex Region C as the sourceapparently dominates over the other four regions regardlessof the stages On the other hand region C as the passive role isaffected mostly among the five regions Region C constantlyexhibits the largest RII at all stages
Wemay draw a tentative hypothesis from the mechanismof Chan-meditation practice Practitioners are required tokeep Chan Chakra active at any moment that results inthe formation of an energy pathway between Chan Chakraand Qian-Ding acupoint on scalp (Figure 10(b)) Does suchphysiological reformation correlate to the significant effec-tiveness of region C It leaves an open question for futureinvestigation
RII characterizing the regional interdependence behavesdifferently for each region when the experimental subjectsswitch their mental states from R (resting) to M (medita-tion) or from R to C (Chakra focusing) To investigate theeffect of different experimental sessions the RII percentageincreasedecrease from stage R to M and from stage R to Cwere computed for each of the five regions (F P C LT andRT)acting as either the active or the passive role In comparisonof RII between stage M and stage R the percentage largerthan 1 was observed in the regions of LTactive(minus124)RTactive (125) and Cpassive (minus107) On the other handthe regions of significant change in RII when comparingstage C with R include Factive (minus184) Pactive (minus178) andCactive (239) On the basis of RII of stage R for each
individual region we summarize the changes of RII at stagesM and C as follows
(1) In the active-role analysis region LT becomes moredeactivated at stage M while region RT becomesmore activatedWhenmeditation subjects focused onChan Chakra the active driving strength of regionC increases significantly (239) On the other handsuppression of the source activity occurs to bothregions F and P (the regions anterior to and posteriorto region C)
(2) In the passive-role analysis only region C becomesnotably deactivated at stage M (free meditation) Ingeneral differences are trivial in comparison of119877119868119868passive between stages M and R
(3) Chan meditation deactivates the left brain hemi-sphere whereas it inactivates the right brain hemi-sphere
Except for region P the active-role effectiveness of a givenregion is better than its passive-role effectiveness
33 Inter-Region Interdependence AnalysismdashControl GroupIn control group the group average and standard deviationof 119878(F rarr P) 119878(P rarr F) 119878(LT rarr RT) and 119878(RT rarr LT) atstage R are respectively 055 plusmn 004 051 plusmn 004 059 plusmn 003and 058 plusmn 004 The 119875 values of student 119905-test for 119878(F rarr
P)-119878(P rarr F) and 119878(LT rarr RT)-119878(RT rarr LT) pairs are0002 and 0457The results also reveal the frontal dominanceand left-right lateral balance for the control group at rest Yetcompared with the Chan-meditation practitioners controlgroup exhibits weaker strength of effectiveness no matter ifthe region plays an active or a passive role
To explore the average effectiveness of a given ROI weaveraged the RIIs for the region in connection with the otherfour regions Figure 7 displays how a given ROI (F P C LT orRT) influences (active) or is influenced (passive) by the otherregions Similar to the results of experimental group regionP as either the active or passive role exhibits the weakest linksto the other regions
Evidence-Based Complementary and Alternative Medicine 9
Sink
Source
070
065
060
055
050
045
040F P C LT RT
Figure 7 Average effectiveness of each region playing either theactive or passive role
Comparing the efficacy of two counteractive roles playedby the same region we observe that the source-role effective-ness of a given ROI is higher than its sink-role effectivenessexcept region P
34 Comparison between Experimental and Control GroupsFigure 8 illustrates the group averages of RIIs including119878(F rarr P) 119878(P rarr F) 119878(LT rarr RT) and 119878(RT rarr LT)for the experimental group at three stages (R M and C)and for the control group at rest Experimental group revealsmuch more intensive lateral (LT larrrarr RT) interactions thancontrol group The differences are statistically significant forexperimental group at stage M (119875 = 00336) and at stage C(119875 = 00411) On the other hand region P responsible forspatial sense and navigation becomes comparatively inactivefor Chan-meditation practitioners at stage C
The assembling illustration in Figure 9 is used to comparethe average effectiveness of each region between two groupsExperimental group playing either a source role or a sinkrole apparently exhibits higher average effectiveness in allfive regions The extraordinarily large RIIs for region Cparticularly acting the source role may be assumed to becorrelated with the strengthening of neural networks ofregion C dominating over the other regions through thespiritual focusing on Chan Chakra According to the post-experimental interview with Chan-meditation practitionerssuch central (FCz-Cz-CPz) dominating behavior could belinked to theChan-Chakra activation that further induces theperception of grand solemn energy flow in and out throughthe cortical regions defined by acupoints DU20 (Baihui)DU21 (Qianding) and DU22 (Xinhui) in TCM (traditionalChinese Medicine) Figure 10(b) (Appendix) illustrates thelocations of these three acupoints
4 Conclusion
The time-transcending nonmaterial sacred spiritual experi-ences of Chan-meditation practitioners bring our attention tothe study of the unique interactions among regional neuralnetworks in the brain Scientific approach to the scope of
Exp (stage R)Exp (stage M)
Exp (stage C)Control
065
060
055
050
045F rarr P P rarr F LT rarr RT RT rarr LT
Figure 8 Group averages of RIIs (119878(F rarr P) 119878(P rarr F) 119878(LT rarr
RT) and 119878(RT rarr LT)) for experimental group at three stages andfor control group at rest
Chan meditation provides insight into the mechanism inaddition to the vague sketch of meditation sensation and itsmultiform benefits to human beings This paper presents ourpreliminary results based on nonlinear dynamical theory ofexploring the spatial interactions among brain local neuralnetworks under alpha-rhythmic oscillationQuantification ofnonlinear interdependence based on similarity index revealssignificant intergroup difference Significant higher lateralinteractions between left and right temporal regions wereobserved in Chan-meditation practitioners at the stages ofChan meditation and Chakra-focusing practice In Chanpractice practitioners follow the doctrine that the mind canbe enlightened only if it surrenders its leadership power tothe ldquoheartrdquo (Bodhi the true self with eternal wisdom) Theyaccordingly can experience better balance and integrationof the brain hemispheres through years of Chan-meditationpractice
Chan-Chakra spiritual focusing (at stage C) remarkablystrengthens the central neural-network dominance over theother regions On the other hand suppression of the sourceactivity in regions F and P at stage C appears to reveal themeditation state of transcending the realm of physical bodyand mind The particular central (FCz-Cz-CPz) dominatingphenomenon is reflected in long-term Chan practitioners asone of the metamorphosing processes that opens the energypathway between Chan Chakra and the central-line scalpfrom acupoint DU20 to DU22 (Figure 10(b) in Appendix)In the case practitioners experience tranquil brain and calmmind in every moment Chan-meditation practice is to real-ize a Chan-style brain and Chan-style physical body insteadof merely sitting still for one hour to pursue temporary peaceof mind and relief of body
Appendix
Chan meditation originating more than 2500 years ago hasbeen proved to benefit the health while on the way toward theultimate Buddhahood state Buddha Shakyamuni disclosedthe eternal truth the supreme wisdom the noumenal energy
10 Evidence-Based Complementary and Alternative Medicine
Source070
065
060
055
050
F P C LT RT
Exp (R)Exp (M)
Exp (C)Control
(a)
Sink070
065
060
055
050
F P C LT RT
Exp (R)Exp (M)
Exp (C)Control
(b)
Figure 9 Comparison of average effectiveness of each region as a source (a) or a sink (b) between experimental and control groups
Chan Chakra
(a)
DU20
DU21DU22
Anteriorhairline
Posteriorhairline
(b)
Figure 10 (a) Location of the Chan Chakra (inside the third ventricle) (b) Illustration of acupoints DU20 (Baihui) DU21 (Qianding) andDU22 (Xinhui) on DU meridian
and the natural powers of the universe in Chan meditationunder a linden tree The orthodox Chan Buddhism wasoriginated by such an exceptional affair that Buddha Shakya-muni transmitted this light of supreme wisdom to the GreatKashiyapa The same path towards perfect enlightenment(Buddhahood) was promulgated in mainland China in 527
by Bodhidharma the 28th patriarch The current patriarchis Chan master Wu Jue Miao Tian the 85th patriarch of theorthodox Chan-Buddhism Sect since the Great KashiyapaIn orthodox Chan-Buddhist practice very few disciples wereable to catch the quintessence since it cannot be taught inany form of lectures Written material and spoken words
Evidence-Based Complementary and Alternative Medicine 11
cannot promulgate the true wisdom of Chan which can onlybe conveyed by the Buddhist Heart-seal Imprint from a truemaster
In Chan meditation practitioners aim to attain the trueself (Buddha nature) with eternal wisdom (Bodhi) throughbody-mind-soul purification Substantially speaking suchpurification procedure involves the journal of transcendingthe physiological state (five sensory organs) themental activ-ities and normal consciousness the subliminal (the manas)consciousness and the Alaya state at which practitioners areable to perceive the sacred light emitted from Buddha natureBuddhist Heart-seal Imprint from the Chan Patriarch is amust to assist in the purification and accomplishment Toprepare for attaining such realm practitioners meditate withfull-lotus half-lotus or leg-crossing posture and sit still tocultivate spiritual Reiki for penetrating into the ten importantChakras In the course of Chan meditation practitionersmust switch their normal chest breathing to the Navel-Chakra breathing (also called ldquofetal breathingrdquo) that is thebreathing scheme for entering into deep meditation Amongthe ten Chakras Chan Chakra locating inside the thirdventricle is the Buddhist paradise implemented in our bodyFigure 10(a) illustrates the location of Chan Chakra
The cun-measurand system is normally used to measureand locate the acupoints To determine the locations ofacupoints DU20 DU21 and DU22 on Governor Vesselmeridian (DU meridian) we first measure the scalp-midlinelength between anterior hairline and posterior hairline thatis divided into 12 cuns The locations are defined as follows
DU20 7 cuns above the posterior hairline and 5 cunsabove the anterior hairlineDU21 35 cuns directly above the anterior hairline or15 cuns anterior to DU20DU22 2 cuns posterior to the anterior hairline or3 cuns anterior to DU20
Acknowledgments
The authors would like to thank Shung-Yu Yo for his assis-tance in data analysis Chan-meditation practitioners of theShakyamuni Buddhist Foundation are gratefully acknowl-edged for their enthusiastic participation in this research asvolunteers This research was supported by the grants fromthe National Science Council of Taiwan (Grant no NSC 100-2221-E-009-006-MY2)
References
[1] T YuH L Tsai andM LHwang ldquoSuppressing tumor progres-sion of in vitro prostate cancer cells by emitted psychosomaticpower through Zen meditationrdquo American Journal of ChineseMedicine vol 31 no 3 pp 499ndash507 2003
[2] K H Coker ldquoMeditation and prostate cancer integrating amindbody interventionwith traditional therapiesrdquo Seminars inUrologic Oncology vol 17 no 2 pp 111ndash118 1999
[3] D Lester ldquoZen and happinessrdquo Psychological Reports vol 84no 2 pp 650ndash651 1999
[4] C R K MacLean K G Walton S R Wenneberg et alldquoEffects of the transcendental meditation program on adaptivemechanisms changes in hormone levels and responses to stressafter 4 months of practicerdquo Psychoneuroendocrinology vol 22no 4 pp 277ndash295 1997
[5] GA Tooley SMArmstrong T RNorman andA Sali ldquoAcuteincreases in night-time plasma melatonin levels following aperiod of meditationrdquo Biological Psychology vol 53 no 1 pp69ndash78 2000
[6] Y-Y Tang Y Ma Y Fan et al ldquoCentral and autonomicnervous system interaction is altered by short-termmeditationrdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 106 no 22 pp 8865ndash8870 2009
[7] A Lutz H A Slagter N B Rawlings A D Francis LL Greischar and R J Davidson ldquoMental training enhancesattentional stability neural and behavioral evidencerdquo Journal ofNeuroscience vol 29 no 42 pp 13418ndash13427 2009
[8] S M Bertisch C C Wee R S Phillips and E P McCarthyldquoAlternative mind-body therapies used by adults with medicalconditionsrdquo Journal of Psychosomatic Research vol 66 no 6 pp511ndash519 2009
[9] W R Marchand ldquoMindfulness-based stress reductionmindfulness-based cognitive therapy and zen meditation fordepression anxiety pain and psychological distressrdquo Journalof Psychiatric Practice vol 18 no 4 pp 233ndash2252 2012
[10] B R Cahn and J Polich ldquoMeditation states and traits EEG ERPand neuroimaging studiesrdquoPsychological Bulletin vol 132 no 2pp 180ndash211 2006
[11] F Travis and J Shear ldquoFocused attention open monitoring andautomatic self-transcending categories to organize meditationsfrom Vedic Buddhist and Chinese traditionsrdquo Consciousnessand Cognition vol 19 no 4 pp 1110ndash1118 2010
[12] P-C Lo M-L Huang and K-M Chang ldquoEEG alpha blockingcorrelated with perception of inner light during Zen medita-tionrdquo American Journal of Chinese Medicine vol 31 no 4 pp629ndash642 2003
[13] H C Liao and P C Lo ldquoInvestigation on spatiotemporalcharacteristics of zen-meditation EEG rhythmsrdquo Journal ofInternational Society of Life Information Science vol 25 no 1pp 63ndash71 2007
[14] H-Y Huang and P-C Lo ldquoEEG dynamics of experienced zenmeditation practitioners probed by complexity index and spec-tral measurerdquo Journal of Medical Engineering and Technologyvol 33 no 4 pp 314ndash321 2009
[15] E K St Louis and E P Lansky ldquoMeditation and epilepsy a stillhung juryrdquoMedical Hypotheses vol 67 no 2 pp 247ndash250 2006
[16] L I Aftanas and S A Golocheikine ldquoHuman anterior andfrontal midline theta and lower alpha reflect emotionallypositive state and internalized attention high-resolution EEGinvestigation of meditationrdquo Neuroscience Letters vol 310 no1 pp 57ndash60 2001
[17] K Ansari-Asl J-J Bellanger F Bartolomei F Wendung andL Senhadji ldquoTime-frequency characterization of interdepen-dencies in nonstationary signals application to epileptic EEGrdquoIEEE Transactions on Biomedical Engineering vol 52 no 7 pp1218ndash1226 2005
[18] F Gans A Y Schumann J W Kantelhardt T Penzel and IFietze ldquoCross-modulated amplitudes and frequencies charac-terize interacting components in complex systemsrdquo PhysicalReview Letters vol 102 no 9 Article ID 098701 2009
12 Evidence-Based Complementary and Alternative Medicine
[19] J Bhattacharya H Petsche and E Pereda ldquoInterdependenciesin the spontaneous EEG while listening to musicrdquo InternationalJournal of Psychophysiology vol 42 no 3 pp 287ndash301 2001
[20] C J Stam ldquoNonlinear dynamical analysis of EEG and MEGreview of an emerging fieldrdquo Clinical Neurophysiology vol 116no 10 pp 2266ndash2301 2005
[21] W Singer ldquoConsciousness and the binding problemrdquo Annals ofthe New York Academy of Sciences vol 929 pp 123ndash146 2001
[22] D Calitoiu B J Oommen and D Nussbaum ldquoLarge-scaleneuro-modeling for understanding and explaining some brain-related chaotic behaviorrdquo Simulation-Transactions of the Societyfor Modeling and Simulation International vol 88 no 11 pp1316ndash1337 2012
[23] F Wendling K Ansari-Asl F Bartolomei and L SenhadjildquoFrom EEG signals to brain connectivity a model-based eval-uation of interdependence measuresrdquo Journal of NeuroscienceMethods vol 183 no 1 pp 9ndash18 2009
[24] H Y Huang and P C Lo ldquoEEG nonlinear interdependencemeasure of brain interactions under zen meditationrdquo Journalof Biomedical Engineering Research vol 29 no 4 pp 286ndash2942008
[25] M Breakspear and J R Terry ldquoDetection and description ofnon-linear interdependence in normal multichannel humanEEG datardquo Clinical Neurophysiology vol 113 no 5 pp 735ndash7532002
[26] M Breakspear and J R Terry ldquoTopographic organizationof nonlinear interdependence in multichannel human EEGrdquoNeuroImage vol 16 no 3 pp 822ndash835 2002
[27] C J Stam M Breakspear A-M van Cappellen van Walsumand B W van Dijk ldquoNonlinear synchronization in EEG andwhole-headMEG recordings of healthy subjectsrdquoHuman BrainMapping vol 19 no 2 pp 63ndash78 2003
[28] U Feldmann and J Bhattacharya ldquoPredictability improvementas an asymmetrical measure of interdependence in bivariatetime seriesrdquo International Journal of Bifurcation and Chaos vol14 no 2 pp 505ndash514 2004
[29] M Rubinov S A Knock C J Stam et al ldquoSmall-worldproperties of nonlinear brain activity in schizophreniardquoHumanBrain Mapping vol 30 no 2 pp 403ndash416 2009
[30] P Mirowski D Madhavan Y LeCun and R KuznieckyldquoClassification of patterns of EEG synchronization for seizurepredictionrdquo Clinical Neurophysiology vol 120 no 11 pp 1927ndash1940 2009
[31] S I Dimitriadis N A Laskaris Y del Rio-Portilla and G CKoudounis ldquoCharacterizing dynamic functional connectivityacross sleep stages from EEGrdquo Brain Topography vol 22 no 2pp 119ndash133 2009
[32] K Sibsambhu and R Aurobinda ldquoEffect of sleep deprivation onfunctional connectivity of EEG channelsrdquo IEEE Transcations onSystems Man and Cybernetics vol 43 no 3 pp 666ndash672 2013
[33] C M W J M Tian Chan Master Miao Tianrsquos Book of Wisdomand the Guide to Heart Chan Meditation Lulu 2010
[34] X-S Zhang R J Roy and E W Jensen ldquoEEG complexity as ameasure of depth of anesthesia for patientsrdquo IEEE Transactionson Biomedical Engineering vol 48 no 12 pp 1424ndash1433 2001
[35] I Daubechies Ten Lectures on Wavelets Society for Industrialand Applied Mathematics Philadelphia Pa USA 1992
[36] C Heil D F Walnut and I Daubechies Fundamental Papersin Wavelet Theory Princeton University Press Princeton NJUSA 2006
[37] C Y Liu and P C Lo ldquoSpatial focalization of zen-meditationbrain based on EEGrdquo Journal of Biomedical EngineeringResearch vol 29 pp 17ndash24 2008
[38] H Adeli Z Zhou and N Dadmehr ldquoAnalysis of EEG recordsin an epileptic patient using wavelet transformrdquo Journal ofNeuroscience Methods vol 123 no 1 pp 69ndash87 2003
[39] F Takens ldquoDetecting strange attractors in turbulencerdquo inDynamical Systems and Turbulence D A Rand and L S YoungEds vol 898 of Lecture Notes in Mathematics pp 366ndash381Springer New York NY USA 1981
[40] P-C Lo and W-P Chung ldquoAn approach to quantifying themulti-channel EEG spatial-temporal featurerdquo Biometrical Jour-nal vol 42 no 7 pp 901ndash916 2000
[41] W S Pritchard and D W Duke ldquoDimensional analysis of no-task human EEG using the Grassberger-Procaccia methodrdquoPsychophysiology vol 29 no 2 pp 182ndash192 1992
[42] R Q Quiroga A Kraskov T Kreuz and P GrassbergerldquoPerformance of different synchronization measures in realdata a case study on electroencephalographic signalsrdquo PhysicalReview E vol 65 no 4 Article ID 041903 14 pages 2002
Figure 3 Scheme for evaluating nonlinear interdependence ofmultichannel EEG
is identified to be alpha dominant if the percentage of120572 powerto the total power is at least 50 in more than 15 channels(one half of the total channels) Figure 4 displays the resultsof interpreting the 5-second EEG recorded from channels OzCz and Fz The alpha-power percentage (denoted as 120588) foreach one-second epoch is listed beneath the EEG tracingThe5-second EEG tracing is plotted with the amplitude rangingfrom minus50120583V to 50120583V Parameter 120588 evaluated for differentchannels may reflect the focalized behavior of alpha activity
To extend the capacity of assessing the neural-networkinteraction the source119883
119895can be generalized as an integrated
local network involving 119871 active electrode sites so that 119878119901(119883119894)
becomes the average of 119871rsquos 119878(119883119894| 119883119895) assuming119883
119895= 119883119894
119878119901(119883119894) =
1
119871sum119895
119878 (119883119894| 119883119895) (5)
Equation (5) then evaluates the integrative effects of 119871 activeelectrodes on119883
119894 On the other hand the influence of an active
6 Evidence-Based Complementary and Alternative Medicine
50
0
minus500 05 1 15 2 25 3 35 4 45 5
Time (s)120588 58 59 52 55 60
(a) Oz
50
0
minus500 05 1 15 2 25 3 35 4 45 5
Time (s)120588 56 60 50 51 60
(b) Cz
50
0
minus500 05 1 15 2 25 3 35 4 45 5
Time (s)120588 62 61 51 59 60
(c) Fz
Figure 4 Percentage of alpha power to total power for each one-second epoch of the five-second EEG segments (amplitude in 120583V)recorded from (a) Oz (b) Cz and (c) Fz
electrode119883119895on the integrative neural network encompassed
by 119871 passive electrodes (119883119894) can be evaluated by
119878119886(119883119895) =
1
119871sum119894
119878 (119883119894| 119883119895) (6)
assuming119883119894= 119883119895 Both 119878
119901(119883119894) and 119878
119886(119883119895) are called regional
interdependence index (RII)In Chan-meditation practice practitioners often focus on
five regions alternately frontal posterior left right and cen-tral regions after activating the Chan Chakra inside the thirdventricle The purpose is to eliminate the stream of jumbledthoughts and produce a tranquil mind To investigate theeffect of such regional focusing we accordingly divided 30EEG recording sites into five regions
frontal (F) Fp1 Fp2 F7 F3 Fz F4 and F8posterior (P Parietal + Occipital) O1 Oz O2 P7 P3Pz P4 and P8central (C) FCz Cz and CPzleft Temporal (LT) FC3 FT7 T7 C3 TP7 and CP3right Temporal (RT) FC4 FT8 T8C4 TP8 andCP4
3 Results and Discussion
31 Interdependence Matrix of Chan-Meditation EEG Con-sider a given source signal Y The influence of source signalY on sink signal X 119878(X | Y) can be expressed as a 30 times
30 interdependence matrix with the element 119878119894119895= 119878(119883
119894| 119884119895)
denoting the coupling strength of interaction of the source119884119895affecting the sink 119883
119894 The similarity index (SI) was
calculated for 870 (30 times 29) electrode pairs As displayed inFigure 5(a) the color image encoded the quantities in the 30times 30 interdependence matrix S The right-side color chartencodes the strength level of 119878
119894119895 from blue to red indicating
the range of 119878 from the smallest to the largest value EEGchannels are in the order of (from topleft) O2 Oz O1 P7P3 Pz P4 P8 TP8 CP4 CPz CP3 TP7 T7 C3 Cz C4 T8FT8 FC4 FCz FC3 FT7 F7 F3 Fz F4 F8 Fp2 and Fp1 Forexample the box at the lower-left corner characterizes theeffect of O2 channel on Fp1 channel as denoted by 119878(Fp1 |
O2) Accordingly the first row reveals the effect of sourceO2Oz and Fp1 respectively on sink O2 On the other handthe first column indicates how source O2 affects sink O2 Oz and Fp1 respectivelyThe dark red along the diagonal lineindicates the highest similarity index 119878 = 1 when the sourceand sink signals are identical
This figure exhibits some typical behavior in the 119878matrixthat is stronger interdependence occurs in the pairs ofnearby EEG channels On the other hand weaker interactionis measured as two channels are much apart Moreoverbox (119894 119895) does not equal its transposed partner box (119895 119894)indicating the asymmetry of 119878 matrix Figures 5(b)ndash5(d)display the top viewof brain topographicmapping of 119878
119886(FP1)
119878119886(FP2) and 119878
119886(Oz) extracted respectively from the 30th
29th and 2nd columns of Figure 5(a) The topographicmapping was plotted by the function topoplotm providedby EEGLab The mappings exhibit the efficacy of the givenchannel acting as the source role The results in Figures 5(b)to 5(d) reveal the right-frontal dominance The occipitalchannels are comparably less active with respect to the frontalneuronal networks Such weaker influence of occipital andposterior regions on the other regions can be clearly observedfrom the blue color dominating in the left three columns of Smatrix (Figure 5(a)) corresponding to the source at O2 Ozand O1
32 Inter-Region Interdependence AnalysismdashExperimentalGroup Inter-regional nonlinear interdependence was ana-lyzed for EEG recorded in three different sessions (stage RM and C) Due to the premeditation brain-drilling practicedescribed in previous section we particularly focused onthe left-right temporal (LT-RT) and frontal-posterior (F-P)neural-network interactions For example 119878(F rarr P) iscomputed by averaging all 119878
119886(119883119895) in (6) for all 119883
119895isin F and
119883119894isin P to assess the integrative source effect of all electrodes
in frontal region driving the posterior region On the otherhand 119878(P rarr F) is computed by averaging all 119878
119886(119883119895) in
(6) for all 119883119895isin P and 119883
119894isin F when all the electrodes in
the posterior region play the source role to drive the frontalregion
Table 1 lists the group averages and standard deviationsof 119878(F rarr P) 119878(P rarr F) 119878(LT rarr RT) and 119878(RT rarr
LT) at three experimental stages (R M and C) Evidently119878(F rarr P) is consistently greater than 119878(P rarr F) for all threestages The 119875 values (00055 00031 and 00302) of pairedsample 119905-test are all smaller than 005 that demonstrates the
Evidence-Based Complementary and Alternative Medicine 7
Figure 5 SI analysis for experienced practitioner during Chanmeditation (StageM) (a) 30 times 30 Smatrix and brain topographical mappings(top view) of (b) 119878
119886(FP1) (c) 119878
119886(FP2) and (d) 119878
119886(Oz) indicating the average driving strength of the EEG sites FP1 FP2 and Oz
070
065
060
055
050
045
040
Source
Stage RStage MStage C
F P C LT RT
(a)
Sink070
065
060
055
050
045
040
Stage RStage MStage C
F P C LT RT
(b)
Figure 6 Average effectiveness of each region playing the role of a source (a) and sink (b) Three bars in each RII cluster correspond to threeexperimental stages
statistical significance of frontal-alpha dominance at all threestages On the other hand results of the left-right temporalanalysis of nonlinear interdependence reveal no distinctlydominant role of the laterally neural-network operation thatis 119878(LT rarr RT) asymp 119878(RT rarr LT) The higher 119875 values forthe 119878(LT rarr RT)-119878(RT rarr LT) paired 119905-test indicate nostatistically significant difference between two sets of resultsWe may further infer the balancing operations between theleft-brain and right-brain hemispheres
Our results demonstrate that interactions between leftand right hemispheres are much more intensive than theinteractions between frontal and posterior regions with 119875 =
00016 considering all the experimental subjects at all threestages
Figure 6 provides an alternative viewpoint for exploringhow a given region of interest ROI (F P C LT or RT)influences or is influenced by the other regions In Figure 6left (right) group of five 3-bar clusters corresponds to theaverage effectiveness of each region playing the active (pas-sive) role at three stages For example the leftmost barindicates the average of 119878(F rarr P) 119878(F rarr LT) 119878(F rarr
RT) and 119878(F rarr C) for stage R while the rightmostbar indicates the average of 119878(F rarr RT) 119878(P rarr RT)119878(C rarr RT) and 119878(LT rarr RT) for stage C Among allfive regions posterior region as either the source or sinkapparently exhibits the weakest link to the other regions Inaddition the effectiveness of active role of posterior regionis weaker than that of passive role The results strongly
8 Evidence-Based Complementary and Alternative Medicine
Table 1 Group averages and standard deviations of 119878(FrarrP) 119878(Prarr F) 119878(LTrarrRT) and 119878(RTrarr LT) at three experimental stages (R Mand C) including the 119875 values of student 119905-test for 119878(FrarrP)-119878(Prarr F) and 119878(LTrarrRT)-119878(RTrarr LT) pairs
Group average 056 051 060 061Group std 005 005 007 005119875 value 00055 03476
MGroup average 056 050 060 061Group std 003 006 006 004119875 value 00031 01987
CGroup average 055 049 061 061Group std 007 006 006 006119875 value 00302 03953
suggest the inactive behaviors of parietal-occipital lobes sinceregion P encompasses the EEG-electrode sites of parietal andoccipital lobesThe parietal lobe is responsible for integratingsensory information from various parts of the body withthe particular functions of determining spatial sense andnavigation Functions of occipital lobe mainly include visualreception visual-spatial processing and color recognitionAs described previously the core essence of orthodox Chan-meditation practice is to transcend physiological mental andall states of consciousness to prove the existence of true beingThe inactive posterior regions may provide the evidence ofbrain rewiring in preparation for such transcendence
Region C encompasses three midline electrodes locatingfrom precentral to postcentral cortex Region C as the sourceapparently dominates over the other four regions regardlessof the stages On the other hand region C as the passive role isaffected mostly among the five regions Region C constantlyexhibits the largest RII at all stages
Wemay draw a tentative hypothesis from the mechanismof Chan-meditation practice Practitioners are required tokeep Chan Chakra active at any moment that results inthe formation of an energy pathway between Chan Chakraand Qian-Ding acupoint on scalp (Figure 10(b)) Does suchphysiological reformation correlate to the significant effec-tiveness of region C It leaves an open question for futureinvestigation
RII characterizing the regional interdependence behavesdifferently for each region when the experimental subjectsswitch their mental states from R (resting) to M (medita-tion) or from R to C (Chakra focusing) To investigate theeffect of different experimental sessions the RII percentageincreasedecrease from stage R to M and from stage R to Cwere computed for each of the five regions (F P C LT andRT)acting as either the active or the passive role In comparisonof RII between stage M and stage R the percentage largerthan 1 was observed in the regions of LTactive(minus124)RTactive (125) and Cpassive (minus107) On the other handthe regions of significant change in RII when comparingstage C with R include Factive (minus184) Pactive (minus178) andCactive (239) On the basis of RII of stage R for each
individual region we summarize the changes of RII at stagesM and C as follows
(1) In the active-role analysis region LT becomes moredeactivated at stage M while region RT becomesmore activatedWhenmeditation subjects focused onChan Chakra the active driving strength of regionC increases significantly (239) On the other handsuppression of the source activity occurs to bothregions F and P (the regions anterior to and posteriorto region C)
(2) In the passive-role analysis only region C becomesnotably deactivated at stage M (free meditation) Ingeneral differences are trivial in comparison of119877119868119868passive between stages M and R
(3) Chan meditation deactivates the left brain hemi-sphere whereas it inactivates the right brain hemi-sphere
Except for region P the active-role effectiveness of a givenregion is better than its passive-role effectiveness
33 Inter-Region Interdependence AnalysismdashControl GroupIn control group the group average and standard deviationof 119878(F rarr P) 119878(P rarr F) 119878(LT rarr RT) and 119878(RT rarr LT) atstage R are respectively 055 plusmn 004 051 plusmn 004 059 plusmn 003and 058 plusmn 004 The 119875 values of student 119905-test for 119878(F rarr
P)-119878(P rarr F) and 119878(LT rarr RT)-119878(RT rarr LT) pairs are0002 and 0457The results also reveal the frontal dominanceand left-right lateral balance for the control group at rest Yetcompared with the Chan-meditation practitioners controlgroup exhibits weaker strength of effectiveness no matter ifthe region plays an active or a passive role
To explore the average effectiveness of a given ROI weaveraged the RIIs for the region in connection with the otherfour regions Figure 7 displays how a given ROI (F P C LT orRT) influences (active) or is influenced (passive) by the otherregions Similar to the results of experimental group regionP as either the active or passive role exhibits the weakest linksto the other regions
Evidence-Based Complementary and Alternative Medicine 9
Sink
Source
070
065
060
055
050
045
040F P C LT RT
Figure 7 Average effectiveness of each region playing either theactive or passive role
Comparing the efficacy of two counteractive roles playedby the same region we observe that the source-role effective-ness of a given ROI is higher than its sink-role effectivenessexcept region P
34 Comparison between Experimental and Control GroupsFigure 8 illustrates the group averages of RIIs including119878(F rarr P) 119878(P rarr F) 119878(LT rarr RT) and 119878(RT rarr LT)for the experimental group at three stages (R M and C)and for the control group at rest Experimental group revealsmuch more intensive lateral (LT larrrarr RT) interactions thancontrol group The differences are statistically significant forexperimental group at stage M (119875 = 00336) and at stage C(119875 = 00411) On the other hand region P responsible forspatial sense and navigation becomes comparatively inactivefor Chan-meditation practitioners at stage C
The assembling illustration in Figure 9 is used to comparethe average effectiveness of each region between two groupsExperimental group playing either a source role or a sinkrole apparently exhibits higher average effectiveness in allfive regions The extraordinarily large RIIs for region Cparticularly acting the source role may be assumed to becorrelated with the strengthening of neural networks ofregion C dominating over the other regions through thespiritual focusing on Chan Chakra According to the post-experimental interview with Chan-meditation practitionerssuch central (FCz-Cz-CPz) dominating behavior could belinked to theChan-Chakra activation that further induces theperception of grand solemn energy flow in and out throughthe cortical regions defined by acupoints DU20 (Baihui)DU21 (Qianding) and DU22 (Xinhui) in TCM (traditionalChinese Medicine) Figure 10(b) (Appendix) illustrates thelocations of these three acupoints
4 Conclusion
The time-transcending nonmaterial sacred spiritual experi-ences of Chan-meditation practitioners bring our attention tothe study of the unique interactions among regional neuralnetworks in the brain Scientific approach to the scope of
Exp (stage R)Exp (stage M)
Exp (stage C)Control
065
060
055
050
045F rarr P P rarr F LT rarr RT RT rarr LT
Figure 8 Group averages of RIIs (119878(F rarr P) 119878(P rarr F) 119878(LT rarr
RT) and 119878(RT rarr LT)) for experimental group at three stages andfor control group at rest
Chan meditation provides insight into the mechanism inaddition to the vague sketch of meditation sensation and itsmultiform benefits to human beings This paper presents ourpreliminary results based on nonlinear dynamical theory ofexploring the spatial interactions among brain local neuralnetworks under alpha-rhythmic oscillationQuantification ofnonlinear interdependence based on similarity index revealssignificant intergroup difference Significant higher lateralinteractions between left and right temporal regions wereobserved in Chan-meditation practitioners at the stages ofChan meditation and Chakra-focusing practice In Chanpractice practitioners follow the doctrine that the mind canbe enlightened only if it surrenders its leadership power tothe ldquoheartrdquo (Bodhi the true self with eternal wisdom) Theyaccordingly can experience better balance and integrationof the brain hemispheres through years of Chan-meditationpractice
Chan-Chakra spiritual focusing (at stage C) remarkablystrengthens the central neural-network dominance over theother regions On the other hand suppression of the sourceactivity in regions F and P at stage C appears to reveal themeditation state of transcending the realm of physical bodyand mind The particular central (FCz-Cz-CPz) dominatingphenomenon is reflected in long-term Chan practitioners asone of the metamorphosing processes that opens the energypathway between Chan Chakra and the central-line scalpfrom acupoint DU20 to DU22 (Figure 10(b) in Appendix)In the case practitioners experience tranquil brain and calmmind in every moment Chan-meditation practice is to real-ize a Chan-style brain and Chan-style physical body insteadof merely sitting still for one hour to pursue temporary peaceof mind and relief of body
Appendix
Chan meditation originating more than 2500 years ago hasbeen proved to benefit the health while on the way toward theultimate Buddhahood state Buddha Shakyamuni disclosedthe eternal truth the supreme wisdom the noumenal energy
10 Evidence-Based Complementary and Alternative Medicine
Source070
065
060
055
050
F P C LT RT
Exp (R)Exp (M)
Exp (C)Control
(a)
Sink070
065
060
055
050
F P C LT RT
Exp (R)Exp (M)
Exp (C)Control
(b)
Figure 9 Comparison of average effectiveness of each region as a source (a) or a sink (b) between experimental and control groups
Chan Chakra
(a)
DU20
DU21DU22
Anteriorhairline
Posteriorhairline
(b)
Figure 10 (a) Location of the Chan Chakra (inside the third ventricle) (b) Illustration of acupoints DU20 (Baihui) DU21 (Qianding) andDU22 (Xinhui) on DU meridian
and the natural powers of the universe in Chan meditationunder a linden tree The orthodox Chan Buddhism wasoriginated by such an exceptional affair that Buddha Shakya-muni transmitted this light of supreme wisdom to the GreatKashiyapa The same path towards perfect enlightenment(Buddhahood) was promulgated in mainland China in 527
by Bodhidharma the 28th patriarch The current patriarchis Chan master Wu Jue Miao Tian the 85th patriarch of theorthodox Chan-Buddhism Sect since the Great KashiyapaIn orthodox Chan-Buddhist practice very few disciples wereable to catch the quintessence since it cannot be taught inany form of lectures Written material and spoken words
Evidence-Based Complementary and Alternative Medicine 11
cannot promulgate the true wisdom of Chan which can onlybe conveyed by the Buddhist Heart-seal Imprint from a truemaster
In Chan meditation practitioners aim to attain the trueself (Buddha nature) with eternal wisdom (Bodhi) throughbody-mind-soul purification Substantially speaking suchpurification procedure involves the journal of transcendingthe physiological state (five sensory organs) themental activ-ities and normal consciousness the subliminal (the manas)consciousness and the Alaya state at which practitioners areable to perceive the sacred light emitted from Buddha natureBuddhist Heart-seal Imprint from the Chan Patriarch is amust to assist in the purification and accomplishment Toprepare for attaining such realm practitioners meditate withfull-lotus half-lotus or leg-crossing posture and sit still tocultivate spiritual Reiki for penetrating into the ten importantChakras In the course of Chan meditation practitionersmust switch their normal chest breathing to the Navel-Chakra breathing (also called ldquofetal breathingrdquo) that is thebreathing scheme for entering into deep meditation Amongthe ten Chakras Chan Chakra locating inside the thirdventricle is the Buddhist paradise implemented in our bodyFigure 10(a) illustrates the location of Chan Chakra
The cun-measurand system is normally used to measureand locate the acupoints To determine the locations ofacupoints DU20 DU21 and DU22 on Governor Vesselmeridian (DU meridian) we first measure the scalp-midlinelength between anterior hairline and posterior hairline thatis divided into 12 cuns The locations are defined as follows
DU20 7 cuns above the posterior hairline and 5 cunsabove the anterior hairlineDU21 35 cuns directly above the anterior hairline or15 cuns anterior to DU20DU22 2 cuns posterior to the anterior hairline or3 cuns anterior to DU20
Acknowledgments
The authors would like to thank Shung-Yu Yo for his assis-tance in data analysis Chan-meditation practitioners of theShakyamuni Buddhist Foundation are gratefully acknowl-edged for their enthusiastic participation in this research asvolunteers This research was supported by the grants fromthe National Science Council of Taiwan (Grant no NSC 100-2221-E-009-006-MY2)
References
[1] T YuH L Tsai andM LHwang ldquoSuppressing tumor progres-sion of in vitro prostate cancer cells by emitted psychosomaticpower through Zen meditationrdquo American Journal of ChineseMedicine vol 31 no 3 pp 499ndash507 2003
[2] K H Coker ldquoMeditation and prostate cancer integrating amindbody interventionwith traditional therapiesrdquo Seminars inUrologic Oncology vol 17 no 2 pp 111ndash118 1999
[3] D Lester ldquoZen and happinessrdquo Psychological Reports vol 84no 2 pp 650ndash651 1999
[4] C R K MacLean K G Walton S R Wenneberg et alldquoEffects of the transcendental meditation program on adaptivemechanisms changes in hormone levels and responses to stressafter 4 months of practicerdquo Psychoneuroendocrinology vol 22no 4 pp 277ndash295 1997
[5] GA Tooley SMArmstrong T RNorman andA Sali ldquoAcuteincreases in night-time plasma melatonin levels following aperiod of meditationrdquo Biological Psychology vol 53 no 1 pp69ndash78 2000
[6] Y-Y Tang Y Ma Y Fan et al ldquoCentral and autonomicnervous system interaction is altered by short-termmeditationrdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 106 no 22 pp 8865ndash8870 2009
[7] A Lutz H A Slagter N B Rawlings A D Francis LL Greischar and R J Davidson ldquoMental training enhancesattentional stability neural and behavioral evidencerdquo Journal ofNeuroscience vol 29 no 42 pp 13418ndash13427 2009
[8] S M Bertisch C C Wee R S Phillips and E P McCarthyldquoAlternative mind-body therapies used by adults with medicalconditionsrdquo Journal of Psychosomatic Research vol 66 no 6 pp511ndash519 2009
[9] W R Marchand ldquoMindfulness-based stress reductionmindfulness-based cognitive therapy and zen meditation fordepression anxiety pain and psychological distressrdquo Journalof Psychiatric Practice vol 18 no 4 pp 233ndash2252 2012
[10] B R Cahn and J Polich ldquoMeditation states and traits EEG ERPand neuroimaging studiesrdquoPsychological Bulletin vol 132 no 2pp 180ndash211 2006
[11] F Travis and J Shear ldquoFocused attention open monitoring andautomatic self-transcending categories to organize meditationsfrom Vedic Buddhist and Chinese traditionsrdquo Consciousnessand Cognition vol 19 no 4 pp 1110ndash1118 2010
[12] P-C Lo M-L Huang and K-M Chang ldquoEEG alpha blockingcorrelated with perception of inner light during Zen medita-tionrdquo American Journal of Chinese Medicine vol 31 no 4 pp629ndash642 2003
[13] H C Liao and P C Lo ldquoInvestigation on spatiotemporalcharacteristics of zen-meditation EEG rhythmsrdquo Journal ofInternational Society of Life Information Science vol 25 no 1pp 63ndash71 2007
[14] H-Y Huang and P-C Lo ldquoEEG dynamics of experienced zenmeditation practitioners probed by complexity index and spec-tral measurerdquo Journal of Medical Engineering and Technologyvol 33 no 4 pp 314ndash321 2009
[15] E K St Louis and E P Lansky ldquoMeditation and epilepsy a stillhung juryrdquoMedical Hypotheses vol 67 no 2 pp 247ndash250 2006
[16] L I Aftanas and S A Golocheikine ldquoHuman anterior andfrontal midline theta and lower alpha reflect emotionallypositive state and internalized attention high-resolution EEGinvestigation of meditationrdquo Neuroscience Letters vol 310 no1 pp 57ndash60 2001
[17] K Ansari-Asl J-J Bellanger F Bartolomei F Wendung andL Senhadji ldquoTime-frequency characterization of interdepen-dencies in nonstationary signals application to epileptic EEGrdquoIEEE Transactions on Biomedical Engineering vol 52 no 7 pp1218ndash1226 2005
[18] F Gans A Y Schumann J W Kantelhardt T Penzel and IFietze ldquoCross-modulated amplitudes and frequencies charac-terize interacting components in complex systemsrdquo PhysicalReview Letters vol 102 no 9 Article ID 098701 2009
12 Evidence-Based Complementary and Alternative Medicine
[19] J Bhattacharya H Petsche and E Pereda ldquoInterdependenciesin the spontaneous EEG while listening to musicrdquo InternationalJournal of Psychophysiology vol 42 no 3 pp 287ndash301 2001
[20] C J Stam ldquoNonlinear dynamical analysis of EEG and MEGreview of an emerging fieldrdquo Clinical Neurophysiology vol 116no 10 pp 2266ndash2301 2005
[21] W Singer ldquoConsciousness and the binding problemrdquo Annals ofthe New York Academy of Sciences vol 929 pp 123ndash146 2001
[22] D Calitoiu B J Oommen and D Nussbaum ldquoLarge-scaleneuro-modeling for understanding and explaining some brain-related chaotic behaviorrdquo Simulation-Transactions of the Societyfor Modeling and Simulation International vol 88 no 11 pp1316ndash1337 2012
[23] F Wendling K Ansari-Asl F Bartolomei and L SenhadjildquoFrom EEG signals to brain connectivity a model-based eval-uation of interdependence measuresrdquo Journal of NeuroscienceMethods vol 183 no 1 pp 9ndash18 2009
[24] H Y Huang and P C Lo ldquoEEG nonlinear interdependencemeasure of brain interactions under zen meditationrdquo Journalof Biomedical Engineering Research vol 29 no 4 pp 286ndash2942008
[25] M Breakspear and J R Terry ldquoDetection and description ofnon-linear interdependence in normal multichannel humanEEG datardquo Clinical Neurophysiology vol 113 no 5 pp 735ndash7532002
[26] M Breakspear and J R Terry ldquoTopographic organizationof nonlinear interdependence in multichannel human EEGrdquoNeuroImage vol 16 no 3 pp 822ndash835 2002
[27] C J Stam M Breakspear A-M van Cappellen van Walsumand B W van Dijk ldquoNonlinear synchronization in EEG andwhole-headMEG recordings of healthy subjectsrdquoHuman BrainMapping vol 19 no 2 pp 63ndash78 2003
[28] U Feldmann and J Bhattacharya ldquoPredictability improvementas an asymmetrical measure of interdependence in bivariatetime seriesrdquo International Journal of Bifurcation and Chaos vol14 no 2 pp 505ndash514 2004
[29] M Rubinov S A Knock C J Stam et al ldquoSmall-worldproperties of nonlinear brain activity in schizophreniardquoHumanBrain Mapping vol 30 no 2 pp 403ndash416 2009
[30] P Mirowski D Madhavan Y LeCun and R KuznieckyldquoClassification of patterns of EEG synchronization for seizurepredictionrdquo Clinical Neurophysiology vol 120 no 11 pp 1927ndash1940 2009
[31] S I Dimitriadis N A Laskaris Y del Rio-Portilla and G CKoudounis ldquoCharacterizing dynamic functional connectivityacross sleep stages from EEGrdquo Brain Topography vol 22 no 2pp 119ndash133 2009
[32] K Sibsambhu and R Aurobinda ldquoEffect of sleep deprivation onfunctional connectivity of EEG channelsrdquo IEEE Transcations onSystems Man and Cybernetics vol 43 no 3 pp 666ndash672 2013
[33] C M W J M Tian Chan Master Miao Tianrsquos Book of Wisdomand the Guide to Heart Chan Meditation Lulu 2010
[34] X-S Zhang R J Roy and E W Jensen ldquoEEG complexity as ameasure of depth of anesthesia for patientsrdquo IEEE Transactionson Biomedical Engineering vol 48 no 12 pp 1424ndash1433 2001
[35] I Daubechies Ten Lectures on Wavelets Society for Industrialand Applied Mathematics Philadelphia Pa USA 1992
[36] C Heil D F Walnut and I Daubechies Fundamental Papersin Wavelet Theory Princeton University Press Princeton NJUSA 2006
[37] C Y Liu and P C Lo ldquoSpatial focalization of zen-meditationbrain based on EEGrdquo Journal of Biomedical EngineeringResearch vol 29 pp 17ndash24 2008
[38] H Adeli Z Zhou and N Dadmehr ldquoAnalysis of EEG recordsin an epileptic patient using wavelet transformrdquo Journal ofNeuroscience Methods vol 123 no 1 pp 69ndash87 2003
[39] F Takens ldquoDetecting strange attractors in turbulencerdquo inDynamical Systems and Turbulence D A Rand and L S YoungEds vol 898 of Lecture Notes in Mathematics pp 366ndash381Springer New York NY USA 1981
[40] P-C Lo and W-P Chung ldquoAn approach to quantifying themulti-channel EEG spatial-temporal featurerdquo Biometrical Jour-nal vol 42 no 7 pp 901ndash916 2000
[41] W S Pritchard and D W Duke ldquoDimensional analysis of no-task human EEG using the Grassberger-Procaccia methodrdquoPsychophysiology vol 29 no 2 pp 182ndash192 1992
[42] R Q Quiroga A Kraskov T Kreuz and P GrassbergerldquoPerformance of different synchronization measures in realdata a case study on electroencephalographic signalsrdquo PhysicalReview E vol 65 no 4 Article ID 041903 14 pages 2002
6 Evidence-Based Complementary and Alternative Medicine
50
0
minus500 05 1 15 2 25 3 35 4 45 5
Time (s)120588 58 59 52 55 60
(a) Oz
50
0
minus500 05 1 15 2 25 3 35 4 45 5
Time (s)120588 56 60 50 51 60
(b) Cz
50
0
minus500 05 1 15 2 25 3 35 4 45 5
Time (s)120588 62 61 51 59 60
(c) Fz
Figure 4 Percentage of alpha power to total power for each one-second epoch of the five-second EEG segments (amplitude in 120583V)recorded from (a) Oz (b) Cz and (c) Fz
electrode119883119895on the integrative neural network encompassed
by 119871 passive electrodes (119883119894) can be evaluated by
119878119886(119883119895) =
1
119871sum119894
119878 (119883119894| 119883119895) (6)
assuming119883119894= 119883119895 Both 119878
119901(119883119894) and 119878
119886(119883119895) are called regional
interdependence index (RII)In Chan-meditation practice practitioners often focus on
five regions alternately frontal posterior left right and cen-tral regions after activating the Chan Chakra inside the thirdventricle The purpose is to eliminate the stream of jumbledthoughts and produce a tranquil mind To investigate theeffect of such regional focusing we accordingly divided 30EEG recording sites into five regions
frontal (F) Fp1 Fp2 F7 F3 Fz F4 and F8posterior (P Parietal + Occipital) O1 Oz O2 P7 P3Pz P4 and P8central (C) FCz Cz and CPzleft Temporal (LT) FC3 FT7 T7 C3 TP7 and CP3right Temporal (RT) FC4 FT8 T8C4 TP8 andCP4
3 Results and Discussion
31 Interdependence Matrix of Chan-Meditation EEG Con-sider a given source signal Y The influence of source signalY on sink signal X 119878(X | Y) can be expressed as a 30 times
30 interdependence matrix with the element 119878119894119895= 119878(119883
119894| 119884119895)
denoting the coupling strength of interaction of the source119884119895affecting the sink 119883
119894 The similarity index (SI) was
calculated for 870 (30 times 29) electrode pairs As displayed inFigure 5(a) the color image encoded the quantities in the 30times 30 interdependence matrix S The right-side color chartencodes the strength level of 119878
119894119895 from blue to red indicating
the range of 119878 from the smallest to the largest value EEGchannels are in the order of (from topleft) O2 Oz O1 P7P3 Pz P4 P8 TP8 CP4 CPz CP3 TP7 T7 C3 Cz C4 T8FT8 FC4 FCz FC3 FT7 F7 F3 Fz F4 F8 Fp2 and Fp1 Forexample the box at the lower-left corner characterizes theeffect of O2 channel on Fp1 channel as denoted by 119878(Fp1 |
O2) Accordingly the first row reveals the effect of sourceO2Oz and Fp1 respectively on sink O2 On the other handthe first column indicates how source O2 affects sink O2 Oz and Fp1 respectivelyThe dark red along the diagonal lineindicates the highest similarity index 119878 = 1 when the sourceand sink signals are identical
This figure exhibits some typical behavior in the 119878matrixthat is stronger interdependence occurs in the pairs ofnearby EEG channels On the other hand weaker interactionis measured as two channels are much apart Moreoverbox (119894 119895) does not equal its transposed partner box (119895 119894)indicating the asymmetry of 119878 matrix Figures 5(b)ndash5(d)display the top viewof brain topographicmapping of 119878
119886(FP1)
119878119886(FP2) and 119878
119886(Oz) extracted respectively from the 30th
29th and 2nd columns of Figure 5(a) The topographicmapping was plotted by the function topoplotm providedby EEGLab The mappings exhibit the efficacy of the givenchannel acting as the source role The results in Figures 5(b)to 5(d) reveal the right-frontal dominance The occipitalchannels are comparably less active with respect to the frontalneuronal networks Such weaker influence of occipital andposterior regions on the other regions can be clearly observedfrom the blue color dominating in the left three columns of Smatrix (Figure 5(a)) corresponding to the source at O2 Ozand O1
32 Inter-Region Interdependence AnalysismdashExperimentalGroup Inter-regional nonlinear interdependence was ana-lyzed for EEG recorded in three different sessions (stage RM and C) Due to the premeditation brain-drilling practicedescribed in previous section we particularly focused onthe left-right temporal (LT-RT) and frontal-posterior (F-P)neural-network interactions For example 119878(F rarr P) iscomputed by averaging all 119878
119886(119883119895) in (6) for all 119883
119895isin F and
119883119894isin P to assess the integrative source effect of all electrodes
in frontal region driving the posterior region On the otherhand 119878(P rarr F) is computed by averaging all 119878
119886(119883119895) in
(6) for all 119883119895isin P and 119883
119894isin F when all the electrodes in
the posterior region play the source role to drive the frontalregion
Table 1 lists the group averages and standard deviationsof 119878(F rarr P) 119878(P rarr F) 119878(LT rarr RT) and 119878(RT rarr
LT) at three experimental stages (R M and C) Evidently119878(F rarr P) is consistently greater than 119878(P rarr F) for all threestages The 119875 values (00055 00031 and 00302) of pairedsample 119905-test are all smaller than 005 that demonstrates the
Evidence-Based Complementary and Alternative Medicine 7
Figure 5 SI analysis for experienced practitioner during Chanmeditation (StageM) (a) 30 times 30 Smatrix and brain topographical mappings(top view) of (b) 119878
119886(FP1) (c) 119878
119886(FP2) and (d) 119878
119886(Oz) indicating the average driving strength of the EEG sites FP1 FP2 and Oz
070
065
060
055
050
045
040
Source
Stage RStage MStage C
F P C LT RT
(a)
Sink070
065
060
055
050
045
040
Stage RStage MStage C
F P C LT RT
(b)
Figure 6 Average effectiveness of each region playing the role of a source (a) and sink (b) Three bars in each RII cluster correspond to threeexperimental stages
statistical significance of frontal-alpha dominance at all threestages On the other hand results of the left-right temporalanalysis of nonlinear interdependence reveal no distinctlydominant role of the laterally neural-network operation thatis 119878(LT rarr RT) asymp 119878(RT rarr LT) The higher 119875 values forthe 119878(LT rarr RT)-119878(RT rarr LT) paired 119905-test indicate nostatistically significant difference between two sets of resultsWe may further infer the balancing operations between theleft-brain and right-brain hemispheres
Our results demonstrate that interactions between leftand right hemispheres are much more intensive than theinteractions between frontal and posterior regions with 119875 =
00016 considering all the experimental subjects at all threestages
Figure 6 provides an alternative viewpoint for exploringhow a given region of interest ROI (F P C LT or RT)influences or is influenced by the other regions In Figure 6left (right) group of five 3-bar clusters corresponds to theaverage effectiveness of each region playing the active (pas-sive) role at three stages For example the leftmost barindicates the average of 119878(F rarr P) 119878(F rarr LT) 119878(F rarr
RT) and 119878(F rarr C) for stage R while the rightmostbar indicates the average of 119878(F rarr RT) 119878(P rarr RT)119878(C rarr RT) and 119878(LT rarr RT) for stage C Among allfive regions posterior region as either the source or sinkapparently exhibits the weakest link to the other regions Inaddition the effectiveness of active role of posterior regionis weaker than that of passive role The results strongly
8 Evidence-Based Complementary and Alternative Medicine
Table 1 Group averages and standard deviations of 119878(FrarrP) 119878(Prarr F) 119878(LTrarrRT) and 119878(RTrarr LT) at three experimental stages (R Mand C) including the 119875 values of student 119905-test for 119878(FrarrP)-119878(Prarr F) and 119878(LTrarrRT)-119878(RTrarr LT) pairs
Group average 056 051 060 061Group std 005 005 007 005119875 value 00055 03476
MGroup average 056 050 060 061Group std 003 006 006 004119875 value 00031 01987
CGroup average 055 049 061 061Group std 007 006 006 006119875 value 00302 03953
suggest the inactive behaviors of parietal-occipital lobes sinceregion P encompasses the EEG-electrode sites of parietal andoccipital lobesThe parietal lobe is responsible for integratingsensory information from various parts of the body withthe particular functions of determining spatial sense andnavigation Functions of occipital lobe mainly include visualreception visual-spatial processing and color recognitionAs described previously the core essence of orthodox Chan-meditation practice is to transcend physiological mental andall states of consciousness to prove the existence of true beingThe inactive posterior regions may provide the evidence ofbrain rewiring in preparation for such transcendence
Region C encompasses three midline electrodes locatingfrom precentral to postcentral cortex Region C as the sourceapparently dominates over the other four regions regardlessof the stages On the other hand region C as the passive role isaffected mostly among the five regions Region C constantlyexhibits the largest RII at all stages
Wemay draw a tentative hypothesis from the mechanismof Chan-meditation practice Practitioners are required tokeep Chan Chakra active at any moment that results inthe formation of an energy pathway between Chan Chakraand Qian-Ding acupoint on scalp (Figure 10(b)) Does suchphysiological reformation correlate to the significant effec-tiveness of region C It leaves an open question for futureinvestigation
RII characterizing the regional interdependence behavesdifferently for each region when the experimental subjectsswitch their mental states from R (resting) to M (medita-tion) or from R to C (Chakra focusing) To investigate theeffect of different experimental sessions the RII percentageincreasedecrease from stage R to M and from stage R to Cwere computed for each of the five regions (F P C LT andRT)acting as either the active or the passive role In comparisonof RII between stage M and stage R the percentage largerthan 1 was observed in the regions of LTactive(minus124)RTactive (125) and Cpassive (minus107) On the other handthe regions of significant change in RII when comparingstage C with R include Factive (minus184) Pactive (minus178) andCactive (239) On the basis of RII of stage R for each
individual region we summarize the changes of RII at stagesM and C as follows
(1) In the active-role analysis region LT becomes moredeactivated at stage M while region RT becomesmore activatedWhenmeditation subjects focused onChan Chakra the active driving strength of regionC increases significantly (239) On the other handsuppression of the source activity occurs to bothregions F and P (the regions anterior to and posteriorto region C)
(2) In the passive-role analysis only region C becomesnotably deactivated at stage M (free meditation) Ingeneral differences are trivial in comparison of119877119868119868passive between stages M and R
(3) Chan meditation deactivates the left brain hemi-sphere whereas it inactivates the right brain hemi-sphere
Except for region P the active-role effectiveness of a givenregion is better than its passive-role effectiveness
33 Inter-Region Interdependence AnalysismdashControl GroupIn control group the group average and standard deviationof 119878(F rarr P) 119878(P rarr F) 119878(LT rarr RT) and 119878(RT rarr LT) atstage R are respectively 055 plusmn 004 051 plusmn 004 059 plusmn 003and 058 plusmn 004 The 119875 values of student 119905-test for 119878(F rarr
P)-119878(P rarr F) and 119878(LT rarr RT)-119878(RT rarr LT) pairs are0002 and 0457The results also reveal the frontal dominanceand left-right lateral balance for the control group at rest Yetcompared with the Chan-meditation practitioners controlgroup exhibits weaker strength of effectiveness no matter ifthe region plays an active or a passive role
To explore the average effectiveness of a given ROI weaveraged the RIIs for the region in connection with the otherfour regions Figure 7 displays how a given ROI (F P C LT orRT) influences (active) or is influenced (passive) by the otherregions Similar to the results of experimental group regionP as either the active or passive role exhibits the weakest linksto the other regions
Evidence-Based Complementary and Alternative Medicine 9
Sink
Source
070
065
060
055
050
045
040F P C LT RT
Figure 7 Average effectiveness of each region playing either theactive or passive role
Comparing the efficacy of two counteractive roles playedby the same region we observe that the source-role effective-ness of a given ROI is higher than its sink-role effectivenessexcept region P
34 Comparison between Experimental and Control GroupsFigure 8 illustrates the group averages of RIIs including119878(F rarr P) 119878(P rarr F) 119878(LT rarr RT) and 119878(RT rarr LT)for the experimental group at three stages (R M and C)and for the control group at rest Experimental group revealsmuch more intensive lateral (LT larrrarr RT) interactions thancontrol group The differences are statistically significant forexperimental group at stage M (119875 = 00336) and at stage C(119875 = 00411) On the other hand region P responsible forspatial sense and navigation becomes comparatively inactivefor Chan-meditation practitioners at stage C
The assembling illustration in Figure 9 is used to comparethe average effectiveness of each region between two groupsExperimental group playing either a source role or a sinkrole apparently exhibits higher average effectiveness in allfive regions The extraordinarily large RIIs for region Cparticularly acting the source role may be assumed to becorrelated with the strengthening of neural networks ofregion C dominating over the other regions through thespiritual focusing on Chan Chakra According to the post-experimental interview with Chan-meditation practitionerssuch central (FCz-Cz-CPz) dominating behavior could belinked to theChan-Chakra activation that further induces theperception of grand solemn energy flow in and out throughthe cortical regions defined by acupoints DU20 (Baihui)DU21 (Qianding) and DU22 (Xinhui) in TCM (traditionalChinese Medicine) Figure 10(b) (Appendix) illustrates thelocations of these three acupoints
4 Conclusion
The time-transcending nonmaterial sacred spiritual experi-ences of Chan-meditation practitioners bring our attention tothe study of the unique interactions among regional neuralnetworks in the brain Scientific approach to the scope of
Exp (stage R)Exp (stage M)
Exp (stage C)Control
065
060
055
050
045F rarr P P rarr F LT rarr RT RT rarr LT
Figure 8 Group averages of RIIs (119878(F rarr P) 119878(P rarr F) 119878(LT rarr
RT) and 119878(RT rarr LT)) for experimental group at three stages andfor control group at rest
Chan meditation provides insight into the mechanism inaddition to the vague sketch of meditation sensation and itsmultiform benefits to human beings This paper presents ourpreliminary results based on nonlinear dynamical theory ofexploring the spatial interactions among brain local neuralnetworks under alpha-rhythmic oscillationQuantification ofnonlinear interdependence based on similarity index revealssignificant intergroup difference Significant higher lateralinteractions between left and right temporal regions wereobserved in Chan-meditation practitioners at the stages ofChan meditation and Chakra-focusing practice In Chanpractice practitioners follow the doctrine that the mind canbe enlightened only if it surrenders its leadership power tothe ldquoheartrdquo (Bodhi the true self with eternal wisdom) Theyaccordingly can experience better balance and integrationof the brain hemispheres through years of Chan-meditationpractice
Chan-Chakra spiritual focusing (at stage C) remarkablystrengthens the central neural-network dominance over theother regions On the other hand suppression of the sourceactivity in regions F and P at stage C appears to reveal themeditation state of transcending the realm of physical bodyand mind The particular central (FCz-Cz-CPz) dominatingphenomenon is reflected in long-term Chan practitioners asone of the metamorphosing processes that opens the energypathway between Chan Chakra and the central-line scalpfrom acupoint DU20 to DU22 (Figure 10(b) in Appendix)In the case practitioners experience tranquil brain and calmmind in every moment Chan-meditation practice is to real-ize a Chan-style brain and Chan-style physical body insteadof merely sitting still for one hour to pursue temporary peaceof mind and relief of body
Appendix
Chan meditation originating more than 2500 years ago hasbeen proved to benefit the health while on the way toward theultimate Buddhahood state Buddha Shakyamuni disclosedthe eternal truth the supreme wisdom the noumenal energy
10 Evidence-Based Complementary and Alternative Medicine
Source070
065
060
055
050
F P C LT RT
Exp (R)Exp (M)
Exp (C)Control
(a)
Sink070
065
060
055
050
F P C LT RT
Exp (R)Exp (M)
Exp (C)Control
(b)
Figure 9 Comparison of average effectiveness of each region as a source (a) or a sink (b) between experimental and control groups
Chan Chakra
(a)
DU20
DU21DU22
Anteriorhairline
Posteriorhairline
(b)
Figure 10 (a) Location of the Chan Chakra (inside the third ventricle) (b) Illustration of acupoints DU20 (Baihui) DU21 (Qianding) andDU22 (Xinhui) on DU meridian
and the natural powers of the universe in Chan meditationunder a linden tree The orthodox Chan Buddhism wasoriginated by such an exceptional affair that Buddha Shakya-muni transmitted this light of supreme wisdom to the GreatKashiyapa The same path towards perfect enlightenment(Buddhahood) was promulgated in mainland China in 527
by Bodhidharma the 28th patriarch The current patriarchis Chan master Wu Jue Miao Tian the 85th patriarch of theorthodox Chan-Buddhism Sect since the Great KashiyapaIn orthodox Chan-Buddhist practice very few disciples wereable to catch the quintessence since it cannot be taught inany form of lectures Written material and spoken words
Evidence-Based Complementary and Alternative Medicine 11
cannot promulgate the true wisdom of Chan which can onlybe conveyed by the Buddhist Heart-seal Imprint from a truemaster
In Chan meditation practitioners aim to attain the trueself (Buddha nature) with eternal wisdom (Bodhi) throughbody-mind-soul purification Substantially speaking suchpurification procedure involves the journal of transcendingthe physiological state (five sensory organs) themental activ-ities and normal consciousness the subliminal (the manas)consciousness and the Alaya state at which practitioners areable to perceive the sacred light emitted from Buddha natureBuddhist Heart-seal Imprint from the Chan Patriarch is amust to assist in the purification and accomplishment Toprepare for attaining such realm practitioners meditate withfull-lotus half-lotus or leg-crossing posture and sit still tocultivate spiritual Reiki for penetrating into the ten importantChakras In the course of Chan meditation practitionersmust switch their normal chest breathing to the Navel-Chakra breathing (also called ldquofetal breathingrdquo) that is thebreathing scheme for entering into deep meditation Amongthe ten Chakras Chan Chakra locating inside the thirdventricle is the Buddhist paradise implemented in our bodyFigure 10(a) illustrates the location of Chan Chakra
The cun-measurand system is normally used to measureand locate the acupoints To determine the locations ofacupoints DU20 DU21 and DU22 on Governor Vesselmeridian (DU meridian) we first measure the scalp-midlinelength between anterior hairline and posterior hairline thatis divided into 12 cuns The locations are defined as follows
DU20 7 cuns above the posterior hairline and 5 cunsabove the anterior hairlineDU21 35 cuns directly above the anterior hairline or15 cuns anterior to DU20DU22 2 cuns posterior to the anterior hairline or3 cuns anterior to DU20
Acknowledgments
The authors would like to thank Shung-Yu Yo for his assis-tance in data analysis Chan-meditation practitioners of theShakyamuni Buddhist Foundation are gratefully acknowl-edged for their enthusiastic participation in this research asvolunteers This research was supported by the grants fromthe National Science Council of Taiwan (Grant no NSC 100-2221-E-009-006-MY2)
References
[1] T YuH L Tsai andM LHwang ldquoSuppressing tumor progres-sion of in vitro prostate cancer cells by emitted psychosomaticpower through Zen meditationrdquo American Journal of ChineseMedicine vol 31 no 3 pp 499ndash507 2003
[2] K H Coker ldquoMeditation and prostate cancer integrating amindbody interventionwith traditional therapiesrdquo Seminars inUrologic Oncology vol 17 no 2 pp 111ndash118 1999
[3] D Lester ldquoZen and happinessrdquo Psychological Reports vol 84no 2 pp 650ndash651 1999
[4] C R K MacLean K G Walton S R Wenneberg et alldquoEffects of the transcendental meditation program on adaptivemechanisms changes in hormone levels and responses to stressafter 4 months of practicerdquo Psychoneuroendocrinology vol 22no 4 pp 277ndash295 1997
[5] GA Tooley SMArmstrong T RNorman andA Sali ldquoAcuteincreases in night-time plasma melatonin levels following aperiod of meditationrdquo Biological Psychology vol 53 no 1 pp69ndash78 2000
[6] Y-Y Tang Y Ma Y Fan et al ldquoCentral and autonomicnervous system interaction is altered by short-termmeditationrdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 106 no 22 pp 8865ndash8870 2009
[7] A Lutz H A Slagter N B Rawlings A D Francis LL Greischar and R J Davidson ldquoMental training enhancesattentional stability neural and behavioral evidencerdquo Journal ofNeuroscience vol 29 no 42 pp 13418ndash13427 2009
[8] S M Bertisch C C Wee R S Phillips and E P McCarthyldquoAlternative mind-body therapies used by adults with medicalconditionsrdquo Journal of Psychosomatic Research vol 66 no 6 pp511ndash519 2009
[9] W R Marchand ldquoMindfulness-based stress reductionmindfulness-based cognitive therapy and zen meditation fordepression anxiety pain and psychological distressrdquo Journalof Psychiatric Practice vol 18 no 4 pp 233ndash2252 2012
[10] B R Cahn and J Polich ldquoMeditation states and traits EEG ERPand neuroimaging studiesrdquoPsychological Bulletin vol 132 no 2pp 180ndash211 2006
[11] F Travis and J Shear ldquoFocused attention open monitoring andautomatic self-transcending categories to organize meditationsfrom Vedic Buddhist and Chinese traditionsrdquo Consciousnessand Cognition vol 19 no 4 pp 1110ndash1118 2010
[12] P-C Lo M-L Huang and K-M Chang ldquoEEG alpha blockingcorrelated with perception of inner light during Zen medita-tionrdquo American Journal of Chinese Medicine vol 31 no 4 pp629ndash642 2003
[13] H C Liao and P C Lo ldquoInvestigation on spatiotemporalcharacteristics of zen-meditation EEG rhythmsrdquo Journal ofInternational Society of Life Information Science vol 25 no 1pp 63ndash71 2007
[14] H-Y Huang and P-C Lo ldquoEEG dynamics of experienced zenmeditation practitioners probed by complexity index and spec-tral measurerdquo Journal of Medical Engineering and Technologyvol 33 no 4 pp 314ndash321 2009
[15] E K St Louis and E P Lansky ldquoMeditation and epilepsy a stillhung juryrdquoMedical Hypotheses vol 67 no 2 pp 247ndash250 2006
[16] L I Aftanas and S A Golocheikine ldquoHuman anterior andfrontal midline theta and lower alpha reflect emotionallypositive state and internalized attention high-resolution EEGinvestigation of meditationrdquo Neuroscience Letters vol 310 no1 pp 57ndash60 2001
[17] K Ansari-Asl J-J Bellanger F Bartolomei F Wendung andL Senhadji ldquoTime-frequency characterization of interdepen-dencies in nonstationary signals application to epileptic EEGrdquoIEEE Transactions on Biomedical Engineering vol 52 no 7 pp1218ndash1226 2005
[18] F Gans A Y Schumann J W Kantelhardt T Penzel and IFietze ldquoCross-modulated amplitudes and frequencies charac-terize interacting components in complex systemsrdquo PhysicalReview Letters vol 102 no 9 Article ID 098701 2009
12 Evidence-Based Complementary and Alternative Medicine
[19] J Bhattacharya H Petsche and E Pereda ldquoInterdependenciesin the spontaneous EEG while listening to musicrdquo InternationalJournal of Psychophysiology vol 42 no 3 pp 287ndash301 2001
[20] C J Stam ldquoNonlinear dynamical analysis of EEG and MEGreview of an emerging fieldrdquo Clinical Neurophysiology vol 116no 10 pp 2266ndash2301 2005
[21] W Singer ldquoConsciousness and the binding problemrdquo Annals ofthe New York Academy of Sciences vol 929 pp 123ndash146 2001
[22] D Calitoiu B J Oommen and D Nussbaum ldquoLarge-scaleneuro-modeling for understanding and explaining some brain-related chaotic behaviorrdquo Simulation-Transactions of the Societyfor Modeling and Simulation International vol 88 no 11 pp1316ndash1337 2012
[23] F Wendling K Ansari-Asl F Bartolomei and L SenhadjildquoFrom EEG signals to brain connectivity a model-based eval-uation of interdependence measuresrdquo Journal of NeuroscienceMethods vol 183 no 1 pp 9ndash18 2009
[24] H Y Huang and P C Lo ldquoEEG nonlinear interdependencemeasure of brain interactions under zen meditationrdquo Journalof Biomedical Engineering Research vol 29 no 4 pp 286ndash2942008
[25] M Breakspear and J R Terry ldquoDetection and description ofnon-linear interdependence in normal multichannel humanEEG datardquo Clinical Neurophysiology vol 113 no 5 pp 735ndash7532002
[26] M Breakspear and J R Terry ldquoTopographic organizationof nonlinear interdependence in multichannel human EEGrdquoNeuroImage vol 16 no 3 pp 822ndash835 2002
[27] C J Stam M Breakspear A-M van Cappellen van Walsumand B W van Dijk ldquoNonlinear synchronization in EEG andwhole-headMEG recordings of healthy subjectsrdquoHuman BrainMapping vol 19 no 2 pp 63ndash78 2003
[28] U Feldmann and J Bhattacharya ldquoPredictability improvementas an asymmetrical measure of interdependence in bivariatetime seriesrdquo International Journal of Bifurcation and Chaos vol14 no 2 pp 505ndash514 2004
[29] M Rubinov S A Knock C J Stam et al ldquoSmall-worldproperties of nonlinear brain activity in schizophreniardquoHumanBrain Mapping vol 30 no 2 pp 403ndash416 2009
[30] P Mirowski D Madhavan Y LeCun and R KuznieckyldquoClassification of patterns of EEG synchronization for seizurepredictionrdquo Clinical Neurophysiology vol 120 no 11 pp 1927ndash1940 2009
[31] S I Dimitriadis N A Laskaris Y del Rio-Portilla and G CKoudounis ldquoCharacterizing dynamic functional connectivityacross sleep stages from EEGrdquo Brain Topography vol 22 no 2pp 119ndash133 2009
[32] K Sibsambhu and R Aurobinda ldquoEffect of sleep deprivation onfunctional connectivity of EEG channelsrdquo IEEE Transcations onSystems Man and Cybernetics vol 43 no 3 pp 666ndash672 2013
[33] C M W J M Tian Chan Master Miao Tianrsquos Book of Wisdomand the Guide to Heart Chan Meditation Lulu 2010
[34] X-S Zhang R J Roy and E W Jensen ldquoEEG complexity as ameasure of depth of anesthesia for patientsrdquo IEEE Transactionson Biomedical Engineering vol 48 no 12 pp 1424ndash1433 2001
[35] I Daubechies Ten Lectures on Wavelets Society for Industrialand Applied Mathematics Philadelphia Pa USA 1992
[36] C Heil D F Walnut and I Daubechies Fundamental Papersin Wavelet Theory Princeton University Press Princeton NJUSA 2006
[37] C Y Liu and P C Lo ldquoSpatial focalization of zen-meditationbrain based on EEGrdquo Journal of Biomedical EngineeringResearch vol 29 pp 17ndash24 2008
[38] H Adeli Z Zhou and N Dadmehr ldquoAnalysis of EEG recordsin an epileptic patient using wavelet transformrdquo Journal ofNeuroscience Methods vol 123 no 1 pp 69ndash87 2003
[39] F Takens ldquoDetecting strange attractors in turbulencerdquo inDynamical Systems and Turbulence D A Rand and L S YoungEds vol 898 of Lecture Notes in Mathematics pp 366ndash381Springer New York NY USA 1981
[40] P-C Lo and W-P Chung ldquoAn approach to quantifying themulti-channel EEG spatial-temporal featurerdquo Biometrical Jour-nal vol 42 no 7 pp 901ndash916 2000
[41] W S Pritchard and D W Duke ldquoDimensional analysis of no-task human EEG using the Grassberger-Procaccia methodrdquoPsychophysiology vol 29 no 2 pp 182ndash192 1992
[42] R Q Quiroga A Kraskov T Kreuz and P GrassbergerldquoPerformance of different synchronization measures in realdata a case study on electroencephalographic signalsrdquo PhysicalReview E vol 65 no 4 Article ID 041903 14 pages 2002
Figure 5 SI analysis for experienced practitioner during Chanmeditation (StageM) (a) 30 times 30 Smatrix and brain topographical mappings(top view) of (b) 119878
119886(FP1) (c) 119878
119886(FP2) and (d) 119878
119886(Oz) indicating the average driving strength of the EEG sites FP1 FP2 and Oz
070
065
060
055
050
045
040
Source
Stage RStage MStage C
F P C LT RT
(a)
Sink070
065
060
055
050
045
040
Stage RStage MStage C
F P C LT RT
(b)
Figure 6 Average effectiveness of each region playing the role of a source (a) and sink (b) Three bars in each RII cluster correspond to threeexperimental stages
statistical significance of frontal-alpha dominance at all threestages On the other hand results of the left-right temporalanalysis of nonlinear interdependence reveal no distinctlydominant role of the laterally neural-network operation thatis 119878(LT rarr RT) asymp 119878(RT rarr LT) The higher 119875 values forthe 119878(LT rarr RT)-119878(RT rarr LT) paired 119905-test indicate nostatistically significant difference between two sets of resultsWe may further infer the balancing operations between theleft-brain and right-brain hemispheres
Our results demonstrate that interactions between leftand right hemispheres are much more intensive than theinteractions between frontal and posterior regions with 119875 =
00016 considering all the experimental subjects at all threestages
Figure 6 provides an alternative viewpoint for exploringhow a given region of interest ROI (F P C LT or RT)influences or is influenced by the other regions In Figure 6left (right) group of five 3-bar clusters corresponds to theaverage effectiveness of each region playing the active (pas-sive) role at three stages For example the leftmost barindicates the average of 119878(F rarr P) 119878(F rarr LT) 119878(F rarr
RT) and 119878(F rarr C) for stage R while the rightmostbar indicates the average of 119878(F rarr RT) 119878(P rarr RT)119878(C rarr RT) and 119878(LT rarr RT) for stage C Among allfive regions posterior region as either the source or sinkapparently exhibits the weakest link to the other regions Inaddition the effectiveness of active role of posterior regionis weaker than that of passive role The results strongly
8 Evidence-Based Complementary and Alternative Medicine
Table 1 Group averages and standard deviations of 119878(FrarrP) 119878(Prarr F) 119878(LTrarrRT) and 119878(RTrarr LT) at three experimental stages (R Mand C) including the 119875 values of student 119905-test for 119878(FrarrP)-119878(Prarr F) and 119878(LTrarrRT)-119878(RTrarr LT) pairs
Group average 056 051 060 061Group std 005 005 007 005119875 value 00055 03476
MGroup average 056 050 060 061Group std 003 006 006 004119875 value 00031 01987
CGroup average 055 049 061 061Group std 007 006 006 006119875 value 00302 03953
suggest the inactive behaviors of parietal-occipital lobes sinceregion P encompasses the EEG-electrode sites of parietal andoccipital lobesThe parietal lobe is responsible for integratingsensory information from various parts of the body withthe particular functions of determining spatial sense andnavigation Functions of occipital lobe mainly include visualreception visual-spatial processing and color recognitionAs described previously the core essence of orthodox Chan-meditation practice is to transcend physiological mental andall states of consciousness to prove the existence of true beingThe inactive posterior regions may provide the evidence ofbrain rewiring in preparation for such transcendence
Region C encompasses three midline electrodes locatingfrom precentral to postcentral cortex Region C as the sourceapparently dominates over the other four regions regardlessof the stages On the other hand region C as the passive role isaffected mostly among the five regions Region C constantlyexhibits the largest RII at all stages
Wemay draw a tentative hypothesis from the mechanismof Chan-meditation practice Practitioners are required tokeep Chan Chakra active at any moment that results inthe formation of an energy pathway between Chan Chakraand Qian-Ding acupoint on scalp (Figure 10(b)) Does suchphysiological reformation correlate to the significant effec-tiveness of region C It leaves an open question for futureinvestigation
RII characterizing the regional interdependence behavesdifferently for each region when the experimental subjectsswitch their mental states from R (resting) to M (medita-tion) or from R to C (Chakra focusing) To investigate theeffect of different experimental sessions the RII percentageincreasedecrease from stage R to M and from stage R to Cwere computed for each of the five regions (F P C LT andRT)acting as either the active or the passive role In comparisonof RII between stage M and stage R the percentage largerthan 1 was observed in the regions of LTactive(minus124)RTactive (125) and Cpassive (minus107) On the other handthe regions of significant change in RII when comparingstage C with R include Factive (minus184) Pactive (minus178) andCactive (239) On the basis of RII of stage R for each
individual region we summarize the changes of RII at stagesM and C as follows
(1) In the active-role analysis region LT becomes moredeactivated at stage M while region RT becomesmore activatedWhenmeditation subjects focused onChan Chakra the active driving strength of regionC increases significantly (239) On the other handsuppression of the source activity occurs to bothregions F and P (the regions anterior to and posteriorto region C)
(2) In the passive-role analysis only region C becomesnotably deactivated at stage M (free meditation) Ingeneral differences are trivial in comparison of119877119868119868passive between stages M and R
(3) Chan meditation deactivates the left brain hemi-sphere whereas it inactivates the right brain hemi-sphere
Except for region P the active-role effectiveness of a givenregion is better than its passive-role effectiveness
33 Inter-Region Interdependence AnalysismdashControl GroupIn control group the group average and standard deviationof 119878(F rarr P) 119878(P rarr F) 119878(LT rarr RT) and 119878(RT rarr LT) atstage R are respectively 055 plusmn 004 051 plusmn 004 059 plusmn 003and 058 plusmn 004 The 119875 values of student 119905-test for 119878(F rarr
P)-119878(P rarr F) and 119878(LT rarr RT)-119878(RT rarr LT) pairs are0002 and 0457The results also reveal the frontal dominanceand left-right lateral balance for the control group at rest Yetcompared with the Chan-meditation practitioners controlgroup exhibits weaker strength of effectiveness no matter ifthe region plays an active or a passive role
To explore the average effectiveness of a given ROI weaveraged the RIIs for the region in connection with the otherfour regions Figure 7 displays how a given ROI (F P C LT orRT) influences (active) or is influenced (passive) by the otherregions Similar to the results of experimental group regionP as either the active or passive role exhibits the weakest linksto the other regions
Evidence-Based Complementary and Alternative Medicine 9
Sink
Source
070
065
060
055
050
045
040F P C LT RT
Figure 7 Average effectiveness of each region playing either theactive or passive role
Comparing the efficacy of two counteractive roles playedby the same region we observe that the source-role effective-ness of a given ROI is higher than its sink-role effectivenessexcept region P
34 Comparison between Experimental and Control GroupsFigure 8 illustrates the group averages of RIIs including119878(F rarr P) 119878(P rarr F) 119878(LT rarr RT) and 119878(RT rarr LT)for the experimental group at three stages (R M and C)and for the control group at rest Experimental group revealsmuch more intensive lateral (LT larrrarr RT) interactions thancontrol group The differences are statistically significant forexperimental group at stage M (119875 = 00336) and at stage C(119875 = 00411) On the other hand region P responsible forspatial sense and navigation becomes comparatively inactivefor Chan-meditation practitioners at stage C
The assembling illustration in Figure 9 is used to comparethe average effectiveness of each region between two groupsExperimental group playing either a source role or a sinkrole apparently exhibits higher average effectiveness in allfive regions The extraordinarily large RIIs for region Cparticularly acting the source role may be assumed to becorrelated with the strengthening of neural networks ofregion C dominating over the other regions through thespiritual focusing on Chan Chakra According to the post-experimental interview with Chan-meditation practitionerssuch central (FCz-Cz-CPz) dominating behavior could belinked to theChan-Chakra activation that further induces theperception of grand solemn energy flow in and out throughthe cortical regions defined by acupoints DU20 (Baihui)DU21 (Qianding) and DU22 (Xinhui) in TCM (traditionalChinese Medicine) Figure 10(b) (Appendix) illustrates thelocations of these three acupoints
4 Conclusion
The time-transcending nonmaterial sacred spiritual experi-ences of Chan-meditation practitioners bring our attention tothe study of the unique interactions among regional neuralnetworks in the brain Scientific approach to the scope of
Exp (stage R)Exp (stage M)
Exp (stage C)Control
065
060
055
050
045F rarr P P rarr F LT rarr RT RT rarr LT
Figure 8 Group averages of RIIs (119878(F rarr P) 119878(P rarr F) 119878(LT rarr
RT) and 119878(RT rarr LT)) for experimental group at three stages andfor control group at rest
Chan meditation provides insight into the mechanism inaddition to the vague sketch of meditation sensation and itsmultiform benefits to human beings This paper presents ourpreliminary results based on nonlinear dynamical theory ofexploring the spatial interactions among brain local neuralnetworks under alpha-rhythmic oscillationQuantification ofnonlinear interdependence based on similarity index revealssignificant intergroup difference Significant higher lateralinteractions between left and right temporal regions wereobserved in Chan-meditation practitioners at the stages ofChan meditation and Chakra-focusing practice In Chanpractice practitioners follow the doctrine that the mind canbe enlightened only if it surrenders its leadership power tothe ldquoheartrdquo (Bodhi the true self with eternal wisdom) Theyaccordingly can experience better balance and integrationof the brain hemispheres through years of Chan-meditationpractice
Chan-Chakra spiritual focusing (at stage C) remarkablystrengthens the central neural-network dominance over theother regions On the other hand suppression of the sourceactivity in regions F and P at stage C appears to reveal themeditation state of transcending the realm of physical bodyand mind The particular central (FCz-Cz-CPz) dominatingphenomenon is reflected in long-term Chan practitioners asone of the metamorphosing processes that opens the energypathway between Chan Chakra and the central-line scalpfrom acupoint DU20 to DU22 (Figure 10(b) in Appendix)In the case practitioners experience tranquil brain and calmmind in every moment Chan-meditation practice is to real-ize a Chan-style brain and Chan-style physical body insteadof merely sitting still for one hour to pursue temporary peaceof mind and relief of body
Appendix
Chan meditation originating more than 2500 years ago hasbeen proved to benefit the health while on the way toward theultimate Buddhahood state Buddha Shakyamuni disclosedthe eternal truth the supreme wisdom the noumenal energy
10 Evidence-Based Complementary and Alternative Medicine
Source070
065
060
055
050
F P C LT RT
Exp (R)Exp (M)
Exp (C)Control
(a)
Sink070
065
060
055
050
F P C LT RT
Exp (R)Exp (M)
Exp (C)Control
(b)
Figure 9 Comparison of average effectiveness of each region as a source (a) or a sink (b) between experimental and control groups
Chan Chakra
(a)
DU20
DU21DU22
Anteriorhairline
Posteriorhairline
(b)
Figure 10 (a) Location of the Chan Chakra (inside the third ventricle) (b) Illustration of acupoints DU20 (Baihui) DU21 (Qianding) andDU22 (Xinhui) on DU meridian
and the natural powers of the universe in Chan meditationunder a linden tree The orthodox Chan Buddhism wasoriginated by such an exceptional affair that Buddha Shakya-muni transmitted this light of supreme wisdom to the GreatKashiyapa The same path towards perfect enlightenment(Buddhahood) was promulgated in mainland China in 527
by Bodhidharma the 28th patriarch The current patriarchis Chan master Wu Jue Miao Tian the 85th patriarch of theorthodox Chan-Buddhism Sect since the Great KashiyapaIn orthodox Chan-Buddhist practice very few disciples wereable to catch the quintessence since it cannot be taught inany form of lectures Written material and spoken words
Evidence-Based Complementary and Alternative Medicine 11
cannot promulgate the true wisdom of Chan which can onlybe conveyed by the Buddhist Heart-seal Imprint from a truemaster
In Chan meditation practitioners aim to attain the trueself (Buddha nature) with eternal wisdom (Bodhi) throughbody-mind-soul purification Substantially speaking suchpurification procedure involves the journal of transcendingthe physiological state (five sensory organs) themental activ-ities and normal consciousness the subliminal (the manas)consciousness and the Alaya state at which practitioners areable to perceive the sacred light emitted from Buddha natureBuddhist Heart-seal Imprint from the Chan Patriarch is amust to assist in the purification and accomplishment Toprepare for attaining such realm practitioners meditate withfull-lotus half-lotus or leg-crossing posture and sit still tocultivate spiritual Reiki for penetrating into the ten importantChakras In the course of Chan meditation practitionersmust switch their normal chest breathing to the Navel-Chakra breathing (also called ldquofetal breathingrdquo) that is thebreathing scheme for entering into deep meditation Amongthe ten Chakras Chan Chakra locating inside the thirdventricle is the Buddhist paradise implemented in our bodyFigure 10(a) illustrates the location of Chan Chakra
The cun-measurand system is normally used to measureand locate the acupoints To determine the locations ofacupoints DU20 DU21 and DU22 on Governor Vesselmeridian (DU meridian) we first measure the scalp-midlinelength between anterior hairline and posterior hairline thatis divided into 12 cuns The locations are defined as follows
DU20 7 cuns above the posterior hairline and 5 cunsabove the anterior hairlineDU21 35 cuns directly above the anterior hairline or15 cuns anterior to DU20DU22 2 cuns posterior to the anterior hairline or3 cuns anterior to DU20
Acknowledgments
The authors would like to thank Shung-Yu Yo for his assis-tance in data analysis Chan-meditation practitioners of theShakyamuni Buddhist Foundation are gratefully acknowl-edged for their enthusiastic participation in this research asvolunteers This research was supported by the grants fromthe National Science Council of Taiwan (Grant no NSC 100-2221-E-009-006-MY2)
References
[1] T YuH L Tsai andM LHwang ldquoSuppressing tumor progres-sion of in vitro prostate cancer cells by emitted psychosomaticpower through Zen meditationrdquo American Journal of ChineseMedicine vol 31 no 3 pp 499ndash507 2003
[2] K H Coker ldquoMeditation and prostate cancer integrating amindbody interventionwith traditional therapiesrdquo Seminars inUrologic Oncology vol 17 no 2 pp 111ndash118 1999
[3] D Lester ldquoZen and happinessrdquo Psychological Reports vol 84no 2 pp 650ndash651 1999
[4] C R K MacLean K G Walton S R Wenneberg et alldquoEffects of the transcendental meditation program on adaptivemechanisms changes in hormone levels and responses to stressafter 4 months of practicerdquo Psychoneuroendocrinology vol 22no 4 pp 277ndash295 1997
[5] GA Tooley SMArmstrong T RNorman andA Sali ldquoAcuteincreases in night-time plasma melatonin levels following aperiod of meditationrdquo Biological Psychology vol 53 no 1 pp69ndash78 2000
[6] Y-Y Tang Y Ma Y Fan et al ldquoCentral and autonomicnervous system interaction is altered by short-termmeditationrdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 106 no 22 pp 8865ndash8870 2009
[7] A Lutz H A Slagter N B Rawlings A D Francis LL Greischar and R J Davidson ldquoMental training enhancesattentional stability neural and behavioral evidencerdquo Journal ofNeuroscience vol 29 no 42 pp 13418ndash13427 2009
[8] S M Bertisch C C Wee R S Phillips and E P McCarthyldquoAlternative mind-body therapies used by adults with medicalconditionsrdquo Journal of Psychosomatic Research vol 66 no 6 pp511ndash519 2009
[9] W R Marchand ldquoMindfulness-based stress reductionmindfulness-based cognitive therapy and zen meditation fordepression anxiety pain and psychological distressrdquo Journalof Psychiatric Practice vol 18 no 4 pp 233ndash2252 2012
[10] B R Cahn and J Polich ldquoMeditation states and traits EEG ERPand neuroimaging studiesrdquoPsychological Bulletin vol 132 no 2pp 180ndash211 2006
[11] F Travis and J Shear ldquoFocused attention open monitoring andautomatic self-transcending categories to organize meditationsfrom Vedic Buddhist and Chinese traditionsrdquo Consciousnessand Cognition vol 19 no 4 pp 1110ndash1118 2010
[12] P-C Lo M-L Huang and K-M Chang ldquoEEG alpha blockingcorrelated with perception of inner light during Zen medita-tionrdquo American Journal of Chinese Medicine vol 31 no 4 pp629ndash642 2003
[13] H C Liao and P C Lo ldquoInvestigation on spatiotemporalcharacteristics of zen-meditation EEG rhythmsrdquo Journal ofInternational Society of Life Information Science vol 25 no 1pp 63ndash71 2007
[14] H-Y Huang and P-C Lo ldquoEEG dynamics of experienced zenmeditation practitioners probed by complexity index and spec-tral measurerdquo Journal of Medical Engineering and Technologyvol 33 no 4 pp 314ndash321 2009
[15] E K St Louis and E P Lansky ldquoMeditation and epilepsy a stillhung juryrdquoMedical Hypotheses vol 67 no 2 pp 247ndash250 2006
[16] L I Aftanas and S A Golocheikine ldquoHuman anterior andfrontal midline theta and lower alpha reflect emotionallypositive state and internalized attention high-resolution EEGinvestigation of meditationrdquo Neuroscience Letters vol 310 no1 pp 57ndash60 2001
[17] K Ansari-Asl J-J Bellanger F Bartolomei F Wendung andL Senhadji ldquoTime-frequency characterization of interdepen-dencies in nonstationary signals application to epileptic EEGrdquoIEEE Transactions on Biomedical Engineering vol 52 no 7 pp1218ndash1226 2005
[18] F Gans A Y Schumann J W Kantelhardt T Penzel and IFietze ldquoCross-modulated amplitudes and frequencies charac-terize interacting components in complex systemsrdquo PhysicalReview Letters vol 102 no 9 Article ID 098701 2009
12 Evidence-Based Complementary and Alternative Medicine
[19] J Bhattacharya H Petsche and E Pereda ldquoInterdependenciesin the spontaneous EEG while listening to musicrdquo InternationalJournal of Psychophysiology vol 42 no 3 pp 287ndash301 2001
[20] C J Stam ldquoNonlinear dynamical analysis of EEG and MEGreview of an emerging fieldrdquo Clinical Neurophysiology vol 116no 10 pp 2266ndash2301 2005
[21] W Singer ldquoConsciousness and the binding problemrdquo Annals ofthe New York Academy of Sciences vol 929 pp 123ndash146 2001
[22] D Calitoiu B J Oommen and D Nussbaum ldquoLarge-scaleneuro-modeling for understanding and explaining some brain-related chaotic behaviorrdquo Simulation-Transactions of the Societyfor Modeling and Simulation International vol 88 no 11 pp1316ndash1337 2012
[23] F Wendling K Ansari-Asl F Bartolomei and L SenhadjildquoFrom EEG signals to brain connectivity a model-based eval-uation of interdependence measuresrdquo Journal of NeuroscienceMethods vol 183 no 1 pp 9ndash18 2009
[24] H Y Huang and P C Lo ldquoEEG nonlinear interdependencemeasure of brain interactions under zen meditationrdquo Journalof Biomedical Engineering Research vol 29 no 4 pp 286ndash2942008
[25] M Breakspear and J R Terry ldquoDetection and description ofnon-linear interdependence in normal multichannel humanEEG datardquo Clinical Neurophysiology vol 113 no 5 pp 735ndash7532002
[26] M Breakspear and J R Terry ldquoTopographic organizationof nonlinear interdependence in multichannel human EEGrdquoNeuroImage vol 16 no 3 pp 822ndash835 2002
[27] C J Stam M Breakspear A-M van Cappellen van Walsumand B W van Dijk ldquoNonlinear synchronization in EEG andwhole-headMEG recordings of healthy subjectsrdquoHuman BrainMapping vol 19 no 2 pp 63ndash78 2003
[28] U Feldmann and J Bhattacharya ldquoPredictability improvementas an asymmetrical measure of interdependence in bivariatetime seriesrdquo International Journal of Bifurcation and Chaos vol14 no 2 pp 505ndash514 2004
[29] M Rubinov S A Knock C J Stam et al ldquoSmall-worldproperties of nonlinear brain activity in schizophreniardquoHumanBrain Mapping vol 30 no 2 pp 403ndash416 2009
[30] P Mirowski D Madhavan Y LeCun and R KuznieckyldquoClassification of patterns of EEG synchronization for seizurepredictionrdquo Clinical Neurophysiology vol 120 no 11 pp 1927ndash1940 2009
[31] S I Dimitriadis N A Laskaris Y del Rio-Portilla and G CKoudounis ldquoCharacterizing dynamic functional connectivityacross sleep stages from EEGrdquo Brain Topography vol 22 no 2pp 119ndash133 2009
[32] K Sibsambhu and R Aurobinda ldquoEffect of sleep deprivation onfunctional connectivity of EEG channelsrdquo IEEE Transcations onSystems Man and Cybernetics vol 43 no 3 pp 666ndash672 2013
[33] C M W J M Tian Chan Master Miao Tianrsquos Book of Wisdomand the Guide to Heart Chan Meditation Lulu 2010
[34] X-S Zhang R J Roy and E W Jensen ldquoEEG complexity as ameasure of depth of anesthesia for patientsrdquo IEEE Transactionson Biomedical Engineering vol 48 no 12 pp 1424ndash1433 2001
[35] I Daubechies Ten Lectures on Wavelets Society for Industrialand Applied Mathematics Philadelphia Pa USA 1992
[36] C Heil D F Walnut and I Daubechies Fundamental Papersin Wavelet Theory Princeton University Press Princeton NJUSA 2006
[37] C Y Liu and P C Lo ldquoSpatial focalization of zen-meditationbrain based on EEGrdquo Journal of Biomedical EngineeringResearch vol 29 pp 17ndash24 2008
[38] H Adeli Z Zhou and N Dadmehr ldquoAnalysis of EEG recordsin an epileptic patient using wavelet transformrdquo Journal ofNeuroscience Methods vol 123 no 1 pp 69ndash87 2003
[39] F Takens ldquoDetecting strange attractors in turbulencerdquo inDynamical Systems and Turbulence D A Rand and L S YoungEds vol 898 of Lecture Notes in Mathematics pp 366ndash381Springer New York NY USA 1981
[40] P-C Lo and W-P Chung ldquoAn approach to quantifying themulti-channel EEG spatial-temporal featurerdquo Biometrical Jour-nal vol 42 no 7 pp 901ndash916 2000
[41] W S Pritchard and D W Duke ldquoDimensional analysis of no-task human EEG using the Grassberger-Procaccia methodrdquoPsychophysiology vol 29 no 2 pp 182ndash192 1992
[42] R Q Quiroga A Kraskov T Kreuz and P GrassbergerldquoPerformance of different synchronization measures in realdata a case study on electroencephalographic signalsrdquo PhysicalReview E vol 65 no 4 Article ID 041903 14 pages 2002
8 Evidence-Based Complementary and Alternative Medicine
Table 1 Group averages and standard deviations of 119878(FrarrP) 119878(Prarr F) 119878(LTrarrRT) and 119878(RTrarr LT) at three experimental stages (R Mand C) including the 119875 values of student 119905-test for 119878(FrarrP)-119878(Prarr F) and 119878(LTrarrRT)-119878(RTrarr LT) pairs
Group average 056 051 060 061Group std 005 005 007 005119875 value 00055 03476
MGroup average 056 050 060 061Group std 003 006 006 004119875 value 00031 01987
CGroup average 055 049 061 061Group std 007 006 006 006119875 value 00302 03953
suggest the inactive behaviors of parietal-occipital lobes sinceregion P encompasses the EEG-electrode sites of parietal andoccipital lobesThe parietal lobe is responsible for integratingsensory information from various parts of the body withthe particular functions of determining spatial sense andnavigation Functions of occipital lobe mainly include visualreception visual-spatial processing and color recognitionAs described previously the core essence of orthodox Chan-meditation practice is to transcend physiological mental andall states of consciousness to prove the existence of true beingThe inactive posterior regions may provide the evidence ofbrain rewiring in preparation for such transcendence
Region C encompasses three midline electrodes locatingfrom precentral to postcentral cortex Region C as the sourceapparently dominates over the other four regions regardlessof the stages On the other hand region C as the passive role isaffected mostly among the five regions Region C constantlyexhibits the largest RII at all stages
Wemay draw a tentative hypothesis from the mechanismof Chan-meditation practice Practitioners are required tokeep Chan Chakra active at any moment that results inthe formation of an energy pathway between Chan Chakraand Qian-Ding acupoint on scalp (Figure 10(b)) Does suchphysiological reformation correlate to the significant effec-tiveness of region C It leaves an open question for futureinvestigation
RII characterizing the regional interdependence behavesdifferently for each region when the experimental subjectsswitch their mental states from R (resting) to M (medita-tion) or from R to C (Chakra focusing) To investigate theeffect of different experimental sessions the RII percentageincreasedecrease from stage R to M and from stage R to Cwere computed for each of the five regions (F P C LT andRT)acting as either the active or the passive role In comparisonof RII between stage M and stage R the percentage largerthan 1 was observed in the regions of LTactive(minus124)RTactive (125) and Cpassive (minus107) On the other handthe regions of significant change in RII when comparingstage C with R include Factive (minus184) Pactive (minus178) andCactive (239) On the basis of RII of stage R for each
individual region we summarize the changes of RII at stagesM and C as follows
(1) In the active-role analysis region LT becomes moredeactivated at stage M while region RT becomesmore activatedWhenmeditation subjects focused onChan Chakra the active driving strength of regionC increases significantly (239) On the other handsuppression of the source activity occurs to bothregions F and P (the regions anterior to and posteriorto region C)
(2) In the passive-role analysis only region C becomesnotably deactivated at stage M (free meditation) Ingeneral differences are trivial in comparison of119877119868119868passive between stages M and R
(3) Chan meditation deactivates the left brain hemi-sphere whereas it inactivates the right brain hemi-sphere
Except for region P the active-role effectiveness of a givenregion is better than its passive-role effectiveness
33 Inter-Region Interdependence AnalysismdashControl GroupIn control group the group average and standard deviationof 119878(F rarr P) 119878(P rarr F) 119878(LT rarr RT) and 119878(RT rarr LT) atstage R are respectively 055 plusmn 004 051 plusmn 004 059 plusmn 003and 058 plusmn 004 The 119875 values of student 119905-test for 119878(F rarr
P)-119878(P rarr F) and 119878(LT rarr RT)-119878(RT rarr LT) pairs are0002 and 0457The results also reveal the frontal dominanceand left-right lateral balance for the control group at rest Yetcompared with the Chan-meditation practitioners controlgroup exhibits weaker strength of effectiveness no matter ifthe region plays an active or a passive role
To explore the average effectiveness of a given ROI weaveraged the RIIs for the region in connection with the otherfour regions Figure 7 displays how a given ROI (F P C LT orRT) influences (active) or is influenced (passive) by the otherregions Similar to the results of experimental group regionP as either the active or passive role exhibits the weakest linksto the other regions
Evidence-Based Complementary and Alternative Medicine 9
Sink
Source
070
065
060
055
050
045
040F P C LT RT
Figure 7 Average effectiveness of each region playing either theactive or passive role
Comparing the efficacy of two counteractive roles playedby the same region we observe that the source-role effective-ness of a given ROI is higher than its sink-role effectivenessexcept region P
34 Comparison between Experimental and Control GroupsFigure 8 illustrates the group averages of RIIs including119878(F rarr P) 119878(P rarr F) 119878(LT rarr RT) and 119878(RT rarr LT)for the experimental group at three stages (R M and C)and for the control group at rest Experimental group revealsmuch more intensive lateral (LT larrrarr RT) interactions thancontrol group The differences are statistically significant forexperimental group at stage M (119875 = 00336) and at stage C(119875 = 00411) On the other hand region P responsible forspatial sense and navigation becomes comparatively inactivefor Chan-meditation practitioners at stage C
The assembling illustration in Figure 9 is used to comparethe average effectiveness of each region between two groupsExperimental group playing either a source role or a sinkrole apparently exhibits higher average effectiveness in allfive regions The extraordinarily large RIIs for region Cparticularly acting the source role may be assumed to becorrelated with the strengthening of neural networks ofregion C dominating over the other regions through thespiritual focusing on Chan Chakra According to the post-experimental interview with Chan-meditation practitionerssuch central (FCz-Cz-CPz) dominating behavior could belinked to theChan-Chakra activation that further induces theperception of grand solemn energy flow in and out throughthe cortical regions defined by acupoints DU20 (Baihui)DU21 (Qianding) and DU22 (Xinhui) in TCM (traditionalChinese Medicine) Figure 10(b) (Appendix) illustrates thelocations of these three acupoints
4 Conclusion
The time-transcending nonmaterial sacred spiritual experi-ences of Chan-meditation practitioners bring our attention tothe study of the unique interactions among regional neuralnetworks in the brain Scientific approach to the scope of
Exp (stage R)Exp (stage M)
Exp (stage C)Control
065
060
055
050
045F rarr P P rarr F LT rarr RT RT rarr LT
Figure 8 Group averages of RIIs (119878(F rarr P) 119878(P rarr F) 119878(LT rarr
RT) and 119878(RT rarr LT)) for experimental group at three stages andfor control group at rest
Chan meditation provides insight into the mechanism inaddition to the vague sketch of meditation sensation and itsmultiform benefits to human beings This paper presents ourpreliminary results based on nonlinear dynamical theory ofexploring the spatial interactions among brain local neuralnetworks under alpha-rhythmic oscillationQuantification ofnonlinear interdependence based on similarity index revealssignificant intergroup difference Significant higher lateralinteractions between left and right temporal regions wereobserved in Chan-meditation practitioners at the stages ofChan meditation and Chakra-focusing practice In Chanpractice practitioners follow the doctrine that the mind canbe enlightened only if it surrenders its leadership power tothe ldquoheartrdquo (Bodhi the true self with eternal wisdom) Theyaccordingly can experience better balance and integrationof the brain hemispheres through years of Chan-meditationpractice
Chan-Chakra spiritual focusing (at stage C) remarkablystrengthens the central neural-network dominance over theother regions On the other hand suppression of the sourceactivity in regions F and P at stage C appears to reveal themeditation state of transcending the realm of physical bodyand mind The particular central (FCz-Cz-CPz) dominatingphenomenon is reflected in long-term Chan practitioners asone of the metamorphosing processes that opens the energypathway between Chan Chakra and the central-line scalpfrom acupoint DU20 to DU22 (Figure 10(b) in Appendix)In the case practitioners experience tranquil brain and calmmind in every moment Chan-meditation practice is to real-ize a Chan-style brain and Chan-style physical body insteadof merely sitting still for one hour to pursue temporary peaceof mind and relief of body
Appendix
Chan meditation originating more than 2500 years ago hasbeen proved to benefit the health while on the way toward theultimate Buddhahood state Buddha Shakyamuni disclosedthe eternal truth the supreme wisdom the noumenal energy
10 Evidence-Based Complementary and Alternative Medicine
Source070
065
060
055
050
F P C LT RT
Exp (R)Exp (M)
Exp (C)Control
(a)
Sink070
065
060
055
050
F P C LT RT
Exp (R)Exp (M)
Exp (C)Control
(b)
Figure 9 Comparison of average effectiveness of each region as a source (a) or a sink (b) between experimental and control groups
Chan Chakra
(a)
DU20
DU21DU22
Anteriorhairline
Posteriorhairline
(b)
Figure 10 (a) Location of the Chan Chakra (inside the third ventricle) (b) Illustration of acupoints DU20 (Baihui) DU21 (Qianding) andDU22 (Xinhui) on DU meridian
and the natural powers of the universe in Chan meditationunder a linden tree The orthodox Chan Buddhism wasoriginated by such an exceptional affair that Buddha Shakya-muni transmitted this light of supreme wisdom to the GreatKashiyapa The same path towards perfect enlightenment(Buddhahood) was promulgated in mainland China in 527
by Bodhidharma the 28th patriarch The current patriarchis Chan master Wu Jue Miao Tian the 85th patriarch of theorthodox Chan-Buddhism Sect since the Great KashiyapaIn orthodox Chan-Buddhist practice very few disciples wereable to catch the quintessence since it cannot be taught inany form of lectures Written material and spoken words
Evidence-Based Complementary and Alternative Medicine 11
cannot promulgate the true wisdom of Chan which can onlybe conveyed by the Buddhist Heart-seal Imprint from a truemaster
In Chan meditation practitioners aim to attain the trueself (Buddha nature) with eternal wisdom (Bodhi) throughbody-mind-soul purification Substantially speaking suchpurification procedure involves the journal of transcendingthe physiological state (five sensory organs) themental activ-ities and normal consciousness the subliminal (the manas)consciousness and the Alaya state at which practitioners areable to perceive the sacred light emitted from Buddha natureBuddhist Heart-seal Imprint from the Chan Patriarch is amust to assist in the purification and accomplishment Toprepare for attaining such realm practitioners meditate withfull-lotus half-lotus or leg-crossing posture and sit still tocultivate spiritual Reiki for penetrating into the ten importantChakras In the course of Chan meditation practitionersmust switch their normal chest breathing to the Navel-Chakra breathing (also called ldquofetal breathingrdquo) that is thebreathing scheme for entering into deep meditation Amongthe ten Chakras Chan Chakra locating inside the thirdventricle is the Buddhist paradise implemented in our bodyFigure 10(a) illustrates the location of Chan Chakra
The cun-measurand system is normally used to measureand locate the acupoints To determine the locations ofacupoints DU20 DU21 and DU22 on Governor Vesselmeridian (DU meridian) we first measure the scalp-midlinelength between anterior hairline and posterior hairline thatis divided into 12 cuns The locations are defined as follows
DU20 7 cuns above the posterior hairline and 5 cunsabove the anterior hairlineDU21 35 cuns directly above the anterior hairline or15 cuns anterior to DU20DU22 2 cuns posterior to the anterior hairline or3 cuns anterior to DU20
Acknowledgments
The authors would like to thank Shung-Yu Yo for his assis-tance in data analysis Chan-meditation practitioners of theShakyamuni Buddhist Foundation are gratefully acknowl-edged for their enthusiastic participation in this research asvolunteers This research was supported by the grants fromthe National Science Council of Taiwan (Grant no NSC 100-2221-E-009-006-MY2)
References
[1] T YuH L Tsai andM LHwang ldquoSuppressing tumor progres-sion of in vitro prostate cancer cells by emitted psychosomaticpower through Zen meditationrdquo American Journal of ChineseMedicine vol 31 no 3 pp 499ndash507 2003
[2] K H Coker ldquoMeditation and prostate cancer integrating amindbody interventionwith traditional therapiesrdquo Seminars inUrologic Oncology vol 17 no 2 pp 111ndash118 1999
[3] D Lester ldquoZen and happinessrdquo Psychological Reports vol 84no 2 pp 650ndash651 1999
[4] C R K MacLean K G Walton S R Wenneberg et alldquoEffects of the transcendental meditation program on adaptivemechanisms changes in hormone levels and responses to stressafter 4 months of practicerdquo Psychoneuroendocrinology vol 22no 4 pp 277ndash295 1997
[5] GA Tooley SMArmstrong T RNorman andA Sali ldquoAcuteincreases in night-time plasma melatonin levels following aperiod of meditationrdquo Biological Psychology vol 53 no 1 pp69ndash78 2000
[6] Y-Y Tang Y Ma Y Fan et al ldquoCentral and autonomicnervous system interaction is altered by short-termmeditationrdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 106 no 22 pp 8865ndash8870 2009
[7] A Lutz H A Slagter N B Rawlings A D Francis LL Greischar and R J Davidson ldquoMental training enhancesattentional stability neural and behavioral evidencerdquo Journal ofNeuroscience vol 29 no 42 pp 13418ndash13427 2009
[8] S M Bertisch C C Wee R S Phillips and E P McCarthyldquoAlternative mind-body therapies used by adults with medicalconditionsrdquo Journal of Psychosomatic Research vol 66 no 6 pp511ndash519 2009
[9] W R Marchand ldquoMindfulness-based stress reductionmindfulness-based cognitive therapy and zen meditation fordepression anxiety pain and psychological distressrdquo Journalof Psychiatric Practice vol 18 no 4 pp 233ndash2252 2012
[10] B R Cahn and J Polich ldquoMeditation states and traits EEG ERPand neuroimaging studiesrdquoPsychological Bulletin vol 132 no 2pp 180ndash211 2006
[11] F Travis and J Shear ldquoFocused attention open monitoring andautomatic self-transcending categories to organize meditationsfrom Vedic Buddhist and Chinese traditionsrdquo Consciousnessand Cognition vol 19 no 4 pp 1110ndash1118 2010
[12] P-C Lo M-L Huang and K-M Chang ldquoEEG alpha blockingcorrelated with perception of inner light during Zen medita-tionrdquo American Journal of Chinese Medicine vol 31 no 4 pp629ndash642 2003
[13] H C Liao and P C Lo ldquoInvestigation on spatiotemporalcharacteristics of zen-meditation EEG rhythmsrdquo Journal ofInternational Society of Life Information Science vol 25 no 1pp 63ndash71 2007
[14] H-Y Huang and P-C Lo ldquoEEG dynamics of experienced zenmeditation practitioners probed by complexity index and spec-tral measurerdquo Journal of Medical Engineering and Technologyvol 33 no 4 pp 314ndash321 2009
[15] E K St Louis and E P Lansky ldquoMeditation and epilepsy a stillhung juryrdquoMedical Hypotheses vol 67 no 2 pp 247ndash250 2006
[16] L I Aftanas and S A Golocheikine ldquoHuman anterior andfrontal midline theta and lower alpha reflect emotionallypositive state and internalized attention high-resolution EEGinvestigation of meditationrdquo Neuroscience Letters vol 310 no1 pp 57ndash60 2001
[17] K Ansari-Asl J-J Bellanger F Bartolomei F Wendung andL Senhadji ldquoTime-frequency characterization of interdepen-dencies in nonstationary signals application to epileptic EEGrdquoIEEE Transactions on Biomedical Engineering vol 52 no 7 pp1218ndash1226 2005
[18] F Gans A Y Schumann J W Kantelhardt T Penzel and IFietze ldquoCross-modulated amplitudes and frequencies charac-terize interacting components in complex systemsrdquo PhysicalReview Letters vol 102 no 9 Article ID 098701 2009
12 Evidence-Based Complementary and Alternative Medicine
[19] J Bhattacharya H Petsche and E Pereda ldquoInterdependenciesin the spontaneous EEG while listening to musicrdquo InternationalJournal of Psychophysiology vol 42 no 3 pp 287ndash301 2001
[20] C J Stam ldquoNonlinear dynamical analysis of EEG and MEGreview of an emerging fieldrdquo Clinical Neurophysiology vol 116no 10 pp 2266ndash2301 2005
[21] W Singer ldquoConsciousness and the binding problemrdquo Annals ofthe New York Academy of Sciences vol 929 pp 123ndash146 2001
[22] D Calitoiu B J Oommen and D Nussbaum ldquoLarge-scaleneuro-modeling for understanding and explaining some brain-related chaotic behaviorrdquo Simulation-Transactions of the Societyfor Modeling and Simulation International vol 88 no 11 pp1316ndash1337 2012
[23] F Wendling K Ansari-Asl F Bartolomei and L SenhadjildquoFrom EEG signals to brain connectivity a model-based eval-uation of interdependence measuresrdquo Journal of NeuroscienceMethods vol 183 no 1 pp 9ndash18 2009
[24] H Y Huang and P C Lo ldquoEEG nonlinear interdependencemeasure of brain interactions under zen meditationrdquo Journalof Biomedical Engineering Research vol 29 no 4 pp 286ndash2942008
[25] M Breakspear and J R Terry ldquoDetection and description ofnon-linear interdependence in normal multichannel humanEEG datardquo Clinical Neurophysiology vol 113 no 5 pp 735ndash7532002
[26] M Breakspear and J R Terry ldquoTopographic organizationof nonlinear interdependence in multichannel human EEGrdquoNeuroImage vol 16 no 3 pp 822ndash835 2002
[27] C J Stam M Breakspear A-M van Cappellen van Walsumand B W van Dijk ldquoNonlinear synchronization in EEG andwhole-headMEG recordings of healthy subjectsrdquoHuman BrainMapping vol 19 no 2 pp 63ndash78 2003
[28] U Feldmann and J Bhattacharya ldquoPredictability improvementas an asymmetrical measure of interdependence in bivariatetime seriesrdquo International Journal of Bifurcation and Chaos vol14 no 2 pp 505ndash514 2004
[29] M Rubinov S A Knock C J Stam et al ldquoSmall-worldproperties of nonlinear brain activity in schizophreniardquoHumanBrain Mapping vol 30 no 2 pp 403ndash416 2009
[30] P Mirowski D Madhavan Y LeCun and R KuznieckyldquoClassification of patterns of EEG synchronization for seizurepredictionrdquo Clinical Neurophysiology vol 120 no 11 pp 1927ndash1940 2009
[31] S I Dimitriadis N A Laskaris Y del Rio-Portilla and G CKoudounis ldquoCharacterizing dynamic functional connectivityacross sleep stages from EEGrdquo Brain Topography vol 22 no 2pp 119ndash133 2009
[32] K Sibsambhu and R Aurobinda ldquoEffect of sleep deprivation onfunctional connectivity of EEG channelsrdquo IEEE Transcations onSystems Man and Cybernetics vol 43 no 3 pp 666ndash672 2013
[33] C M W J M Tian Chan Master Miao Tianrsquos Book of Wisdomand the Guide to Heart Chan Meditation Lulu 2010
[34] X-S Zhang R J Roy and E W Jensen ldquoEEG complexity as ameasure of depth of anesthesia for patientsrdquo IEEE Transactionson Biomedical Engineering vol 48 no 12 pp 1424ndash1433 2001
[35] I Daubechies Ten Lectures on Wavelets Society for Industrialand Applied Mathematics Philadelphia Pa USA 1992
[36] C Heil D F Walnut and I Daubechies Fundamental Papersin Wavelet Theory Princeton University Press Princeton NJUSA 2006
[37] C Y Liu and P C Lo ldquoSpatial focalization of zen-meditationbrain based on EEGrdquo Journal of Biomedical EngineeringResearch vol 29 pp 17ndash24 2008
[38] H Adeli Z Zhou and N Dadmehr ldquoAnalysis of EEG recordsin an epileptic patient using wavelet transformrdquo Journal ofNeuroscience Methods vol 123 no 1 pp 69ndash87 2003
[39] F Takens ldquoDetecting strange attractors in turbulencerdquo inDynamical Systems and Turbulence D A Rand and L S YoungEds vol 898 of Lecture Notes in Mathematics pp 366ndash381Springer New York NY USA 1981
[40] P-C Lo and W-P Chung ldquoAn approach to quantifying themulti-channel EEG spatial-temporal featurerdquo Biometrical Jour-nal vol 42 no 7 pp 901ndash916 2000
[41] W S Pritchard and D W Duke ldquoDimensional analysis of no-task human EEG using the Grassberger-Procaccia methodrdquoPsychophysiology vol 29 no 2 pp 182ndash192 1992
[42] R Q Quiroga A Kraskov T Kreuz and P GrassbergerldquoPerformance of different synchronization measures in realdata a case study on electroencephalographic signalsrdquo PhysicalReview E vol 65 no 4 Article ID 041903 14 pages 2002
Evidence-Based Complementary and Alternative Medicine 9
Sink
Source
070
065
060
055
050
045
040F P C LT RT
Figure 7 Average effectiveness of each region playing either theactive or passive role
Comparing the efficacy of two counteractive roles playedby the same region we observe that the source-role effective-ness of a given ROI is higher than its sink-role effectivenessexcept region P
34 Comparison between Experimental and Control GroupsFigure 8 illustrates the group averages of RIIs including119878(F rarr P) 119878(P rarr F) 119878(LT rarr RT) and 119878(RT rarr LT)for the experimental group at three stages (R M and C)and for the control group at rest Experimental group revealsmuch more intensive lateral (LT larrrarr RT) interactions thancontrol group The differences are statistically significant forexperimental group at stage M (119875 = 00336) and at stage C(119875 = 00411) On the other hand region P responsible forspatial sense and navigation becomes comparatively inactivefor Chan-meditation practitioners at stage C
The assembling illustration in Figure 9 is used to comparethe average effectiveness of each region between two groupsExperimental group playing either a source role or a sinkrole apparently exhibits higher average effectiveness in allfive regions The extraordinarily large RIIs for region Cparticularly acting the source role may be assumed to becorrelated with the strengthening of neural networks ofregion C dominating over the other regions through thespiritual focusing on Chan Chakra According to the post-experimental interview with Chan-meditation practitionerssuch central (FCz-Cz-CPz) dominating behavior could belinked to theChan-Chakra activation that further induces theperception of grand solemn energy flow in and out throughthe cortical regions defined by acupoints DU20 (Baihui)DU21 (Qianding) and DU22 (Xinhui) in TCM (traditionalChinese Medicine) Figure 10(b) (Appendix) illustrates thelocations of these three acupoints
4 Conclusion
The time-transcending nonmaterial sacred spiritual experi-ences of Chan-meditation practitioners bring our attention tothe study of the unique interactions among regional neuralnetworks in the brain Scientific approach to the scope of
Exp (stage R)Exp (stage M)
Exp (stage C)Control
065
060
055
050
045F rarr P P rarr F LT rarr RT RT rarr LT
Figure 8 Group averages of RIIs (119878(F rarr P) 119878(P rarr F) 119878(LT rarr
RT) and 119878(RT rarr LT)) for experimental group at three stages andfor control group at rest
Chan meditation provides insight into the mechanism inaddition to the vague sketch of meditation sensation and itsmultiform benefits to human beings This paper presents ourpreliminary results based on nonlinear dynamical theory ofexploring the spatial interactions among brain local neuralnetworks under alpha-rhythmic oscillationQuantification ofnonlinear interdependence based on similarity index revealssignificant intergroup difference Significant higher lateralinteractions between left and right temporal regions wereobserved in Chan-meditation practitioners at the stages ofChan meditation and Chakra-focusing practice In Chanpractice practitioners follow the doctrine that the mind canbe enlightened only if it surrenders its leadership power tothe ldquoheartrdquo (Bodhi the true self with eternal wisdom) Theyaccordingly can experience better balance and integrationof the brain hemispheres through years of Chan-meditationpractice
Chan-Chakra spiritual focusing (at stage C) remarkablystrengthens the central neural-network dominance over theother regions On the other hand suppression of the sourceactivity in regions F and P at stage C appears to reveal themeditation state of transcending the realm of physical bodyand mind The particular central (FCz-Cz-CPz) dominatingphenomenon is reflected in long-term Chan practitioners asone of the metamorphosing processes that opens the energypathway between Chan Chakra and the central-line scalpfrom acupoint DU20 to DU22 (Figure 10(b) in Appendix)In the case practitioners experience tranquil brain and calmmind in every moment Chan-meditation practice is to real-ize a Chan-style brain and Chan-style physical body insteadof merely sitting still for one hour to pursue temporary peaceof mind and relief of body
Appendix
Chan meditation originating more than 2500 years ago hasbeen proved to benefit the health while on the way toward theultimate Buddhahood state Buddha Shakyamuni disclosedthe eternal truth the supreme wisdom the noumenal energy
10 Evidence-Based Complementary and Alternative Medicine
Source070
065
060
055
050
F P C LT RT
Exp (R)Exp (M)
Exp (C)Control
(a)
Sink070
065
060
055
050
F P C LT RT
Exp (R)Exp (M)
Exp (C)Control
(b)
Figure 9 Comparison of average effectiveness of each region as a source (a) or a sink (b) between experimental and control groups
Chan Chakra
(a)
DU20
DU21DU22
Anteriorhairline
Posteriorhairline
(b)
Figure 10 (a) Location of the Chan Chakra (inside the third ventricle) (b) Illustration of acupoints DU20 (Baihui) DU21 (Qianding) andDU22 (Xinhui) on DU meridian
and the natural powers of the universe in Chan meditationunder a linden tree The orthodox Chan Buddhism wasoriginated by such an exceptional affair that Buddha Shakya-muni transmitted this light of supreme wisdom to the GreatKashiyapa The same path towards perfect enlightenment(Buddhahood) was promulgated in mainland China in 527
by Bodhidharma the 28th patriarch The current patriarchis Chan master Wu Jue Miao Tian the 85th patriarch of theorthodox Chan-Buddhism Sect since the Great KashiyapaIn orthodox Chan-Buddhist practice very few disciples wereable to catch the quintessence since it cannot be taught inany form of lectures Written material and spoken words
Evidence-Based Complementary and Alternative Medicine 11
cannot promulgate the true wisdom of Chan which can onlybe conveyed by the Buddhist Heart-seal Imprint from a truemaster
In Chan meditation practitioners aim to attain the trueself (Buddha nature) with eternal wisdom (Bodhi) throughbody-mind-soul purification Substantially speaking suchpurification procedure involves the journal of transcendingthe physiological state (five sensory organs) themental activ-ities and normal consciousness the subliminal (the manas)consciousness and the Alaya state at which practitioners areable to perceive the sacred light emitted from Buddha natureBuddhist Heart-seal Imprint from the Chan Patriarch is amust to assist in the purification and accomplishment Toprepare for attaining such realm practitioners meditate withfull-lotus half-lotus or leg-crossing posture and sit still tocultivate spiritual Reiki for penetrating into the ten importantChakras In the course of Chan meditation practitionersmust switch their normal chest breathing to the Navel-Chakra breathing (also called ldquofetal breathingrdquo) that is thebreathing scheme for entering into deep meditation Amongthe ten Chakras Chan Chakra locating inside the thirdventricle is the Buddhist paradise implemented in our bodyFigure 10(a) illustrates the location of Chan Chakra
The cun-measurand system is normally used to measureand locate the acupoints To determine the locations ofacupoints DU20 DU21 and DU22 on Governor Vesselmeridian (DU meridian) we first measure the scalp-midlinelength between anterior hairline and posterior hairline thatis divided into 12 cuns The locations are defined as follows
DU20 7 cuns above the posterior hairline and 5 cunsabove the anterior hairlineDU21 35 cuns directly above the anterior hairline or15 cuns anterior to DU20DU22 2 cuns posterior to the anterior hairline or3 cuns anterior to DU20
Acknowledgments
The authors would like to thank Shung-Yu Yo for his assis-tance in data analysis Chan-meditation practitioners of theShakyamuni Buddhist Foundation are gratefully acknowl-edged for their enthusiastic participation in this research asvolunteers This research was supported by the grants fromthe National Science Council of Taiwan (Grant no NSC 100-2221-E-009-006-MY2)
References
[1] T YuH L Tsai andM LHwang ldquoSuppressing tumor progres-sion of in vitro prostate cancer cells by emitted psychosomaticpower through Zen meditationrdquo American Journal of ChineseMedicine vol 31 no 3 pp 499ndash507 2003
[2] K H Coker ldquoMeditation and prostate cancer integrating amindbody interventionwith traditional therapiesrdquo Seminars inUrologic Oncology vol 17 no 2 pp 111ndash118 1999
[3] D Lester ldquoZen and happinessrdquo Psychological Reports vol 84no 2 pp 650ndash651 1999
[4] C R K MacLean K G Walton S R Wenneberg et alldquoEffects of the transcendental meditation program on adaptivemechanisms changes in hormone levels and responses to stressafter 4 months of practicerdquo Psychoneuroendocrinology vol 22no 4 pp 277ndash295 1997
[5] GA Tooley SMArmstrong T RNorman andA Sali ldquoAcuteincreases in night-time plasma melatonin levels following aperiod of meditationrdquo Biological Psychology vol 53 no 1 pp69ndash78 2000
[6] Y-Y Tang Y Ma Y Fan et al ldquoCentral and autonomicnervous system interaction is altered by short-termmeditationrdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 106 no 22 pp 8865ndash8870 2009
[7] A Lutz H A Slagter N B Rawlings A D Francis LL Greischar and R J Davidson ldquoMental training enhancesattentional stability neural and behavioral evidencerdquo Journal ofNeuroscience vol 29 no 42 pp 13418ndash13427 2009
[8] S M Bertisch C C Wee R S Phillips and E P McCarthyldquoAlternative mind-body therapies used by adults with medicalconditionsrdquo Journal of Psychosomatic Research vol 66 no 6 pp511ndash519 2009
[9] W R Marchand ldquoMindfulness-based stress reductionmindfulness-based cognitive therapy and zen meditation fordepression anxiety pain and psychological distressrdquo Journalof Psychiatric Practice vol 18 no 4 pp 233ndash2252 2012
[10] B R Cahn and J Polich ldquoMeditation states and traits EEG ERPand neuroimaging studiesrdquoPsychological Bulletin vol 132 no 2pp 180ndash211 2006
[11] F Travis and J Shear ldquoFocused attention open monitoring andautomatic self-transcending categories to organize meditationsfrom Vedic Buddhist and Chinese traditionsrdquo Consciousnessand Cognition vol 19 no 4 pp 1110ndash1118 2010
[12] P-C Lo M-L Huang and K-M Chang ldquoEEG alpha blockingcorrelated with perception of inner light during Zen medita-tionrdquo American Journal of Chinese Medicine vol 31 no 4 pp629ndash642 2003
[13] H C Liao and P C Lo ldquoInvestigation on spatiotemporalcharacteristics of zen-meditation EEG rhythmsrdquo Journal ofInternational Society of Life Information Science vol 25 no 1pp 63ndash71 2007
[14] H-Y Huang and P-C Lo ldquoEEG dynamics of experienced zenmeditation practitioners probed by complexity index and spec-tral measurerdquo Journal of Medical Engineering and Technologyvol 33 no 4 pp 314ndash321 2009
[15] E K St Louis and E P Lansky ldquoMeditation and epilepsy a stillhung juryrdquoMedical Hypotheses vol 67 no 2 pp 247ndash250 2006
[16] L I Aftanas and S A Golocheikine ldquoHuman anterior andfrontal midline theta and lower alpha reflect emotionallypositive state and internalized attention high-resolution EEGinvestigation of meditationrdquo Neuroscience Letters vol 310 no1 pp 57ndash60 2001
[17] K Ansari-Asl J-J Bellanger F Bartolomei F Wendung andL Senhadji ldquoTime-frequency characterization of interdepen-dencies in nonstationary signals application to epileptic EEGrdquoIEEE Transactions on Biomedical Engineering vol 52 no 7 pp1218ndash1226 2005
[18] F Gans A Y Schumann J W Kantelhardt T Penzel and IFietze ldquoCross-modulated amplitudes and frequencies charac-terize interacting components in complex systemsrdquo PhysicalReview Letters vol 102 no 9 Article ID 098701 2009
12 Evidence-Based Complementary and Alternative Medicine
[19] J Bhattacharya H Petsche and E Pereda ldquoInterdependenciesin the spontaneous EEG while listening to musicrdquo InternationalJournal of Psychophysiology vol 42 no 3 pp 287ndash301 2001
[20] C J Stam ldquoNonlinear dynamical analysis of EEG and MEGreview of an emerging fieldrdquo Clinical Neurophysiology vol 116no 10 pp 2266ndash2301 2005
[21] W Singer ldquoConsciousness and the binding problemrdquo Annals ofthe New York Academy of Sciences vol 929 pp 123ndash146 2001
[22] D Calitoiu B J Oommen and D Nussbaum ldquoLarge-scaleneuro-modeling for understanding and explaining some brain-related chaotic behaviorrdquo Simulation-Transactions of the Societyfor Modeling and Simulation International vol 88 no 11 pp1316ndash1337 2012
[23] F Wendling K Ansari-Asl F Bartolomei and L SenhadjildquoFrom EEG signals to brain connectivity a model-based eval-uation of interdependence measuresrdquo Journal of NeuroscienceMethods vol 183 no 1 pp 9ndash18 2009
[24] H Y Huang and P C Lo ldquoEEG nonlinear interdependencemeasure of brain interactions under zen meditationrdquo Journalof Biomedical Engineering Research vol 29 no 4 pp 286ndash2942008
[25] M Breakspear and J R Terry ldquoDetection and description ofnon-linear interdependence in normal multichannel humanEEG datardquo Clinical Neurophysiology vol 113 no 5 pp 735ndash7532002
[26] M Breakspear and J R Terry ldquoTopographic organizationof nonlinear interdependence in multichannel human EEGrdquoNeuroImage vol 16 no 3 pp 822ndash835 2002
[27] C J Stam M Breakspear A-M van Cappellen van Walsumand B W van Dijk ldquoNonlinear synchronization in EEG andwhole-headMEG recordings of healthy subjectsrdquoHuman BrainMapping vol 19 no 2 pp 63ndash78 2003
[28] U Feldmann and J Bhattacharya ldquoPredictability improvementas an asymmetrical measure of interdependence in bivariatetime seriesrdquo International Journal of Bifurcation and Chaos vol14 no 2 pp 505ndash514 2004
[29] M Rubinov S A Knock C J Stam et al ldquoSmall-worldproperties of nonlinear brain activity in schizophreniardquoHumanBrain Mapping vol 30 no 2 pp 403ndash416 2009
[30] P Mirowski D Madhavan Y LeCun and R KuznieckyldquoClassification of patterns of EEG synchronization for seizurepredictionrdquo Clinical Neurophysiology vol 120 no 11 pp 1927ndash1940 2009
[31] S I Dimitriadis N A Laskaris Y del Rio-Portilla and G CKoudounis ldquoCharacterizing dynamic functional connectivityacross sleep stages from EEGrdquo Brain Topography vol 22 no 2pp 119ndash133 2009
[32] K Sibsambhu and R Aurobinda ldquoEffect of sleep deprivation onfunctional connectivity of EEG channelsrdquo IEEE Transcations onSystems Man and Cybernetics vol 43 no 3 pp 666ndash672 2013
[33] C M W J M Tian Chan Master Miao Tianrsquos Book of Wisdomand the Guide to Heart Chan Meditation Lulu 2010
[34] X-S Zhang R J Roy and E W Jensen ldquoEEG complexity as ameasure of depth of anesthesia for patientsrdquo IEEE Transactionson Biomedical Engineering vol 48 no 12 pp 1424ndash1433 2001
[35] I Daubechies Ten Lectures on Wavelets Society for Industrialand Applied Mathematics Philadelphia Pa USA 1992
[36] C Heil D F Walnut and I Daubechies Fundamental Papersin Wavelet Theory Princeton University Press Princeton NJUSA 2006
[37] C Y Liu and P C Lo ldquoSpatial focalization of zen-meditationbrain based on EEGrdquo Journal of Biomedical EngineeringResearch vol 29 pp 17ndash24 2008
[38] H Adeli Z Zhou and N Dadmehr ldquoAnalysis of EEG recordsin an epileptic patient using wavelet transformrdquo Journal ofNeuroscience Methods vol 123 no 1 pp 69ndash87 2003
[39] F Takens ldquoDetecting strange attractors in turbulencerdquo inDynamical Systems and Turbulence D A Rand and L S YoungEds vol 898 of Lecture Notes in Mathematics pp 366ndash381Springer New York NY USA 1981
[40] P-C Lo and W-P Chung ldquoAn approach to quantifying themulti-channel EEG spatial-temporal featurerdquo Biometrical Jour-nal vol 42 no 7 pp 901ndash916 2000
[41] W S Pritchard and D W Duke ldquoDimensional analysis of no-task human EEG using the Grassberger-Procaccia methodrdquoPsychophysiology vol 29 no 2 pp 182ndash192 1992
[42] R Q Quiroga A Kraskov T Kreuz and P GrassbergerldquoPerformance of different synchronization measures in realdata a case study on electroencephalographic signalsrdquo PhysicalReview E vol 65 no 4 Article ID 041903 14 pages 2002
10 Evidence-Based Complementary and Alternative Medicine
Source070
065
060
055
050
F P C LT RT
Exp (R)Exp (M)
Exp (C)Control
(a)
Sink070
065
060
055
050
F P C LT RT
Exp (R)Exp (M)
Exp (C)Control
(b)
Figure 9 Comparison of average effectiveness of each region as a source (a) or a sink (b) between experimental and control groups
Chan Chakra
(a)
DU20
DU21DU22
Anteriorhairline
Posteriorhairline
(b)
Figure 10 (a) Location of the Chan Chakra (inside the third ventricle) (b) Illustration of acupoints DU20 (Baihui) DU21 (Qianding) andDU22 (Xinhui) on DU meridian
and the natural powers of the universe in Chan meditationunder a linden tree The orthodox Chan Buddhism wasoriginated by such an exceptional affair that Buddha Shakya-muni transmitted this light of supreme wisdom to the GreatKashiyapa The same path towards perfect enlightenment(Buddhahood) was promulgated in mainland China in 527
by Bodhidharma the 28th patriarch The current patriarchis Chan master Wu Jue Miao Tian the 85th patriarch of theorthodox Chan-Buddhism Sect since the Great KashiyapaIn orthodox Chan-Buddhist practice very few disciples wereable to catch the quintessence since it cannot be taught inany form of lectures Written material and spoken words
Evidence-Based Complementary and Alternative Medicine 11
cannot promulgate the true wisdom of Chan which can onlybe conveyed by the Buddhist Heart-seal Imprint from a truemaster
In Chan meditation practitioners aim to attain the trueself (Buddha nature) with eternal wisdom (Bodhi) throughbody-mind-soul purification Substantially speaking suchpurification procedure involves the journal of transcendingthe physiological state (five sensory organs) themental activ-ities and normal consciousness the subliminal (the manas)consciousness and the Alaya state at which practitioners areable to perceive the sacred light emitted from Buddha natureBuddhist Heart-seal Imprint from the Chan Patriarch is amust to assist in the purification and accomplishment Toprepare for attaining such realm practitioners meditate withfull-lotus half-lotus or leg-crossing posture and sit still tocultivate spiritual Reiki for penetrating into the ten importantChakras In the course of Chan meditation practitionersmust switch their normal chest breathing to the Navel-Chakra breathing (also called ldquofetal breathingrdquo) that is thebreathing scheme for entering into deep meditation Amongthe ten Chakras Chan Chakra locating inside the thirdventricle is the Buddhist paradise implemented in our bodyFigure 10(a) illustrates the location of Chan Chakra
The cun-measurand system is normally used to measureand locate the acupoints To determine the locations ofacupoints DU20 DU21 and DU22 on Governor Vesselmeridian (DU meridian) we first measure the scalp-midlinelength between anterior hairline and posterior hairline thatis divided into 12 cuns The locations are defined as follows
DU20 7 cuns above the posterior hairline and 5 cunsabove the anterior hairlineDU21 35 cuns directly above the anterior hairline or15 cuns anterior to DU20DU22 2 cuns posterior to the anterior hairline or3 cuns anterior to DU20
Acknowledgments
The authors would like to thank Shung-Yu Yo for his assis-tance in data analysis Chan-meditation practitioners of theShakyamuni Buddhist Foundation are gratefully acknowl-edged for their enthusiastic participation in this research asvolunteers This research was supported by the grants fromthe National Science Council of Taiwan (Grant no NSC 100-2221-E-009-006-MY2)
References
[1] T YuH L Tsai andM LHwang ldquoSuppressing tumor progres-sion of in vitro prostate cancer cells by emitted psychosomaticpower through Zen meditationrdquo American Journal of ChineseMedicine vol 31 no 3 pp 499ndash507 2003
[2] K H Coker ldquoMeditation and prostate cancer integrating amindbody interventionwith traditional therapiesrdquo Seminars inUrologic Oncology vol 17 no 2 pp 111ndash118 1999
[3] D Lester ldquoZen and happinessrdquo Psychological Reports vol 84no 2 pp 650ndash651 1999
[4] C R K MacLean K G Walton S R Wenneberg et alldquoEffects of the transcendental meditation program on adaptivemechanisms changes in hormone levels and responses to stressafter 4 months of practicerdquo Psychoneuroendocrinology vol 22no 4 pp 277ndash295 1997
[5] GA Tooley SMArmstrong T RNorman andA Sali ldquoAcuteincreases in night-time plasma melatonin levels following aperiod of meditationrdquo Biological Psychology vol 53 no 1 pp69ndash78 2000
[6] Y-Y Tang Y Ma Y Fan et al ldquoCentral and autonomicnervous system interaction is altered by short-termmeditationrdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 106 no 22 pp 8865ndash8870 2009
[7] A Lutz H A Slagter N B Rawlings A D Francis LL Greischar and R J Davidson ldquoMental training enhancesattentional stability neural and behavioral evidencerdquo Journal ofNeuroscience vol 29 no 42 pp 13418ndash13427 2009
[8] S M Bertisch C C Wee R S Phillips and E P McCarthyldquoAlternative mind-body therapies used by adults with medicalconditionsrdquo Journal of Psychosomatic Research vol 66 no 6 pp511ndash519 2009
[9] W R Marchand ldquoMindfulness-based stress reductionmindfulness-based cognitive therapy and zen meditation fordepression anxiety pain and psychological distressrdquo Journalof Psychiatric Practice vol 18 no 4 pp 233ndash2252 2012
[10] B R Cahn and J Polich ldquoMeditation states and traits EEG ERPand neuroimaging studiesrdquoPsychological Bulletin vol 132 no 2pp 180ndash211 2006
[11] F Travis and J Shear ldquoFocused attention open monitoring andautomatic self-transcending categories to organize meditationsfrom Vedic Buddhist and Chinese traditionsrdquo Consciousnessand Cognition vol 19 no 4 pp 1110ndash1118 2010
[12] P-C Lo M-L Huang and K-M Chang ldquoEEG alpha blockingcorrelated with perception of inner light during Zen medita-tionrdquo American Journal of Chinese Medicine vol 31 no 4 pp629ndash642 2003
[13] H C Liao and P C Lo ldquoInvestigation on spatiotemporalcharacteristics of zen-meditation EEG rhythmsrdquo Journal ofInternational Society of Life Information Science vol 25 no 1pp 63ndash71 2007
[14] H-Y Huang and P-C Lo ldquoEEG dynamics of experienced zenmeditation practitioners probed by complexity index and spec-tral measurerdquo Journal of Medical Engineering and Technologyvol 33 no 4 pp 314ndash321 2009
[15] E K St Louis and E P Lansky ldquoMeditation and epilepsy a stillhung juryrdquoMedical Hypotheses vol 67 no 2 pp 247ndash250 2006
[16] L I Aftanas and S A Golocheikine ldquoHuman anterior andfrontal midline theta and lower alpha reflect emotionallypositive state and internalized attention high-resolution EEGinvestigation of meditationrdquo Neuroscience Letters vol 310 no1 pp 57ndash60 2001
[17] K Ansari-Asl J-J Bellanger F Bartolomei F Wendung andL Senhadji ldquoTime-frequency characterization of interdepen-dencies in nonstationary signals application to epileptic EEGrdquoIEEE Transactions on Biomedical Engineering vol 52 no 7 pp1218ndash1226 2005
[18] F Gans A Y Schumann J W Kantelhardt T Penzel and IFietze ldquoCross-modulated amplitudes and frequencies charac-terize interacting components in complex systemsrdquo PhysicalReview Letters vol 102 no 9 Article ID 098701 2009
12 Evidence-Based Complementary and Alternative Medicine
[19] J Bhattacharya H Petsche and E Pereda ldquoInterdependenciesin the spontaneous EEG while listening to musicrdquo InternationalJournal of Psychophysiology vol 42 no 3 pp 287ndash301 2001
[20] C J Stam ldquoNonlinear dynamical analysis of EEG and MEGreview of an emerging fieldrdquo Clinical Neurophysiology vol 116no 10 pp 2266ndash2301 2005
[21] W Singer ldquoConsciousness and the binding problemrdquo Annals ofthe New York Academy of Sciences vol 929 pp 123ndash146 2001
[22] D Calitoiu B J Oommen and D Nussbaum ldquoLarge-scaleneuro-modeling for understanding and explaining some brain-related chaotic behaviorrdquo Simulation-Transactions of the Societyfor Modeling and Simulation International vol 88 no 11 pp1316ndash1337 2012
[23] F Wendling K Ansari-Asl F Bartolomei and L SenhadjildquoFrom EEG signals to brain connectivity a model-based eval-uation of interdependence measuresrdquo Journal of NeuroscienceMethods vol 183 no 1 pp 9ndash18 2009
[24] H Y Huang and P C Lo ldquoEEG nonlinear interdependencemeasure of brain interactions under zen meditationrdquo Journalof Biomedical Engineering Research vol 29 no 4 pp 286ndash2942008
[25] M Breakspear and J R Terry ldquoDetection and description ofnon-linear interdependence in normal multichannel humanEEG datardquo Clinical Neurophysiology vol 113 no 5 pp 735ndash7532002
[26] M Breakspear and J R Terry ldquoTopographic organizationof nonlinear interdependence in multichannel human EEGrdquoNeuroImage vol 16 no 3 pp 822ndash835 2002
[27] C J Stam M Breakspear A-M van Cappellen van Walsumand B W van Dijk ldquoNonlinear synchronization in EEG andwhole-headMEG recordings of healthy subjectsrdquoHuman BrainMapping vol 19 no 2 pp 63ndash78 2003
[28] U Feldmann and J Bhattacharya ldquoPredictability improvementas an asymmetrical measure of interdependence in bivariatetime seriesrdquo International Journal of Bifurcation and Chaos vol14 no 2 pp 505ndash514 2004
[29] M Rubinov S A Knock C J Stam et al ldquoSmall-worldproperties of nonlinear brain activity in schizophreniardquoHumanBrain Mapping vol 30 no 2 pp 403ndash416 2009
[30] P Mirowski D Madhavan Y LeCun and R KuznieckyldquoClassification of patterns of EEG synchronization for seizurepredictionrdquo Clinical Neurophysiology vol 120 no 11 pp 1927ndash1940 2009
[31] S I Dimitriadis N A Laskaris Y del Rio-Portilla and G CKoudounis ldquoCharacterizing dynamic functional connectivityacross sleep stages from EEGrdquo Brain Topography vol 22 no 2pp 119ndash133 2009
[32] K Sibsambhu and R Aurobinda ldquoEffect of sleep deprivation onfunctional connectivity of EEG channelsrdquo IEEE Transcations onSystems Man and Cybernetics vol 43 no 3 pp 666ndash672 2013
[33] C M W J M Tian Chan Master Miao Tianrsquos Book of Wisdomand the Guide to Heart Chan Meditation Lulu 2010
[34] X-S Zhang R J Roy and E W Jensen ldquoEEG complexity as ameasure of depth of anesthesia for patientsrdquo IEEE Transactionson Biomedical Engineering vol 48 no 12 pp 1424ndash1433 2001
[35] I Daubechies Ten Lectures on Wavelets Society for Industrialand Applied Mathematics Philadelphia Pa USA 1992
[36] C Heil D F Walnut and I Daubechies Fundamental Papersin Wavelet Theory Princeton University Press Princeton NJUSA 2006
[37] C Y Liu and P C Lo ldquoSpatial focalization of zen-meditationbrain based on EEGrdquo Journal of Biomedical EngineeringResearch vol 29 pp 17ndash24 2008
[38] H Adeli Z Zhou and N Dadmehr ldquoAnalysis of EEG recordsin an epileptic patient using wavelet transformrdquo Journal ofNeuroscience Methods vol 123 no 1 pp 69ndash87 2003
[39] F Takens ldquoDetecting strange attractors in turbulencerdquo inDynamical Systems and Turbulence D A Rand and L S YoungEds vol 898 of Lecture Notes in Mathematics pp 366ndash381Springer New York NY USA 1981
[40] P-C Lo and W-P Chung ldquoAn approach to quantifying themulti-channel EEG spatial-temporal featurerdquo Biometrical Jour-nal vol 42 no 7 pp 901ndash916 2000
[41] W S Pritchard and D W Duke ldquoDimensional analysis of no-task human EEG using the Grassberger-Procaccia methodrdquoPsychophysiology vol 29 no 2 pp 182ndash192 1992
[42] R Q Quiroga A Kraskov T Kreuz and P GrassbergerldquoPerformance of different synchronization measures in realdata a case study on electroencephalographic signalsrdquo PhysicalReview E vol 65 no 4 Article ID 041903 14 pages 2002
Evidence-Based Complementary and Alternative Medicine 11
cannot promulgate the true wisdom of Chan which can onlybe conveyed by the Buddhist Heart-seal Imprint from a truemaster
In Chan meditation practitioners aim to attain the trueself (Buddha nature) with eternal wisdom (Bodhi) throughbody-mind-soul purification Substantially speaking suchpurification procedure involves the journal of transcendingthe physiological state (five sensory organs) themental activ-ities and normal consciousness the subliminal (the manas)consciousness and the Alaya state at which practitioners areable to perceive the sacred light emitted from Buddha natureBuddhist Heart-seal Imprint from the Chan Patriarch is amust to assist in the purification and accomplishment Toprepare for attaining such realm practitioners meditate withfull-lotus half-lotus or leg-crossing posture and sit still tocultivate spiritual Reiki for penetrating into the ten importantChakras In the course of Chan meditation practitionersmust switch their normal chest breathing to the Navel-Chakra breathing (also called ldquofetal breathingrdquo) that is thebreathing scheme for entering into deep meditation Amongthe ten Chakras Chan Chakra locating inside the thirdventricle is the Buddhist paradise implemented in our bodyFigure 10(a) illustrates the location of Chan Chakra
The cun-measurand system is normally used to measureand locate the acupoints To determine the locations ofacupoints DU20 DU21 and DU22 on Governor Vesselmeridian (DU meridian) we first measure the scalp-midlinelength between anterior hairline and posterior hairline thatis divided into 12 cuns The locations are defined as follows
DU20 7 cuns above the posterior hairline and 5 cunsabove the anterior hairlineDU21 35 cuns directly above the anterior hairline or15 cuns anterior to DU20DU22 2 cuns posterior to the anterior hairline or3 cuns anterior to DU20
Acknowledgments
The authors would like to thank Shung-Yu Yo for his assis-tance in data analysis Chan-meditation practitioners of theShakyamuni Buddhist Foundation are gratefully acknowl-edged for their enthusiastic participation in this research asvolunteers This research was supported by the grants fromthe National Science Council of Taiwan (Grant no NSC 100-2221-E-009-006-MY2)
References
[1] T YuH L Tsai andM LHwang ldquoSuppressing tumor progres-sion of in vitro prostate cancer cells by emitted psychosomaticpower through Zen meditationrdquo American Journal of ChineseMedicine vol 31 no 3 pp 499ndash507 2003
[2] K H Coker ldquoMeditation and prostate cancer integrating amindbody interventionwith traditional therapiesrdquo Seminars inUrologic Oncology vol 17 no 2 pp 111ndash118 1999
[3] D Lester ldquoZen and happinessrdquo Psychological Reports vol 84no 2 pp 650ndash651 1999
[4] C R K MacLean K G Walton S R Wenneberg et alldquoEffects of the transcendental meditation program on adaptivemechanisms changes in hormone levels and responses to stressafter 4 months of practicerdquo Psychoneuroendocrinology vol 22no 4 pp 277ndash295 1997
[5] GA Tooley SMArmstrong T RNorman andA Sali ldquoAcuteincreases in night-time plasma melatonin levels following aperiod of meditationrdquo Biological Psychology vol 53 no 1 pp69ndash78 2000
[6] Y-Y Tang Y Ma Y Fan et al ldquoCentral and autonomicnervous system interaction is altered by short-termmeditationrdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 106 no 22 pp 8865ndash8870 2009
[7] A Lutz H A Slagter N B Rawlings A D Francis LL Greischar and R J Davidson ldquoMental training enhancesattentional stability neural and behavioral evidencerdquo Journal ofNeuroscience vol 29 no 42 pp 13418ndash13427 2009
[8] S M Bertisch C C Wee R S Phillips and E P McCarthyldquoAlternative mind-body therapies used by adults with medicalconditionsrdquo Journal of Psychosomatic Research vol 66 no 6 pp511ndash519 2009
[9] W R Marchand ldquoMindfulness-based stress reductionmindfulness-based cognitive therapy and zen meditation fordepression anxiety pain and psychological distressrdquo Journalof Psychiatric Practice vol 18 no 4 pp 233ndash2252 2012
[10] B R Cahn and J Polich ldquoMeditation states and traits EEG ERPand neuroimaging studiesrdquoPsychological Bulletin vol 132 no 2pp 180ndash211 2006
[11] F Travis and J Shear ldquoFocused attention open monitoring andautomatic self-transcending categories to organize meditationsfrom Vedic Buddhist and Chinese traditionsrdquo Consciousnessand Cognition vol 19 no 4 pp 1110ndash1118 2010
[12] P-C Lo M-L Huang and K-M Chang ldquoEEG alpha blockingcorrelated with perception of inner light during Zen medita-tionrdquo American Journal of Chinese Medicine vol 31 no 4 pp629ndash642 2003
[13] H C Liao and P C Lo ldquoInvestigation on spatiotemporalcharacteristics of zen-meditation EEG rhythmsrdquo Journal ofInternational Society of Life Information Science vol 25 no 1pp 63ndash71 2007
[14] H-Y Huang and P-C Lo ldquoEEG dynamics of experienced zenmeditation practitioners probed by complexity index and spec-tral measurerdquo Journal of Medical Engineering and Technologyvol 33 no 4 pp 314ndash321 2009
[15] E K St Louis and E P Lansky ldquoMeditation and epilepsy a stillhung juryrdquoMedical Hypotheses vol 67 no 2 pp 247ndash250 2006
[16] L I Aftanas and S A Golocheikine ldquoHuman anterior andfrontal midline theta and lower alpha reflect emotionallypositive state and internalized attention high-resolution EEGinvestigation of meditationrdquo Neuroscience Letters vol 310 no1 pp 57ndash60 2001
[17] K Ansari-Asl J-J Bellanger F Bartolomei F Wendung andL Senhadji ldquoTime-frequency characterization of interdepen-dencies in nonstationary signals application to epileptic EEGrdquoIEEE Transactions on Biomedical Engineering vol 52 no 7 pp1218ndash1226 2005
[18] F Gans A Y Schumann J W Kantelhardt T Penzel and IFietze ldquoCross-modulated amplitudes and frequencies charac-terize interacting components in complex systemsrdquo PhysicalReview Letters vol 102 no 9 Article ID 098701 2009
12 Evidence-Based Complementary and Alternative Medicine
[19] J Bhattacharya H Petsche and E Pereda ldquoInterdependenciesin the spontaneous EEG while listening to musicrdquo InternationalJournal of Psychophysiology vol 42 no 3 pp 287ndash301 2001
[20] C J Stam ldquoNonlinear dynamical analysis of EEG and MEGreview of an emerging fieldrdquo Clinical Neurophysiology vol 116no 10 pp 2266ndash2301 2005
[21] W Singer ldquoConsciousness and the binding problemrdquo Annals ofthe New York Academy of Sciences vol 929 pp 123ndash146 2001
[22] D Calitoiu B J Oommen and D Nussbaum ldquoLarge-scaleneuro-modeling for understanding and explaining some brain-related chaotic behaviorrdquo Simulation-Transactions of the Societyfor Modeling and Simulation International vol 88 no 11 pp1316ndash1337 2012
[23] F Wendling K Ansari-Asl F Bartolomei and L SenhadjildquoFrom EEG signals to brain connectivity a model-based eval-uation of interdependence measuresrdquo Journal of NeuroscienceMethods vol 183 no 1 pp 9ndash18 2009
[24] H Y Huang and P C Lo ldquoEEG nonlinear interdependencemeasure of brain interactions under zen meditationrdquo Journalof Biomedical Engineering Research vol 29 no 4 pp 286ndash2942008
[25] M Breakspear and J R Terry ldquoDetection and description ofnon-linear interdependence in normal multichannel humanEEG datardquo Clinical Neurophysiology vol 113 no 5 pp 735ndash7532002
[26] M Breakspear and J R Terry ldquoTopographic organizationof nonlinear interdependence in multichannel human EEGrdquoNeuroImage vol 16 no 3 pp 822ndash835 2002
[27] C J Stam M Breakspear A-M van Cappellen van Walsumand B W van Dijk ldquoNonlinear synchronization in EEG andwhole-headMEG recordings of healthy subjectsrdquoHuman BrainMapping vol 19 no 2 pp 63ndash78 2003
[28] U Feldmann and J Bhattacharya ldquoPredictability improvementas an asymmetrical measure of interdependence in bivariatetime seriesrdquo International Journal of Bifurcation and Chaos vol14 no 2 pp 505ndash514 2004
[29] M Rubinov S A Knock C J Stam et al ldquoSmall-worldproperties of nonlinear brain activity in schizophreniardquoHumanBrain Mapping vol 30 no 2 pp 403ndash416 2009
[30] P Mirowski D Madhavan Y LeCun and R KuznieckyldquoClassification of patterns of EEG synchronization for seizurepredictionrdquo Clinical Neurophysiology vol 120 no 11 pp 1927ndash1940 2009
[31] S I Dimitriadis N A Laskaris Y del Rio-Portilla and G CKoudounis ldquoCharacterizing dynamic functional connectivityacross sleep stages from EEGrdquo Brain Topography vol 22 no 2pp 119ndash133 2009
[32] K Sibsambhu and R Aurobinda ldquoEffect of sleep deprivation onfunctional connectivity of EEG channelsrdquo IEEE Transcations onSystems Man and Cybernetics vol 43 no 3 pp 666ndash672 2013
[33] C M W J M Tian Chan Master Miao Tianrsquos Book of Wisdomand the Guide to Heart Chan Meditation Lulu 2010
[34] X-S Zhang R J Roy and E W Jensen ldquoEEG complexity as ameasure of depth of anesthesia for patientsrdquo IEEE Transactionson Biomedical Engineering vol 48 no 12 pp 1424ndash1433 2001
[35] I Daubechies Ten Lectures on Wavelets Society for Industrialand Applied Mathematics Philadelphia Pa USA 1992
[36] C Heil D F Walnut and I Daubechies Fundamental Papersin Wavelet Theory Princeton University Press Princeton NJUSA 2006
[37] C Y Liu and P C Lo ldquoSpatial focalization of zen-meditationbrain based on EEGrdquo Journal of Biomedical EngineeringResearch vol 29 pp 17ndash24 2008
[38] H Adeli Z Zhou and N Dadmehr ldquoAnalysis of EEG recordsin an epileptic patient using wavelet transformrdquo Journal ofNeuroscience Methods vol 123 no 1 pp 69ndash87 2003
[39] F Takens ldquoDetecting strange attractors in turbulencerdquo inDynamical Systems and Turbulence D A Rand and L S YoungEds vol 898 of Lecture Notes in Mathematics pp 366ndash381Springer New York NY USA 1981
[40] P-C Lo and W-P Chung ldquoAn approach to quantifying themulti-channel EEG spatial-temporal featurerdquo Biometrical Jour-nal vol 42 no 7 pp 901ndash916 2000
[41] W S Pritchard and D W Duke ldquoDimensional analysis of no-task human EEG using the Grassberger-Procaccia methodrdquoPsychophysiology vol 29 no 2 pp 182ndash192 1992
[42] R Q Quiroga A Kraskov T Kreuz and P GrassbergerldquoPerformance of different synchronization measures in realdata a case study on electroencephalographic signalsrdquo PhysicalReview E vol 65 no 4 Article ID 041903 14 pages 2002
12 Evidence-Based Complementary and Alternative Medicine
[19] J Bhattacharya H Petsche and E Pereda ldquoInterdependenciesin the spontaneous EEG while listening to musicrdquo InternationalJournal of Psychophysiology vol 42 no 3 pp 287ndash301 2001
[20] C J Stam ldquoNonlinear dynamical analysis of EEG and MEGreview of an emerging fieldrdquo Clinical Neurophysiology vol 116no 10 pp 2266ndash2301 2005
[21] W Singer ldquoConsciousness and the binding problemrdquo Annals ofthe New York Academy of Sciences vol 929 pp 123ndash146 2001
[22] D Calitoiu B J Oommen and D Nussbaum ldquoLarge-scaleneuro-modeling for understanding and explaining some brain-related chaotic behaviorrdquo Simulation-Transactions of the Societyfor Modeling and Simulation International vol 88 no 11 pp1316ndash1337 2012
[23] F Wendling K Ansari-Asl F Bartolomei and L SenhadjildquoFrom EEG signals to brain connectivity a model-based eval-uation of interdependence measuresrdquo Journal of NeuroscienceMethods vol 183 no 1 pp 9ndash18 2009
[24] H Y Huang and P C Lo ldquoEEG nonlinear interdependencemeasure of brain interactions under zen meditationrdquo Journalof Biomedical Engineering Research vol 29 no 4 pp 286ndash2942008
[25] M Breakspear and J R Terry ldquoDetection and description ofnon-linear interdependence in normal multichannel humanEEG datardquo Clinical Neurophysiology vol 113 no 5 pp 735ndash7532002
[26] M Breakspear and J R Terry ldquoTopographic organizationof nonlinear interdependence in multichannel human EEGrdquoNeuroImage vol 16 no 3 pp 822ndash835 2002
[27] C J Stam M Breakspear A-M van Cappellen van Walsumand B W van Dijk ldquoNonlinear synchronization in EEG andwhole-headMEG recordings of healthy subjectsrdquoHuman BrainMapping vol 19 no 2 pp 63ndash78 2003
[28] U Feldmann and J Bhattacharya ldquoPredictability improvementas an asymmetrical measure of interdependence in bivariatetime seriesrdquo International Journal of Bifurcation and Chaos vol14 no 2 pp 505ndash514 2004
[29] M Rubinov S A Knock C J Stam et al ldquoSmall-worldproperties of nonlinear brain activity in schizophreniardquoHumanBrain Mapping vol 30 no 2 pp 403ndash416 2009
[30] P Mirowski D Madhavan Y LeCun and R KuznieckyldquoClassification of patterns of EEG synchronization for seizurepredictionrdquo Clinical Neurophysiology vol 120 no 11 pp 1927ndash1940 2009
[31] S I Dimitriadis N A Laskaris Y del Rio-Portilla and G CKoudounis ldquoCharacterizing dynamic functional connectivityacross sleep stages from EEGrdquo Brain Topography vol 22 no 2pp 119ndash133 2009
[32] K Sibsambhu and R Aurobinda ldquoEffect of sleep deprivation onfunctional connectivity of EEG channelsrdquo IEEE Transcations onSystems Man and Cybernetics vol 43 no 3 pp 666ndash672 2013
[33] C M W J M Tian Chan Master Miao Tianrsquos Book of Wisdomand the Guide to Heart Chan Meditation Lulu 2010
[34] X-S Zhang R J Roy and E W Jensen ldquoEEG complexity as ameasure of depth of anesthesia for patientsrdquo IEEE Transactionson Biomedical Engineering vol 48 no 12 pp 1424ndash1433 2001
[35] I Daubechies Ten Lectures on Wavelets Society for Industrialand Applied Mathematics Philadelphia Pa USA 1992
[36] C Heil D F Walnut and I Daubechies Fundamental Papersin Wavelet Theory Princeton University Press Princeton NJUSA 2006
[37] C Y Liu and P C Lo ldquoSpatial focalization of zen-meditationbrain based on EEGrdquo Journal of Biomedical EngineeringResearch vol 29 pp 17ndash24 2008
[38] H Adeli Z Zhou and N Dadmehr ldquoAnalysis of EEG recordsin an epileptic patient using wavelet transformrdquo Journal ofNeuroscience Methods vol 123 no 1 pp 69ndash87 2003
[39] F Takens ldquoDetecting strange attractors in turbulencerdquo inDynamical Systems and Turbulence D A Rand and L S YoungEds vol 898 of Lecture Notes in Mathematics pp 366ndash381Springer New York NY USA 1981
[40] P-C Lo and W-P Chung ldquoAn approach to quantifying themulti-channel EEG spatial-temporal featurerdquo Biometrical Jour-nal vol 42 no 7 pp 901ndash916 2000
[41] W S Pritchard and D W Duke ldquoDimensional analysis of no-task human EEG using the Grassberger-Procaccia methodrdquoPsychophysiology vol 29 no 2 pp 182ndash192 1992
[42] R Q Quiroga A Kraskov T Kreuz and P GrassbergerldquoPerformance of different synchronization measures in realdata a case study on electroencephalographic signalsrdquo PhysicalReview E vol 65 no 4 Article ID 041903 14 pages 2002
