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Week 1. Basics of multimodal imaging and image processing. Functional magnetic resonance imaging.

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2012.10.30. 1 Multimodal Imaging in Neurosciences Course Introduction to Multi-modal neuroimaging Dr. Ervin Berenyi, MD, PhD Dr. András Jakab, MD, PhD Dr. Peter Katona, MD Diagnostic neuroimaging modalities CT – Computed Tomography Brain anatomy Stereotactic reference frame Structural MRI Fine brain anatomy Vascular structure Diffusion, perfusion MRI Fine pathological information Intra-operative imaging modalities, open MRI, low- field Multi-modal imaging spectrum for MR Spectroscopy Brain metabolism Biochemical mapping Positron Emission Tomography PET Brain metabolism Brain function Functional MR imaging fMRI Brain function Electro encephalography, LORETTA, Magnetoencephalography 1.Diagnostic imaging 2.Research 3.Neurosurgery What is multimodality? | Combining images and information from multiple imaging tools, devices | Anatomical alignment of images | Fusion display, co-analysis of multiple information sources What is needed for multimodality? What is needed for multimodality? | CT, PET, MRI, SPECT, EEG, … | Hybrid devices – PET-CT, PET-MRI | Image processing skills to create image fusions, etc. PET-CT HYBRID CT: anatomy + attenuation correction PET: metabolism, function PET-MRI HYBRID SCANNER Acquire PET and MRI together Great technological challenge $$$ Measuring Measuring tissue tissue properties properties with with MRI MRI T1 relaxation T2 relaxation Proton density Ti diff i Structural MRI Diffusion- weighted Tissue diffusion Diffusion direction Diffusion anisotropy Diffusion maps Metabolites weighted imaging Diffusion tensor imaging Diffusion spectral imaging, HARDI MR spectroscopy
Transcript
Page 1: Week 1. Basics of multimodal imaging and image processing. Functional magnetic resonance imaging.

2012.10.30.

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Multimodal Imaging in Neurosciences Course

Introduction to Multi-modalneuroimagingDr. Ervin Berenyi, MD, PhDDr. András Jakab, MD, PhDDr. Peter Katona, MD

Diagnostic neuroimaging modalities

CT – Computed TomographyBrain anatomyStereotactic reference frame

Structural MRIFine brain anatomyVascular structure

Diffusion, perfusion MRIFine pathologicalinformation

Intra-operative imagingmodalities, open MRI, low-field

Multi-modal imagingspectrum for

MR SpectroscopyBrain metabolismBiochemical mapping

Positron EmissionTomography PETBrain metabolismBrain function

Functional MR imaging fMRIBrain function

Electro encephalography, LORETTA, Magnetoencephalography

1.Diagnostic imaging2.Research

3.Neurosurgery

What is multimodality?Combining images and information from multipleimaging tools, devicesAnatomical alignment of imagesFusion display, co-analysis of multipleinformation sources

What is needed for multimodality?What is needed for multimodality?CT, PET, MRI, SPECT, EEG, …Hybrid devices – PET-CT, PET-MRIImage processing skills to create image fusions, etc.

PET-CT HYBRID

CT: anatomy + attenuationcorrectionPET: metabolism, function

PET-MRI HYBRID SCANNER

Acquire PET and MRI togetherGreat technological challenge$$$

MeasuringMeasuring tissuetissue propertiesproperties withwith MRIMRI

T1 relaxation

T2 relaxation

Proton density

Ti diff i

Structural MRI

Diffusion-weightedTissue diffusion

Diffusion direction

Diffusion anisotropy

Diffusion maps

Metabolites

weightedimaging

Diffusion tensorimaging

Diffusion spectralimaging, HARDI

MR spectroscopy

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VISUALIZATION OF STRUCTURE

Recidive tumor, 2 foci, purple and magenta

Markers on the skin

removed temporal lobe parts

VISUALIZATION OF FIBERS

OPTIC RADIATION

CORTICOSPINAL TRACT

Functional MR ImagingDr. Ervin Berenyi, MD, PhDDr. András Jakab, MD, PhDDr. Peter Katona, MD

Multimodal Imaging in Neurosciences Course

Part I.Basics of fMRI and functionalmappingpp g

Brain functions – how to interpret

The synchronous activity of neuronal groupsCerebral cortexExamples of brain functions

Visual processingAuditory processingMemory functions, recallWernicke areaWernicke areaBroca areaMovement of limbsEmotional response: e.g. human face

„not processing anything” -default mode networks andresting state networks

COGNITIVE PROCESSING IN THE BRAIN

Primary sensory areas (somato-, auditory, etc.)Secondary, tertiary, etc. sensory areas (i.e. visual: 5-9

levels)Association areas„Association areas for higher cognitive functions”Motor response behavior

+ Parallel processing (notpurely hierarchical!)

Motor response, behavior

Somatosensory cortex (SI)

Somatosensory cortex (SII)

Parietal association area

„DLPFC – higher cognitive processing”

Drive, behavioral processing etc.

Speech motor center

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The brain never rests!Default network

Default mode networkDefault state networkTask-negative network

„Wandering and Wondering”Posterior cingulate cortexPrecuneusPrefrontal cortex

DaydreamingSynchronised areasAge dependencyDiseases affecting itNot dreaming!

Fair DA, Cohen AL, Power JD et al. (2009). "Functional brain networks develop from a 'local to distributed' organization". PLoS Comput Biol 5 (5): e1000381

Mapping neuronal function

Electric activity of neuronsAction potential, propagation of signalElectric current – magnetic field variations

Metabolic activity of neurons

Electro encephalography EEGMagnetoencephalography MEG

Positron emission tomographyGlucose metabolism

Blood supply of neuronsVasodilatation, perfusion change

Rapid changes of cell compartmentsCell swelling?

(18F-FDG) PET

fMRI

fDTI

History“[In Mosso’s experiments] the subject to be observed lay on a delicately balanced table which could tip downward either at the head or at the foot if the weight of either end were increased. The moment emotional or intellectual activity began in the subject, down went the balance at the head-end, in consequence of the redistribution of blood in his system.”

-- William James, Principles of Psychology (1890)

Angelo Mosso(1846 1910)(1846-1910)

E = mc2

???Zago et al. (2009) The Mosso method for recording brain pulsation: The forerunner offunctional neuroimaging. Neuroimage

HistoryThe first evidence for the coupling between energymetabolism and brain blood perfusion (animals)The blood volumen elevated during brain activitySir C. S. Sherrington, 1890Seymour Kety & Carl Schmidt, 1948

Increased oxigen take-upDilatation of blood vessels

Near infrared spectroscopy

Sir Charles Scott Sherrington

(1857-1952)ea a e spec oscopyPETfMRI (90’s): Seji Ogawa, Ken Wong

(1857 1952)

Cerebral Cortex. 12:225-233; 2002.

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Activity Increases Flow

• sensory stimulation leads to increased blood flow

• sciatic nerve, electronic stimulation (0,2 V 5-10 Hz), rats, automated video dimension analyzer

Blood pressure

dimension analyzerArteriole diameter Blood velocity

Data Source: Ngai et al., 1988, Am J PhysiolFigure Source, Huettel, Song & McCarthy, Functional Magnetic Resonance I i

Summary of in vivo imaging methods

Structural imagingCTMRI

T1 – 3DT1 – „anatomical”T2FLAIR, DWI, etc.

Functional imagingPETfMRI

…..

fMRI

Structural MRI Functional MRI

Good spatial resolution = 0.6 – 1 mm

Short scan time (a few minutes)

One time point is imaged

Good tissue contrast

No image post-processing is required

The result is robust

Bad spatial resolution = 2 – 4 mm

Long scan time (10-30 minutes)

Multiple time points, multiple scans

Bad tissue contrast

Post-processing is required

The result depends on the patient, theprotocol and paradigm

OK. Now show me the trick.

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25

-Four globin chains-Each chain contains a haem molecule

-Each haem has an iron atom in the center(Fe)

-Each haem can absorb one oxygen

The hemoglobine

Source: http://wsrv.clas.virginia.edu/~rjh9u/hemoglob.html, Jorge Jovici& Huettel, Song, McCarthy, Functional Magnetic Resonance Imaging

molecule (O2)

-oxy-Hgb (four O2) has DIAMAGNETIC effect →it does not affect the magneticfield ΔB

-deoxy-Hgb is PARAMAGNETIC → if[deoxy-Hgb] ↓ → then local ΔB ↓

Diamagnetism and paramagnetism

Diamagnetism(oxy- & carbonmonoxyhemoglobine)No magnetic momentumHas paired electrons

Paramagnetism (deoxyhemoglobine)Magnetic momentum – atoms behave as small magnetsHas unpaired electrons

Measuring deoxy-hemoglobine• During fMRI acquisitions, we get information of the brain’s deoxy-

hemoglobine content

• The relative oxygenation changes with the deoxygenated hemoglobinecontent

Seiji Ogawa

How does this work? The BOLD effect!Blood Oxygen Level DependentThe funcitonal activity is coded in the BOLD effect.

OxyHb and DeoxyHb- their MR relaxation properties are different!

deoxyHb: paramagnetic!!!

M

Source:, Huettel, Song & McCarthy, 2004, Functional Magnetic Resonance Imaging

time

MxySignal

Mo sinθT2* task

T2* control

TEoptimum

Stask

ScontrolΔS

Source: Jorge Jovicich

HEMODYNAMIC RESPONSE

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End of Part I. – any questions?

Part II.How to perform an fMRI?p

The MRI recipe

Human, made of

1. Patient (water + fat = lot of spins)

2. Excite (Shout at the patient with a radiofrequency coil)

3. Wait until the excited spins „relax”

4. During relaxation, the spins (water + fat =patient) shout back at you, theysend an ECHO

5. You listen to the echo and record it(this is the k-space acquisition)

Repeat this! This is called SEQUENCE

6 D d th i l t i !,excitable spins (H

proton spins)ECHO

6. Decode the signal, get image!

MRI sequencesImage coded as waves, Fourier transformation is used to „decode” the rawsignal and get an image

You can „excite” the spin system in numerous ways to have image signals, i.e. SPIN ECHO or GRADIENT ECHO sequences.

GRADIENT ECHO SEQUENCES ARE SENSITIVE FOR DEOXYHEMOGLOBINE CHANGES!

How does echo planar imaging works?Echo-planar imaging (SE-EPI, GRE-EPI)T2 contrastAfter one excitation, an entire slice is read out.It is a fast MR imaging sequenceHas many artifacts, i.e. susceptibility

IMAOIS – www.imaios.com

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How to perform an fMRI scan? Checklist!Can our MRI device perform fast EPI, what is thefield strength? 1.5T vs. 3T?What are we interested in?

fMRI experiments are task-specificIt is necessary to construct a PARADIGM which „observes” one specific brain function

D h i i kill ?Do we have image processing skills?$$$Patient cooperative?IQ, attention?Do we have enough time?Sedation, drugs, etc.

fMRI and all the tools

The first step: imaging the anatomyT1 weighted anatomical images as references

• High resolution images (1x1x2.5 mm)• 3D acquisition• pl. 64 anatomical images ~ 5 perc

Anatomical acquisition

Slice Thicknesse.g., 6 mm

SAGITTAL SLICE IN PLANE SLICE

VOXEL(Volumetric Pixel)

3 mm 6

mm

In-plane resolutione.g., 192 mm / 64= 3 mm

Number of Slicese.g., 10

IN-PLANE SLICE

Field of View (FOV)e.g., 19.2 cm

3 mm

Matrix Sizee.g., 64 x 64

Second step: the actual fMRI acquisitionT2*-weighted images

• Image contrast relates to neuronal activity• Low spatial resolution (3x3x5 mm)• One volume of the brain is acquired in 2 seconds!• We acquire many volumes in time (4D), ie. 150• Repeated scanning

first volume(2 sec to acquire)

Paradigm and block design

~2 sec

Functional images

Time

fMRIsignal(% change

ROI Time Course

Tasks

Statisticalactivation map on T1 image

Time

~ 5 minutesRegion of interest kijelölés (ROI)

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Interpreting fMRI results: LOCALIZATION

TALAIRACH ATLAS- 1988- 1 SZEMÉLY

Variability of sulci - problematic

Source: Szikla et al., 1977 in Tamraz & Comair, 2000

Fathers of Localization (brain atlases)

Jean Talairach(January 15, 1911, Perpignan

– March 15, 2007, Paris)

Gabor Szikla

Anatomical localization of activity: gyri and sulci

gray matter (dendrites & synapses)

white matter (axons)

ANK

FUNDUS

BA

FISSURE

Source: Ludwig & Klingler, 1956 in Tamraz & Comair, 2000

How to display fMRI results?

Creating 3D visualizations of the individual brain: Skull-stripping, inflating the cortex

Brain extraction Inflation

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Segmentation, filtering, masking

Fuzzy thresholding Anisotropic filtering Only brain

Standardization of fMRI images to brainatlases

Displaying fMRI fMRI display

End of Part II. – any questions?

Part III.Examples and research applicationsp pp

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What functions can we image usingfMRI?

Paradigm-dependent!Vision („vibrating checkboard”)Audition (variable frequency stimuli)Limb movement – activePassive limb movement - infantsMemory (hometown walking test)Speech… and many others (but not everything!)

The logic of a „simple” fMRI experimentRest = empty screen

Task1 Task 2Time

The subject views an object, i.e. apple „Scrambled” – image

Results: object recognition

Kalanit Grill-Spector et al.

First images of visual activityFlickering CheckerboardOFF (60 s) - ON (60 s) -OFF (60 s) - ON (60 s) - OFF (60 s)

Source: Kwong et al., 1992

CO-ACTIVATION OF V1 -> V2.. AFTERVISUAL STIMULUS

Motor paradigm of the left hand

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Finger tapping test of theright hand

Source: Katona P., DEOEC

Lesion in the left precentral gyrus (malformation) – REDHand movement activation: Yellow, CS tract: yellow

Jakab, Katona et al.

HOMUNCULUS Left hand

Source: Berenyi, Emri, Jakab et al

Left foot

Forrás: Berényi E, Emri M. DEOEC

Auditory activation

Task:

Listening

to

ordersorders

Forrás: Berényi E, Emri M. DEOEC

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FREQUENCY PROGRESSION OF HUMAN AUDITORY CORTEX

J Neurophysiol. 91:1282-1296, 2004.

Late speech development – pathologicallocalization of speech centers?

Radiology. 2003;229:651-658.

Speech paradigm: say a word beginningwith a,b,c, etc.

Jakab A, Katona P et al.

Localizing swallowing movement

AJNR. 20:1520-0526. 1999.

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Szentágothai TK Szentágothai TK --Semmelweis EgyetemSemmelweis EgyetemMR KutatóközpontMR Kutatóközpont

fMRI in afMRI in a Case of Childhood EpilepsyCase of Childhood Epilepsy

Lajos R KozakMR Research Center, Semmelweis University, Budapest, Hungary

Patient historyPatient historyA case of drug resistant epilepsy A case of drug resistant epilepsy

8 yrs old right handed boyBorn on term from uneventful pregnancy

First seizures at 3.5 yrsAbout the time of falling asleep starting with left hand twithcing then generalizingLater atypical absence seizures

EEG resultsEEG resultsNormal EEG on the onsetLater slow spike and wave activity developed with clinical abscenceFinally, electric status epilepticus during sleep (ESES), irregular high amplitude spike and wave activity, during the whole night

Physical examinationParesis on the left limbs

Patient historyPatient historyImaging

Smaller right hemisphere

On T1 weighted images (A-B) widespread irregularities of the cortical surface suggestive of multiple small folds with abnormally thick cortex, irregular appearance of the gray

tt hit tt j timatter-white matter junction

suggestive of polymicrogyria

On FLAIR images (C)numerous high intensity foci predominantly in the subcortical white matter

Question: is the malformed cortex functional?

Kozák et al., Clin Neurosci2009;62(3–4):130–135.

fMRI #fMRI #11no result

Imaging at 3T Philips Achieva scannerTR=3000ms, TE=30ms, FA=75°, 3x3x3mm2 voxels (80x80 matrix, 240x240 FOV), axial slices, no gap, SENSE factor of 2Block design paradigm, WHAT WAS THE WHAT WAS THE WHAT WAS THE WHAT WAS THE Block design paradigm, 24s movement, 24s rest

• flexion/extension of fingers ~0.5-1Hz

• left and right limb moved in separate blocks

PROBLEM WITH THE PROBLEM WITH THE fMRI?fMRI?

PROBLEM WITH THE PROBLEM WITH THE fMRI?fMRI?

movementrest

Bad acquisition ?Bad stimulation ?Overanesthetized ?

fMRI #1fMRI #1The reason for unsuccesful fMRI?

500-700μV

Electric status epilepticus during sleep (ESES) ?

Clonazepam was the solution

Kozák et al., Clin Neurosci2009;62(3–4):130–135.

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Preop.

fMRI #fMRI #22right hand movement pre- and postoperatively

Postop

Preop.

fMRI #fMRI #22left hand movement pre- and postoperatively

Postop

Functional reorganization to the healthy hemisphereFunctional reorganization to the healthy hemisphere

ConclusionsConclusions

Passive rangePassive range--ofof--movement paradigms are movement paradigms are considered useful considered useful for the mapping of sensory-motor cortex in pediatric epilepsy patientsin pediatric epilepsy patients.

If fMRI failsfMRI fails in this patient population we have toIf fMRI fails fMRI fails in this patient population we have to check if there is ongoing epileptic activity if there is ongoing epileptic activity during anesthesia

These paradigms are able to describe cortical able to describe cortical reorganizationreorganization, thus they have clear have clear prognostic value in a preprognostic value in a pre--operative settingoperative setting.

Research with fMRI

Summary of facts so far

fMRI is based on the BOLD = BloodOxygen Level Dependent contrastNeurovascular couplingA stringent paradigm is required( l)(protocol)Mapping brain activity can be achieved in living humansMany factors can influence theresultsfMRI = localization

"...the single most critical piece of equipment is still the researcher's own brain. All the equipment in the world will not help us if weequipment in the world will not help us if we do not know how to use it properly, which requires more than just knowing how to operate it. Aristotle would not necessarily have been more profound had he owned a laptop and known how to program. What is badly needed now, with all these scanners whirring away, is an understanding of exactly what we are observing, and seeing, and measuring, and wondering about."

-- Endel Tulving, interview in Cognitive Neuroscience (2002, Gazzaniga , Ivry & Mangun, Eds., NY: Norton, p. 323)

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A new localizationism?The accepted application

Surgical planningFor cognitive neuroscience, localizationitself has INFERIOR significancePopularity, factoid literature

Example for a BAD fMRI experiment

~2 sec

Time

Task 1: Subject observes a car on a screenTask 2: Subject observesnoise (control)Task 3: Subject observesCAR + Elmo Muppet

BAD INTERPRETATION OF FMRI RESULTS CANSTILL MAKE A JOURNAL PUBLICATION?

- =Elmo + CARCAR against noise

Visual areas for „carobservation”

Visual areas for „car + elmoobservation”

Elmo (negativeelmo)

Elmo Brain Area ???

The brain before the fMRI era

Polyak, in Savoy, 2001, Acta Psychologica

grasping

motion near head

motorcontrol

reaching and pointing

touch

retinotopic visual maps eyemovements

executive control

THE BRAIN AFTER FMRI (INCOMPLETE)

moving bodiessocial cognition

faces objectsstatic bodies

motion perception

orientation selectivitymemory

scenes

Basic types of fMRI researchTesting models, theoriesLocalize the activations after stimuliActivating networks after stimuliSpatial encoding of the brain:

Retinotopy, somatotopy, frequencyRetinotopy, somatotopy, frequencycoding

Behavior and cognitionDiseases, i.e. psychiatryInter-species comparisons

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The future of functional brain imaging

3T, 4T, 7T, … ?Ultra-low-field imagingArterial spin labelingFunctional diffusion tensorimaging (Le Bihan)

ULTRA-LOW-FIELD IMAGINGEarth magnetic fieldSQUID MAGNETOMETRY

Los Alamos, USA

The small electric currents of neuronal activity induce changesin the magnetic field, whichinterferes with the Earth’s and imaging can be performed

Arterial Spin Labeling - ASLinversionslab

i i

excitation

inversionxy

z (=B0)

bloodblood

99

• Perfusion: delivery of metabolites (via local blood flow) (BOLD - hemoglobin)

• Arterial Spin Labeling (ASL): invert of in-flowing blood

• IMAGEperfusion = IMAGEuninverted - IMAGEinverted

imagingplane

Arterial Spin Labeling - ASL

100

• Represents an interesting physiological parameter• Quantitative: fit kinetic curve for perfusion in

ml/100g/min• Lower SNR than BOLD• Limited coverage (~5 slices)

Arterial Spin Labeling - ASL

Magn Reson Med, 48:242-254 (2002)

Arterial Spin Labeling - ASL

Magn Reson Med, 48:242-254 (2002)

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Stroke. 2000;31:680-687.

End of Part III. – any questions?

Part IV.The functional brain connectome

Resting state fMRI

Don’t do anything.

Spontaneous synchronity in the brain = low frequency oscillations

<0.1 Hz neuronal activity is present during „rest”Background for continuous sensory processing?What regions are „synced” ?

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Correlated time courses = networks1. Regional slow neuronal activity

Hypothesis: if two neuronal time courses arecorrelated, the regions are interconnected.

2. Regional slow neuronal activity

3. Their correlation (temporal)

THE SHORT HISTORY OFCONNECTOMICS

Theodor MeynertJules DejerineTracing studies„In vivo methods”:Diffusion tensor imagingFunctional MR imagingFunctional Connectivity

This is called FUNCTIONAL CONNECTIVITY

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ModelingModeling thethe brain’sbrain’s connectionsconnections

Brain regions: network nodesStructural OR functional brain connection strength: network edges

Graph-theoretical analysis, a purely mathematical approach

Node (region)

How can information be exchanged among brain regions?

Short path-length, Low degree

Edge(connection)

ModelingModeling thethe brain’sbrain’s connectionsconnections

Brain regions: network nodesStructural OR functional brain connection strength: network edges

Graph-theoretical analysis, a purely mathematical approach

How can information be exchanged among brain regions?

Long path-length, Low degree

ModelingModeling thethe brain’sbrain’s connectionsconnections

Brain regions: network nodesStructural OR functional brain connection strength: network edges

Graph-theoretical analysis, a purely mathematical approach

How can information be exchanged among brain regions?

Short path-length, High degree(low efficiency)

ModelingModeling thethe brain’sbrain’s connectionsconnections

Brain regions: network nodesStructural OR functional brain connection strength: network edges

Graph-theoretical analysis, a purely mathematical approach

Hub

How can information be exchanged among brain regions?

Example of a highlyefficient network

Hub

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ModelingModeling thethe brain’sbrain’s connectionsconnections

Brain regions: network nodesStructural OR functional brain connection strength: network edges

Graph-theoretical analysis, a purely mathematical approach

How can information be exchanged among brain regions?

Example of an inefficientnetwork (almost random)

The internet

WhatWhat is is thethe corticocortico--corticalcortical brainbrain networknetwork likelike??CORTEX Facebook

Small World Networks

Source: Paul Weinstein’s blog

Modha & Singh. Network architecture of the long-distance pathways in the macaque brain. PNAS, 2010

Network Network propertiesproperties of of thethe brainbrain: : normalnormal developmentdevelopment

Network cost Network efficiency

Gong et al. Age- and Gender-Related Differences in the Cortical Anatomical Network. The Journal of Neuroscience 2009; 29: 15684-15693.

cost=sum(wij)

Network Network propertiesproperties of of thethe brainbrain: : normalnormal and and pathologicalpathological

Gong et al. Age- and Gender-Related Differences in the Cortical Anatomical Network. The Journal of Neuroscience 2009; 29: 15684-15693.

Network Network propertiesproperties of of thethe brainbrain: : gendergender differencesdifferences

Network cost Network efficiency

Gong et al. Age- and Gender-Related Differences in the Cortical Anatomical Network. The Journal of Neuroscience 2009; 29: 15684-15693.

cost=sum(wij)

Network Network propertiesproperties of of thethe brainbrain: : correlationcorrelation withwith intelligenceintelligence

Van Heuvel et al. Efficiency of Functional Brain Networks and Intellectual PerformanceThe Journal of Neuroscience, 2009, 29(23): 7619-7624.

Path length negatively correlateswith IQ, especially in the leftfrontal medial cortex

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DetectingDetecting areasareas withwith similarsimilar connectivityconnectivity profilesprofiles

+Exekutívskill

-Exekutívskill

Jakab A et al. Mapping changes of in vivo connectivity patterns in the human mediodorsal thalamus: correlations with higher cognitive and executive functions. Brain Imaging and Behavior 2012; DOI: 10.1007/s11682-012-9172-5

Network Network propertiesproperties of of thethe brainbrain: : schizophreniaschizophrenia

LOSS OF HIERARCHICAL ORGANIZATION IN FRONTAL

REGIONS

Bassett, D. S. et al. 2008

Van Heuvel. et al. 2010

n=9 (HLFA) vs. n=40 (controls)

Network Network propertiesproperties of of thethe brainbrain: : highhigh functioningfunctioning autisticautistic adultsadults

Jakab A, Spisak T, Szeman-Nagy A, Beres M, Molnar P, Emri M, Berenyi E. Pathological patterns of functional connectivity and white matter anisotropy in high functioning autistic adults. Under review @ PLoS One

Suggests the impairmentof long-rangeassociation fibers, especially in theleft fronto-temporo-ocipital connectivities

Thank you for your attention!

Presentation credits:

Dr. András Jakab, M.D. Ph.D.Dr. Ervin Berényi, M.D. Ph.D.Dr. Péter Katona, M.D.Dr. Miklós Emri, Ph.D.Tamás Spisák, M.sc.


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