Master Thesis Influence of stimulus frequency-amplitude relation of spinal cord stimulation on reflex responses in individuals with spinal cord injury. Carried out for the purpose of obtaining the degree of Master of Science, submitted at TU Wien, Faculty of Mechanical and Industrial Engineering, by Cemile Gül Polat Matr. Nr: 1429493 Under the supervision of Ao. Univ.-Prof. Dipl.-Ing. Dr. h.c. Dr. Winfried Mayr Institute of Mechanics and Mechatronics (E325), Vienna University of Technology Center for Medical Physics and Biomedical Engineering, Medical University of Vienna and Co.-Advisor: Dr. Jose Luis Vargas Luna Center for Medical Physics and Biomedical Engineering, Medical University of Vienna Vienna, November 2018
Transcript
Master Thesis
Influence of stimulus frequency-amplitude relation of spinal cord stimulation on reflex responses in
individuals with spinal cord injury.
Carried out for the purpose of obtaining the degree of Master of Science, submitted at TU Wien, Faculty of Mechanical and Industrial Engineering, by
Cemile Gül Polat Matr. Nr: 1429493
Under the supervision of
Ao. Univ.-Prof. Dipl.-Ing. Dr. h.c. Dr. Winfried Mayr
Institute of Mechanics and Mechatronics (E325), Vienna University of Technology Center for Medical Physics and Biomedical Engineering, Medical University of Vienna
and
Co.-Advisor: Dr. Jose Luis Vargas Luna
Center for Medical Physics and Biomedical Engineering, Medical University of Vienna
Vienna, November 2018
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Acknowledgements
First and foremost, I would like to thank Dr. Jose Luis Vargas Luna for helping me to answer all
my questions regarding the topic with great patience and supervising every step of this thesis. I
would like to thank Prof. Winfried Mayr for introducing me to this research field and giving me
the opportunity to write my master thesis.
Without my family’s help, I could not have the chance to come this far and I am thankful for their
continuous support during my long years of study. Finally, I would like to thank my friends for
backing me whenever I feel weak and powerless even if they are far away.
Above all, I would like to thank Florian Jesacher for being there for me with all his heart and soul
and helping me to overcome all the difficulties I faced with.
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Abstract
Spinal cord injury (SCI) is a damage to the spinal cord that disrupts the connectivity between brain
and the spinal neural networks caudal to the lesion and the peripheral nervous system, resulting in
loss of partial or complete motor control below the injury level. It is associated with spasticity,
chronic pain, among other problems. Spinal Cord Stimulation (SCS) has shown to be a promising
approach to improve the motor function and manage complications such as spasticity and pain.
Specifically, SCS has shown to be able to ameliorate the spasticity when high frequencies are
applied. It has been suggested that, by depolarizing the posterior roots, epidural (eSCS) and
transcutaneous (tSCS) are able to access the surviving neural centers below the SCI, a
neuromodulation process is conducted in synergy with the residual influence from the brain and
other supraspinal centers . However, since each SCI case alters the nervous system in a unique
way, it has been observed that using the fixed parameters for modulation of spasticity might fail.
This thesis presents the effects of stimulation intensity and frequency on the behavior of the motor
output and how the interaction of these parameters affects the level of motor suppression, which
ultimately leads to spasticity control.
Sustain tSCS was applied at the T11—T12 vertebral level of three subjects with complete SCI to
evoked sustain responses in the lower limbs. The neuromuscular activity was monitored via EMG
from quadriceps (Q), hamstrings (H), tibialis anterior (TA) and triceps surae (TS) of both legs. In
order to assess the suppressing effect of different stimulation frequencies and intensities, the
neuromuscular responses were quantified. An additional validation was carried on with eSCS data
obtained from an early study.
Threshold intensities eliciting the posterior root reflexes were inspected with low frequency (2 Hz)
stimulation and afterwards the suppression frequencies were estimated by increasing the
stimulation frequency gradually at different supra-threshold stimulation strengths. The results have
showed variety among not only the patients but also the muscles. In almost all cases with a few
exceptions, it has been shown that at constant stimulation strength, responses evoked to the
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stimulation are suppressed with increasing frequency. However, when the stimulation intensity is
increased the activity that has been previously suppressed at certain frequency came back.
All our results show a dependency between stimulation frequency and intensity in terms of
suppressing the motor output –controlling the spasticity. Therefore, it is concluded that in order to
increase the efficiency of SCS-based anti-spastic treatments, an assessment of the frequency-
intensity interaction has to be done to properly define the stimulation parameters, helping this way
to increase the success rate of the technique.
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Table of Contents
Acknowledgements .......................................................................................................................... i
Abstract ........................................................................................................................................... ii
Table of Contents ........................................................................................................................... iv
has been applied to both complete and incomplete SCI patients over different vertebral levels with
varying application parameters. Dimitrijevic has suggested that the efficacy of SCS in spasticity
control depends on the electrode placement and the diversity of physiological conditions after the
injury (M. M. R. Dimitrijevic et al., 1986).
Later a significant suppression of lower limb spasticity was shown when the epidural electrodes
were located over lumbar posterior roots and the simulation frequency range was applied within
50-100 Hz range (Pinter, Gerstenbrand, & Dimitrijevic, 2000), due to the modification of the
excitability of neural circuits achieved through continuous posterior root activation (Murg, Binder,
& Dimitrijevic, 2000; Rattay, Minassian, & Dimitrijevic, 2000). Modification of spasticity has
further been investigated by application of transcutaneous spinal cord stimulation (tSCS)
(Hofstoetter et al., 2014) and the results suggested that application of 50 Hz tSCS for certain period
of time leads to a reduction of spasticity and improvement of voluntary motor control.
So far, the literature puts forward that the application of higher frequencies through eSCS and
tSCS are appropriate for the control of the spasticity, however the results of protocols conducted
by our collaborators have shown that there are whole range of effects including total suppression,
mild suppression, no difference and negative effects increasing the spasticity. In consideration of
these results, in this work we investigate the behavior of the motor output to different stimulation
frequency and intensity and try to understand the role of the interaction of these parameters on the
control of the spasticity.
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2. Background
2.1 Anatomy of the Spinal Cord
2.1.1 Anatomy of the Spine
Spine, also known as vertebral column, is part of the axial skeleton. It contains thirty-three
vertebrae, twenty-four of those are movable and consisting of, from superior to inferior, seven
cervical (C1-C7), twelve thoracic (T1-T12), and five lumbar (L1-L5) vertebrae. The rest of the
spine consists of five sacral (S1-S5) vertebrae which fuse in the adult and forming the sacrum and
four more that are inferior to sacrum fuse late in adult life to form the coccyx (Co) or tailbone.
Two special vertebrae are C1(atlas) and C2 vertebrae (axis), on which the head rests. Figure 2.1
depicts the location of the thirty-three vertebrae in humans.
Intervertebral discs are located between the anterior portions of the movable vertebrae. There is
no disc located between the occiput and atlas or between atlas and axis. Discs have their names
from the vertebra found right above the disc; so, the T7 disc is located between T7 and T8
vertebrae.
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Figure 2.1 Five segments of the spine (left) and spinal nerve roots with corresponding vertebrae level and innervation sites (right) (https://en.wikipedia.org/wiki/Vertebral_column)
2.1.2 Spinal Cord
Spinal cord is part of central nervous system (CNS) extending caudally from foramen magnum to
lumbar vertebrae L1 or L2. It is encased by the bony structures of the vertebral column. According
to its location, spinal cord can be divided into five segments: cervical, thoracic, lumbar, sacral and
coccygeal. Although spinal cord is cylindrical, the diameter of the spinal cord enlarges in cervical
and lumbosacral regions due to the increased number of nerve cells innervating upper and lower
limbs respectively.
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Spinal Nerves
The spinal nerves have the function of carrying motor commands from the central nervous system
to target organs and muscles and transmitting sensory information in the other way around. Spinal
nerve pairs arise from the 31 segments of the spinal cord and exit the vertebral column between
the adjacent vertebrae. These 31 pair of nerves consist of 8 cervical (C1-C8), 12 thoracic (T1-T12),
The first seven cervical spine nerve (C1-C7) roots are found in the vertebral canals above their
respective vertebrae, the rest lay beneath their respective vertebrae. Cervical nerves increase in
size as the spinal cord extends downwards until C6 level and from C7 to T1 the size stays constant.
Thoracic spinal nerves from T2 to T12 are similar in size. Spinal nerves then increase in size over
the lumbar region and the largest spinal nerve is S1. After S1, sacral nerves get smaller and the
smallest spinal nerve is the coccygeal nerve.
Each spinal nerve is connected to the spinal cord by a ventral (anterior) and a dorsal (posterior)
root, each of which arises from several rootlets extending throughout the corresponding spinal cord
segment. Figure 2.2 shows the cross-section of a spinal cord and the connection of the spinal nerve.
While dorsal rootlets are made up of axons of sensory neurons, ventral rootlets are made up of
axons of motor neurons of the spinal cord. Each ventral root mainly consists of efferent somatic
motor fibers which are two type: (1) fibers that directly innervate skeletal muscle and (2)
preganglionic fibers that synapse on neuron cell bodies located in a peripheral visceromotor
ganglion. Postganglionic fibers arise from these ganglia innervate smooth muscle, cardiac muscle,
or glandular epithelium. Each dorsal root, on the other hand bears a dorsal root ganglion giving
rise to afferent sensory fibers that conduct sensation from the visceral structures made up of smooth
muscle, cardiac muscle or glandular epithelium.
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Figure 2.2 Cross-section of the spinal cord. Butterfly-shaped gray matter is found in the center and white matter surrounds it. Spinal nerve is composed of sensory and motor neuron soma and attached to the spinal cord via dorsal root and ventral root (http://www.newhealthadvisor.com/spinal-cord-cross-section.html).
2.1.3 Structure of the Spinal Cord
Cross-section of an adult’s spinal cord shows a butterfly-shaped area in the center, the gray matter,
and the white matter surrounding the center (Fig 2.2). The latter one (white matter) consists of
myelinated and unmyelinated nerve fibers, while the contents of the gray matter are cell bodies
and dendrites of the spinal neurons.
White matter
The white matter of the spinal cord is a base for; (1) ascending and descending fibers and (2)
propriospinal fibers. Ascending fibers conduct sensory information from afferents to the higher
levels of the neuroaxis. Descending ones carry information from supraspinal CNS structures and
influence the activity of neurons. Propriospinal fibers project from one spinal level to another and
form the basis for intraspinal reflexes.
The white matter is divided into three large regions. The posterior funiculus is found between the
medial edge of the horn and posterior median septum (Fig. 2.3) and consists of gracile and cuneate
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fasciculi where ascending fibers are located. The lateral funiculus is based between the
anterolateral and posterolateral sulci. In this area, clinically important ascending and descending
fibers are found, the locations are depicted in Figure 2.3. The small region occupying the area
between anterolateral sulcus and ventral median fissure is the anterior funiculus, which contains
vestibulospinal and reticulospinal descending fibers. Finally, regions that are next to the gray
matter are called fasciculus proprius in which propriospinal axons are located.
Figure 2.3 White matter tracts of the spinal cord. Blue and red areas representing ascending and descending fibers respectively. Pointed area surrounding gray matter is the location of propriospinal axons (Haines, Mihailoff, & Yezierski, 2018).
Gray matter
The gray matter within the spinal cord is a composition of neuron cell bodies, dendrites, initial
parts of axons, axon terminals synapsing in this area, and glial cells. It appears rather light due to
the fewer number of myelinated fibers. Gray matter contains prominent nuclear group of cells
intermediolateral nucleus and lower motor neuron nuclei (Figure 2.4).
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Axons of marginal zone neurons contribute to the lateral spinothalamic tract which conducts the
pain and temperature information. Substantia gelatinosa is associated with pain, temperature and
mechanical information. Nucleus proprious is a group of cells related to mechanical and
temperature sensations. Dorsal nucleus of Clarke is related to proprioception. Intermediolateral
nucleus receives viscerosensory information and contains preganglionic sympathetic neurons that
form the lateral horn. Lower motor neuron nuclei contain mostly motor nuclei.
Figure 2.4 Structure of the gray matter. Locations of spinal cord nuclei and Rexed Laminae (https://nba.uth.tmc.edu/neuroscience/s2/chapter03.html) Furthermore, gray matter can also be divided into three regions: posterior (dorsal) horn, anterior
(ventral) horn, intermediate zone, where first two regions meet.
Rexed Laminae
Based on the shape, distribution and size of the neurons, the gray matter is further divided into
laminae, also called Rexed laminae, I to IX and an area X around the central canal (Figure 2.4).
• Lamina Ⅰ corresponds to marginal zone and has low neuronal density with neurons of
variable size and distribution. In this area Waldeyer neuron cells are found predominantly.
These cells mostly respond to noxious and thermal stimuli.
• Lamina Ⅱ contains high number of neurons which receive information from dorsal root
ganglion cells, as well as descending dorsolateral fibers and send it to Lamina III and IV.
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Main two types of cells are stalked and islet cells containing GABA, therefore considered
as inhibitory cells.
• In lamina III low number of neurons with intermediate size are found. Neurons in this area
contain inhibitory transmitters GABA or glycine.
• Lamina IV has neurons projecting to the midbrain and brainstem and sending processes to
lamina IV itself.
• Lamina V-VI accommodate fusiform and triangular neurons in the middle and in its lateral
part medium-sized multipolar neurons corresponding to the reticular formation on the
brainstem are found.
• Lamina VII corresponds to the intermediate zone of the grey matter and is formed by a
homogeneous population of medium-sized multipolar neurons. This area is important for
autonomic sensory and motor functions.
• Lamina Ⅷ has neurons that modulate motor activity, most likely through g motor neurons
innervating the intrafusal muscle fibers.
• Lamina IX is made up of groups of cells that form motor nuclei whose axons are almost
entirely in the peripheral nervous system.
• Lamina Ⅹ contains neurons surrounding the central canal and they occupy the commissural
lateral area of the gray commissure.
To summarize, while laminae Ⅰ- IV is related to exteroceptive sensations, laminae V and VI are
associated with proprioceptive sensation and have the function of conducting between the
periphery, midbrain and cerebellum. Lamina Ⅷ and IX create the final motor pathway and have
the role of initiating and modulating motor activity. Lamina VII innervates neurons in autonomic
ganglia and contains all visceral motor neurons (Nógrádi & Vrbová, 2000-2013).
2.2 Peripheral Nervous System
Peripheral nervous system (PNS), which consists of pathways carrying information between CNS
and the rest of the body, is divided into two regarding the direction that the information is traveling.
Afferent (sensory) nerves within the PNS connects the sensory receptors on the body surface or
deeper within it to CNS and relay the sensory information towards spinal cord or brain. Efferent
(motor) nerves on the other hand conducts motor signals received from the CNS to the periphery.
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Peripheral axons of the neurons are enveloped by the special glial cells called Schwann cells which
cause myelination. Myelin sheet provides high electrical isolation and therefore electric current
cannot leave the axon. However, this sheet is not continuous and contains periodical gaps called
nodes of Ranvier, where the membrane can only be activated on Myelination of axons also result
in increased conduction of the action potentials along the fibers, since impulses propagate by
hoping from one node of Ranvier to another.
2.2.1 Afferent Nerve Fibers
Afferent nerve fibers are classified mainly according to their diameter and the sensory receptors
they innervate. The more myelinated they are, the larger is the diameter, and faster in action
potential conduction.
Aα/β fibers are responsible for transmitting mechanoreceptors signaling to laminae 3-5. These
fibers are highly myelinated, large in diameter and low in threshold. Aα can be divided in Ⅰa and
Ⅰb that innervate the primary endings of muscle spindles and golgi tendon organ respectively. Aβ
fibers also corresponding to type Ⅱ fibers and they innervate secondary endings of muscle spindles
and cutaneous receptors (Sengul, 2015) .
Aδ and C fibers, alternatively type Ⅲ and type Ⅳ, conduct nociception and thermoreception to
laminae 1-2. In comparison to Aα/β fibers, Aδ fibers are thinly myelinated, smaller in diameter,
lower in conduction speed and higher in activation threshold.
Approximately 70% of primary afferent fibers are comprised of unmyelinated C fibers (Nagy &
Hunt, 1983) which are the smallest in diameter and slowest in conduction speed.
2.2.2 Efferent Nerve Fibers
Efferent nerve fibers are the axons of the lower motor neurons originating in the spinal cord and
innervates the target muscle fibers (within the somatic nervous system). Lower motor neurons are
divided into three groups; alpha, beta and gamma motor neurons.
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Extrafusal muscle fibers of skeletal muscles are innervated by alpha motor neurons which are
directly initiating the muscle contraction. Beta motor neurons are responsible for innervating
intrafusal fibers of muscle spindles. Gamma motor neurons warrant alpha neurons firing by
Neurons are electrically excitable cells that possess a resting membrane potential around −70 mV,
which results from a gradient on the ion concentrations of extracellular and intracellular fluid.
Because of the negative membrane potential, in the resting state a neuron is said to be polarized.
The cell membrane contains ion channels, some of which can be opened by external stimuli
(mechanical, electrical, chemical). The opening of these channels results in changed ion
concentrations and membrane potential trend toward positive numbers. If the membrane potential
reaches around −55 mV, an action potential (AP) is triggered and membrane potential goes up to
+30 mV because of positive ion influx (depolarization). This phase is followed by a rapid swing
of membrane potential to even more negative values than in the resting state (hyperpolarization)
and this situation lasts for a few milliseconds resulting in refractory period which ensures that
action potential propagates towards one direction only (Figure 2.5).
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Figure 2.5 Action potential (adapted from https://digital.wwnorton.com/ebooks/epub/psychsci5/OPS/xhtml/Chapter03-1.xhtml)
Eventually the membrane turns back into the resting state, but passive spread of the depolarization
will ensure that the downstream segments of membrane to be depolarized and another action
potential will be triggered. If the neuron is unmyelinated, the AP spreads straight along the axon,
whereas if the neuron is surrounded by a myelin sheet then AP is forced to jump from one node of
Ranvier to another resulting in increased speed of propagation.
2.3.1 Activation with Electrical Stimulation
Action potentials can also be elicited by an artificial electrical field. An electrical field is
introduced on the biological system through electrodes causing the depolarization cells and hence,
arising of action potentials.
Strength-Duration Curve
Strength duration curve shows the relation between the intensity of an electrical stimulus and time
that a fiber needs to give a response.
Rheobase is the minimum amplitude of the applied current for infinite duration, practically 300
milliseconds, which results in the depolarization threshold of the membrane needed for action
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potential and chronaxie (strength-duration constant) is the pulse duration at the doubled rheobase
value. Intensity and the duration are inversely proportional and strength duration time constant is
not the same for different types of nerve fibers as it can be seen in the figure 2.6.
Most commonly used equations to represent strength duration curve is proposed by Weiss (1901);
= 1 +
and by Lapicque;
= 1 − 2 ⁄ where is the minimum stimulation needed to evoke an AP, is the rheobase, is the
chronaxie, is the duration of stimulation
Figure 2.6 Strength duration curve of several nerve fibers (adapted from (Hooker & Prentice, 2005)). Figure 2.6 shows that at a given intensity, low duration of stimulation targets Aβ fibers. In order
to target motor fibers, either intensity or duration of the stimulation should be increased.
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2.4 Spinal Reflexes
Reflex is a mechanism where peripheral sensory stimulation is transformed into an involuntary
motor response through the CNS. Spinal cord reflexes are produced by the activation of mono-,
oligo- or polysynaptic pathways that are found within the gray matter. While in monosynaptic
pathways afferent neuron synapses directly with the efferent neurons, in polysynaptic pathways
multiple synapses take place and interneurons provide the connection between afferent and
efferent neurons. In healthy individuals supraspinal centers have an impact on spinal reflexes, yet
it is still possible to elicit those reflexes in case of a neural disconnection between brain and the
spinal cord because of an injury.
2.4.1 Tendon Reflex
Tendon reflex is an example of stretch reflex. It is triggered by tapping muscle tendons like in knee
jerk response or patellar reflex. It used to be believed that this response is an intrinsic property of
a muscle, however later it was observed by (Liddell & Sherrington, 1924) that it can be abolished
by cutting ventral or the dorsal roots, which shows the requirement of sensory input from the
periphery to spinal cord and a path to return the muscle. Therefore, tendon reflex tests are
commonly used in clinic to observe the integrity of the spinal cord and peripheral nervous system,
as well as to investigate the presence of a neuromuscular disease.
When a tap is applied to a tendon, the muscle is stretched causing a change in the muscle length.
This change is sensed by the muscle spindles through Ia afferent fibers which directly synapse
with two sets of motor neurons: alpha neurons innervating the homonymous (same) muscle that
they originally arose and motor neurons innervating synergist muscles to contracts simultaneously.
While this is an example of monosynaptic pathway, Ia afferent fiber also makes a connection with
Ia inhibitory interneuron which is then connects to another alpha motor neuron innervating
antagonist muscle. This is an example of disynaptic pathway. Excitation of one group of muscles
while inhibiting of the antagonist is referred to reciprocal innervation. Due to the inhibitory effect
of this Ia interneuron, antagonist muscle relaxes. So that the counteraction of muscles is prevented.
Figure 2.7 shows a diagram of a tendon reflex.
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Figure 2.7 a) Tendon Reflex showing both monosynaptic and disynaptic connections within the spinal cord b) Polysynaptic pathways of withdraw reflex (Kendel, 2013).
2.4.2 Withdraw Reflex
Another example of spinal reflexes is withdraw/flexion reflex, which results coordinately
contraction of flexor muscles in a limb to withdrawn quickly after receiving a painful stimulus
from periphery.
Through the sensory signal, several polysynaptic reflex pathways are activated. One pathway
activates motor neurons innervation flexor muscle of the stimulated muscle, while it also inhibits
the motor neurons of extensor muscle through inhibitory interneurons. As a result, the stimulated
limb is withdrawn. Meanwhile an opposite effect in the other limb is produced by reflex to have a
supporting function, that is the activation of the motor neurons innervating extensor muscles and
inhibition of the motor neurons innervating flexor muscle in contralateral limb. This crossed-
extension reflex is reached via intraneuronal connections and results in enhanced posture. Figure
2.7 depicts the polysynaptic reflex arc.
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2.4.3 Hoffmann Reflex
Hoffman reflex, H-reflex is obtained by electrically stimulating the Ia fibers of muscles, most
commonly the soleus muscle and its synergist in the periphery and measuring the response in
homonymous muscle. The measured response depends on the stimulation strength. At low
intensity stimulations, only H-reflex is evoked since the activation threshold of the Ia fibers are
lower than the activation threshold of the motor axons. As the stimulation strength increases motor
axons which are innervating muscles are also excited and therefore two different responses, M-
wave and H-wave, are obtained. M-wave is a result of direct activation of the motor axons
immediately contracts the muscle (green path on Figure 2.8), whereas H-wave is a result of
stimulation of the Ia fiber (red path on Figure 2.8) on which the activation occurs and passes
through spinal cord first and then resulting in contraction, hence having a longer latency and
occurring later than M-wave. The time difference between H-reflex and M-wave is depicted on
Figure 2.8 B.
Recruitment curves of H-reflex and M-wave shows a difference in their amplitudes and stimulation
time they start to occur (Figure 2.8 C). At the low stimulation intensities due to the excitation of
muscle spindle afferents only, solely H-reflex is observed in the EMG recording. With increasing
stimulus intensity, some of the motor axons generate action potentials propagating in antidromic
direction, which starts cancelling reflexively evoked action potentials in the same motor axons. At
this point, M-wave is observed in the EMG recording together with H-reflex. The amplitude of M-
wave keeps increasing with further increased stimulus. However, H-reflex starts to decrease more
and eventually disappears because orthodromic motor signals which are reflexively generated by
muscle spindles are cancelled out entirely by antidromically propagating action potentials elicited
by electrical stimulus in the same motor axons. Therefore, in the EMG recording M-wave is
observed alone.
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Figure 2.8 M-wave and H-reflex. A) Ia sensory fiber is stimulated with an external electric field. Sensory fibers activate motor axon which results in activation of the muscle. Muscle response can be detected by EMG. B) With intermediate strength of the stimulus, M wave is activated as well as H-reflex. Due to the shorter path of M wave, it occurs earlier than H-reflex C) At low stimulus intensity, only H-reflex is seen, as the stimulus strength increases, H-reflex becomes larger and M wave is observed. With stronger stimulation H reflex decreases in amplitude because it is cancelled out by antidromic M-wave (Kendel, 2013)
2.4.4 Posterior Root Reflex
Another reflex that is obtained by electrical stimulation like Hoffmann reflex is the posterior root
reflex (PRR).When the electrical stimuli are applied close to the spinal cord, posterior root is
selectively depolarized and a PRR is evoked. Since PRR is started at proximal sites of spinal cord,
reflex arc is shorter in comparison to H-reflex and the response occurs in a shorter time. However,
between those two reflexes there are also similarities, such as being evoked from the same sensory
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axons, having constant latency, waveforms and amplitude in the EMG signals under invariable
conditions.
Stimulation of the peripheral nerves at high intensities activates motor axons and creates M-waves
besides H-waves as explained before. On the other hand, in case of transcutaneous spinal cord
stimulation, sensory fibers can be selectively recruited. Therefore, the output EMG signal consists
of solely reflex response. Figure 2.9 shows the comparison between Hoffmann and posterior root
muscle reflexes (PRMR).
Figure 2.9 Stimulation of tibial nerve results in M wave and H reflex. Posterior root stimulation over spinal cord results in posterior root muscle reflex (Karen Minassian, Hofstoetter, & Rattay, 2012).
PR reflexes can be elicited by different stimulation methods. In literature, most common ones are;
1) epidural spinal cord stimulation (eSCS), in which the stimulation is applied via electrodes
implanted over the lumbar spinal cord, 2) transcutaneous spinal cord stimulation (tSCS), non-
invasive method in which a pair of surface electrodes are placed over the skin on the both sides of
the spine. The positions of the electrodes are T11-T12 level of the spinal cord to stimulate
lumbosacral region and record the PRMR from the lower limb muscles such as quadriceps,
hamstring, tibialis anterior and triceps surae (Figure 2.10).
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Figure 2.10 Positions of the stimulation electrodes and PRM responses obtained from quadriceps (Q), hamstring (H), tibialis anterior (TA) and triceps surae (TS) elicited by transcutaneous spinal cord stimulation (tSCS) (above) and epidural spinal cord stimulation (eSCS) (Karen Minassian et al., 2012).
2.5 Spinal Cord Injury
Spinal cord injury is referred to a damage on the spinal cord impairing the connectivity between
the brain and the rest of the body. Depending on the severity and the location of the incident the
function of the spinal cord is changed permanently or temporally, and the extension of the damage
differs. Body parts that are innervated by spinal nerves emerging below the injury level can
undergo loss of sensory and autonomic activity. Higher the injury level, the more extensive the
damage is on the body and as a result individual can face with tetraplegia, paraplegia or
monoplegia. In case of tetraplegia, the injured area is at the cervical level and both upper and lower
limbs are affected. If the injury level in on the thoracic or lower levels of the spine, only the lower
limbs are affected, this pathological case is then called paraplegia. Apart from varying degrees of
paralysis, individuals can also experience incontinence, chronic pain, muscle spasms, difficulty in
breathing.
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2.5.1 Epidemiology of Spinal Cord Injury
Although incidence of traumatic spinal cord injury is relatively low, it is not only a devastating
incident in individual level, but also has huge impact on the families and on the society in terms
of economy due to the large costs of acute care in the short term and management of secondary
complications occurring in the long term. According to Krueger et al 2013, estimation of lifetime
economic burden ranges from 960.000 € for a person with incomplete paraplegia to 1.97 million
€ for one with complete tetraplegia (Krueger, Noonan, Trenaman, Joshi, & Rivers, 2013).
Figure 2.11 Recent trends in causes of spinal cord injury (National Spinal Cord Injury Statistical Center, 2018) According to a recent report that is published in 2018 by National Spinal Cord Injury Statistical
Center, vehicular accidents ranks the 1st place in causes of the injury with auto accidents taking
the first place among them. Falls are the second main reason of spinal cord injuries which is then
followed by violence, sports and recreation and other reasons (Figure 2.11).
A review conducted by Yi Kang et al 2011, shows that incidence rate has gradually increased over
time from 13.1 per million to 163.4 per million people in developed countries and from 13.0 to
220.0 per million people in undeveloped countries. (Yi, Han, Hengxing, & Zhijian, 2018).
38.72
30.67
13.46
8.83
8.31
Recent Trends in Causes of Spinal Cord Injury
Vehicular Accidents
Falls
Violence
Sports and Recreation
Others
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Number of males who suffers from SCI were always higher than the women with male/female
ratio varying from 1.1:1 to 6.69:1 among developed countries. The mean age of having SCI ranged
from 14.6 to 67.6 years in developed countries (Yi, Han, Hengxing, & Zhijian, 2018).
In the US only, the average age at injury has increased from 29 years during the 1970s to 43 years
currently and 78% of the new SCI cases were suffered by males (National Spinal Cord Injury
Statistical Center, 2018).
In most of the cases the injury affected the cervical level of the spine and while incomplete injuries
occurred more than complete injuries, in terms of disability classification tetraplegia was reported
more commonly than paraplegia.
Mortality of patients was still high. Estimations of SCI mortality among developed countries
varied from 3.1% to 22.2% (Yi, Han, Hengxing, & Zhijian, 2018).
2.5.2 Clinical Classification of Spinal Cord Injury
There are two main clinical definitions of spinal cord injury:
• Incomplete SCI, in which the spinal cord is partially spared and motor functions caudal to
the lesion are altered but remained to some degree.
• Complete SCI, in which the voluntary and sensory functions are completely lost and no
supraspinal influence is clinically found below the level of the injury.
Apart from these two terms, a subclinical term ‘anatomically discomplete’ is described based on
neurophysiological criteria. In some patients who are first diagnosed as clinically complete,
neurophysiological evidences of signals transmitting across the injured area and resulting in
change in recorded patterns were found. These signals are thought to be coming from supraspinal
structures and induced by conscious effort or by reflex enhancing maneuvers like neck flexion
(Kakulas, Tansey, & Dimitrijevic, 2012). Postmortem evidences of small number of axons
surviving the SCI and passing through the injured level without an interruption exist and supports
the concept of neurologically discomplete SCI syndrome (Kakulas, 1999).
23
ASIA Impairment Scale
Neurological standard scale of American Spinal Injury Association (ASIA)/International Spinal
Cord Society (ISCoS) is commonly used in the clinic to asses and classify spinal cord injuries.
This classification is composed of 4 steps:
1. Determining the lesion level based on conscious and volitional motor testing
2. Determining whether the injury is complete or incomplete
3. Determining the ASIA impairment scale (AIS) grade
4. In case of complete injury, determination of the zone of partial preservation (ZPP) which
refers to the partially innervated dermatomes and myotomes below the injury level
(Kirshblum, 2011)
AIS includes five grades to describe the degree of impairment (Table 2.1).
Table 2.1 ASIA impairment scale grade
ASIA Grade Type of Injury Definition A Complete No sensory or motor function
preserved in S4-S5 B Incomplete Sensory but not motor function is
preserved below the neurological level (including S4-S5)
C Incomplete Motor function is preserved, and more than half of key muscles have a muscle
grade less than 3 D Incomplete Motor function is preserved, at least
half of key muscles have muscle grade greater than or equal to 3
E Normal Sensory and motor function is normal
2.5.3 Residual Motor Control After SCI
A small percentage of people with acute spinal cord injury may experience significant functional
improvement in time, however the majority show diverse dysfunctions with different degrees of
incompleteness and deficient functional recovery. Patients with residual motor control, like in case
24
of discomplete SCI, can produce clinically obvious movements, as well as subclinical alterations
that are observed by means of neurophysiological recordings (Sherwood & Dimitrijevic, 1996).
Some studies show that administered motor tasks induce subclinical motor outputs, which can be
recorded by surface electrodes over several muscles. Recorded EMG patterns then can be
evaluated to understand the dissimilarities between different cases in order to determine the
remaining neural connections for treatment planning after SCI (McKey & Sherwood, 2004). In
case of patients with residual brain influence on spinal reflexes, several restorative neurological
intervention methods such as neuromuscular stimulation, spinal cord stimulation and functional
stimulation can be used to enhance the residual motor control (Milan R. Dimitrijevic, 2012).
2.5.4 Spinal Cord Stimulation
Spinal cord stimulation (SCS) is a technique taking the advantage of nerve cells being electrically
active cells as explained in electrical properties of nerves chapter. Application of the electricity is
applied by means of surface (transcutaneous) and implanted (epidural) electrodes to elicit the
posterior root afferents entering the spinal cord.
Spinal Cord Stimulation has been used to elicit rhythmical and tonic activity, with the purpose of
modification of the motor control in patients with SCI. Early studies showed that application of
non-patterned electrical stimulation to the posterior roots over the lumbar level of the spinal cord,
evoked patterned EMG activity, showing that even if the spinal cord is disconnected from the
brain, it is able to generate locomotor-like activity with the help of external electrical stimulation
(Dimitrijevic, Evidence for a spinal central pattern generator in humans, 1998).
As mentioned in previous sections, the activation threshold of the nerve fibers is inversely
proportional to their diameter. Recruitment of fibers depends on the stimulus intensity, which
means proprioceptive afferents react first, and with increased intensity, cutaneous afferents are
recruited additionally. Activated fibers then project to their homonimus motoneurons—initiating
a reflex—and other interneurons, which can result in complex contraction and relaxation patterns
taking place in muscle groups, which can be observed with EMG (Mayr, Krenn, & Dimitrijevic,
2016).
25
Lower intensities, as well as high intensity stimuli, generate short latency responses. However, as
the intensity increases, interneuronal networks get involved and longer latency potentials are
evoked. Short-latency responses are mostly reproducible, although they can also be modified with
movement in humans with spinal cord injury, 2015).
26
3. Material and Methods
As mentioned in the introduction, spinal cord stimulation can be applied via transcutaneous or
epidural electrodes. This work retrieve data from both kind of stimulations, to assess the influence
the relation of stimulus frequency and amplitude on reflex responses in individuals with SCI. Since
each of these methods has different technological requirements for its application, the
methodology used on each type of stimulation will be described separately.
3.1 Transcutaneous Stimulation
3.1.1 Subjects
Transcutaneous spinal cord stimulations were applied on three male subjects all with clinically
complete spinal cord injury. All the subjects signed written informed consents to participate and
the study was approved by the local ethics committee. Table 3.1 lists the subjects and the relevant
information about them.
Table 3.1 Subject Information for tSCS
Subject ID Sex Age Years Post Injury Level of Injury AIS
P01WI M 36 14 C5/C6 ASIA A
P07HK M 35 15 C5 ASIA A
P08PS M 26 9 C4 ASIA A
27
3.1.2 Equipment
3.1.2.1 Stimulation System
The stimulation system used in transcutaneous measurements can be divided into four main parts:
1) Software to generate the digital stimulation, 2) Digital to analog conversion, 3) Filtering, 4)
Generation of the signal. A visual interface developed in LabVIEW™ was used to choose, create
and transfer the desired stimulation pattern to the external hardware, which is a modified version
of the device developed by a former colleague (Eickhoff, 2017). The stimulation settings, such as
polarity, pulse shape, amplitude, number of pulses, frequency and so on, were selected through the
interface of the program via checkboxes, switches and manually entered numeric values. When
the selection of preferred parameters was finished, the stimulation data itself was generated by
means of an embedded MATLAB® script to realize chosen stimulation patterns with maximum
flexibility. After the generation of the digital stimulation data, it was sent to the multifunctional
I/O device (NI USB 6221 OEM, National Instruments™, USA), where it was converted to an
analog voltage signal with a range of +/-10V and a resolution of 16 bits. Before the output of the
converter transferred to the stimulator, a high pass filter was used to avoid applying direct current
(DC) to the subject.
In this study, the linear isolated stimulator (STMISOLA, Biopac Systems, Inc., USA) (Figure 3.1)
was used in order to generate desired stimulation signals with arbitrary wave shapes. The device
can be controlled by an analog input signal that is ± 10 V. The current mode with Z=100 Ω output
of the stimulator was used. Such modality allows the transducing of ±10 V input into ±100 mA.
Figure 3.1 BIOPAC® Linear Isolated Stimulator STMISOLA used for generating stimulation signals.
28
3.1.2.2 Stimulation Setup
With the aim of obtaining the optimum results, the applications of the spinal cord stimulation had
to be adapted according to the situation of each subject. For subject P01WI rectangular shaped
stimulation electrodes (Axion®, Germany) in size 10x5cm were placed over the spine. To apply
the stimulation to subject P07HK two square shaped stimulation electrodes (FITOP®, U.S) in size
5x5cm used. Finally, for subject P08PS, two pairs of square electrodes (FITOP®, U.S) (two for
cathode and two for anode) were placed on both sides of the spine. In each case cathode electrodes
were placed over T11, anode electrodes were placed over L3 level of the spine (Figure 3.2).
Figure 3.2 Placement of the stimulation electrodes. In order to stimulate the posterior roots, cathode electrode was placed over T11 and anode was placed over L3 level of the vertebrae.
3.1.2.3 Recording Setup
The neuromuscular responses to the transcutaneous spinal cord stimulation were monitored via
surface polyelectromyography on the major muscle groups of the lower limbs. A pair of reusable
Ag/AgCl electrodes (Natus Europe, Germany) were placed centrally over the muscle belly of the
four muscle groups on the both legs; quadriceps (Q), hamstrings (H), tibialis anterior (TA) and
triceps surae (TS), which refers to channels from 1 to 8 in recording setup (details can be read in
measurement protocol section). Apart from eight channels recording the neuromuscular activity,
one channel to record the stimulation onset was used. EMG electrodes were positioned along the
29
long axis of the muscles with 3 cm distance from each other. A reference electrode was situated
on the proximal end of the fibula bone of both legs. Positions of the EMG electrodes are depicted
on Figure 3.3.
Figure 3.3 EMG electrode positions over the lower limbs A) quadriceps, triceps surae B) hamstrings, tibialis anterior C) reference electrode on the proximal end of fibula. The EMG activity was amplified with a customize bio-amplifier developed at Center for Medical
Physics and Biomedical Engineering at the Medical University of Vienna. The signals were
amplified with a gain of 600 and bandwidth filtered between 10 – 600 Hz. The conditioned signals
were then sent to a National Instruments USB-6221 OEM (National Instruments Corp., USA)
device to be digitized and saved. Recording of the signals were achieved with a software previously
written in LabVIEW™.
3.1.3 Measurement Protocol
Measurement protocol of this study was designed to detect the threshold intensities that excite the
lumbar spinal cord network and frequencies needed to reduce/suppress the motor output of four
leg muscle groups. In order to reach this goal, after preparation of the subject and placement of the
electrodes, a fast recruitment curve was realized during the measurements to detect threshold
intensities where neuromuscular responses evoke and start saturating. These intensities were then
30
further used in frequency sweeps to observe the reduction in the responses affected by different
frequencies. The protocol is explained in detail in the following sections.
Preparation of the skin and placement of the electrodes
Protocol was started with the preparation phase, where the subjects were first informed about the
procedure. Before the placement of the electrodes, the skin was gently cleaned by application of
an abrasive skin preparation gel (Nuprep®, Weaver and Company Aurora CO, USA) in circular
movements with cotton swabs to decrease the skin impedance and each electrode was filled with
EMG electrodes were placed over target muscles as shown in figure 3.2 with a channel order of:
1. Left Quadriceps (LQ)
2. Left Hamstrings (LH)
3. Left Tibialis Anterior (LTA)
4. Left Triceps Surae (LTS)
5. Right Quadriceps (RQ)
6. Right Hamstrings (RH)
7. Right Tibialis Anterior (RTA)
8. Right Triceps Surae (RTS)
In order to avoid the accidental detachment of the electrodes during the measurement, they were
attached to the skin with skin-friendly transparent tape. Last but not least, the channels were
checked to ensure the connection quality and to avoid noise.
Recruitment Curve (RC)
Stimulation electrodes were placed over the spine as explained above in 3.2.2 Stimulation Setup.
The intensity was increased by applying single pulses until the first response (It) was observed and
the maximum tolerable intensity (Ip) was reached. The pulse was configured as biphasic +/- of 1
ms per phase.
Parameters of the recruitment curve were set on the LabVIEW interface. The software started
stimulating with It and the intensity was increased 5 or 10 mA at each step until the Ip or 100 mA
were reached. Recorded data was then processed in MATLAB (The MathWorks, Inc., Natick, MA,
31
USA) with a previously written script. Two intensities were selected: I100 was defined as the
intensity at which the first muscle starts to saturate, I80 was defined as 80% of I100. If I80 could
not produce evoked potentials in all muscles, then a higher intensity was applied. Table 3.2 lists
the stimulation intensities applied during recruitment curves.
Table 3.2 List of Recruitment Curves in tSCS Subjects
Subject
ID
Stimulation Intensity (mA)
P01WI 30, 40, 50, 55, 60, 65, 70, 95
P07HK 30, 40, 50, 60, 65, 70, 75
P08PS 50, 55, 60, 70, 75, 85, 95
Frequency Sweep (FS)
Before running frequency sweep, it was tested if the subject could tolerate I80 at 100 Hz, if not
I80 was defined as the maximum tolerable intensity at 100 Hz. Frequency sweep run a continuous
sweep of frequencies with intensity of I80. Application of each frequency continued for 5 seconds
and followed by the next frequency without a pause in between. Table 3.3 lists all the frequencies
applied per stimulation intensity.
Table 3.3 List of the Parameters used in Frequency Sweeps in tSCS Subjects
Subject ID Frequencies (Hz) Intensity (mA)
P01WI 2, 5, 8, 10, 15, 20, 25, 30, 40, 50 70
P01WI 2, 5, 10, 15, 20, 25, 30, 40 95
P07HK 2, 5, 8, 10, 15, 20, 25, 30, 40 75
P07HK 2, 5, 8, 10, 15, 20, 25, 30, 40 90
P08PS 2, 5, 8, 10, 15, 20, 25, 30, 50, 80 85
P08PS 2, 5, 8, 10, 15, 20, 30, 50, 80 95
32
3.1.4 Data Analysis
Pre-processing
To pre-process the transcutaneous stimulation data, it was first filtered with a 6th order Butterworth
band pass filter by using butter function of MATLAB R2015b, to reduce the 50 Hz noise from the
signals. The channel storing the onset of the stimulation artifacts was used for identifying the exact
stimulation time. In the written algorithm, parameters of each stimulation section (frequency,
intensity) were entered manually and the artifact localization was applied per channel and section.
Artifact indexes were searched on the stimulation channel with manually entered parameters: 1)
Threshold 2) Find next range. As a result, absolute values of the signal were taken and the peaks
whose amplitudes were higher than threshold and that are in a distance from previous artifact by
6 ms were detected. Parameter values were chosen after manual observations on the data. Artifacts
were removed by replacing artifact data points with zeros.
Following step of the pre-processing was offset removal, which was done by subtracting the mean
noise from the signal. Noise of the signals were calculated separately for each channel from parts
of the signals where there was neither artifact nor response.
Quantification of Data
After cleaning the data from artifacts and correcting the baseline, the neuromuscular responses to
each stimulus applied were estimated by detecting the peak to peak (P2P) and root mean square
(RMS) values of the responses. P2P and RMS values of every single stimulation were stored in a
database and a summary was created with taking the mean and standard deviation of these values
taken from each section to be plotted afterwards.
Peak to peak values were calculated by taking the difference between minimum and the maximum
points of the EMG responses between each adjacent stimulus. This operation was applied through
the whole stimulation section except the first three responses, since these responses were showing
behavior similar to single pulse stimulation, which is not the interest of this thesis. Peak to peak
values were used to plot the recruitment curves to observe the intensities (threshold intensities) at
which muscles give response to the stimulation. Determination of the threshold intensities was
done by comparing the mean P2P of the first (2 Hz) stimulation section to a limit value which is
33
six times of the standard deviation of the noise per channel. If the mean P2P value of the
corresponding section was higher than the limit, this intensity was accepted as the beginning of
the muscle responses.
In the next step RMS values of the signals were calculated with the help of rms function in
MATLAB R2015b (The MathWorks, Inc., Natick, MA, USA). RMS function was applied to the
areas of the signals where the responses are expected to occur. Therefore, in upper leg muscles
like quadriceps and hamstrings, rms calculation was conducted between 11 and 37 milliseconds
(ms) after the stimulation onset, and in lower leg muscles like tibialis anterior and tibialis surae,
since the responses occur later, this time interval was set to 17 ms and 40 ms after the stimulation
onset. Figure 3.4 shows the time difference between the responses of different muscles.
Figure 3.4 An example of evoked potentials in each muscle to stimulation of 95mA at 10 Hz. Vertical red lines indicate the regions that the stimulation artifacts were removed. First red line corresponds to the stimulation onset. Blue lines are the recorded signals. As it can be seen the responses elicited the stimulation arise on slightly different moments.
The effects of intensity and frequency on overall suppression of the posterior root reflexes were
quantified in relation to the RMS calculation of the whole stimulation section (between 2
contiguous pulses). RMS values were intended to be used in frequency sweep plots for better
visualization of the data and determination of the suppression frequency. In order to determine the
34
suppression frequency, in the first step, recordings were classified as a response or not response
according to the mean P2P value calculated from a stimulation section with intensity of interest
and 2 Hz frequency. If mean P2P value was higher than six times of the standard deviation of the
corresponding channel, then this recording was classified as a response. As a second step, if there
was a response, two parameters were used to determine the suppression intensity. The first
suppression parameter was decided as the 20% of the mean RMS value of the first section and the
second parameter was decided as the six times of standard deviation of the noise. The algorithm
searched for the intensity in which the mean RMS goes below of one of these two parameters and
this intensity was decided as suppression intensity. This procedure was applied to each channel
separately.
3.2 Epidural Stimulation
Findings observed on the transcutaneous stimulation data are further validated with an additional
dataset available at the Medical University of Vienna. This dataset contains data acquired during
the application of epidural stimulation in early studies (Murg et al., 2000; Rattay et al., 2000)
3.2.1 Subjects
Subject EP1, whose eSCS data was used in this thesis, was a 25 years old male with spinal cord
injury type ASIA B. The measurements were done 2 years after the injury. The vertebral level of
fracture was noted as C5/C6 and the neurological level of injury was noted as C8.
Datasets that are used were obtained with two electrode set up; 0-3+ and 3-0+ depending on the
location of cathode and anode electrodes. For detailed explanation please read the stimulation
setup section.
35
3.2.2 Stimulation and Recording Setup
Stimulation Setup
The epidural stimulation (eSCS) was applied via surgically placed quadripolar electrodes (3487A,
Medtronic, USA) (Fig 3.5). The electrodes contacts were implants in the posterior epidural space
at the T11 to L1 levels of vertebrae. The four contacts of the electrodes were labeled as 0, 1, 2 and
3 from most rostral to most caudal. Positions of the electrodes were confirmed with fluoroscopy
and fine adjustments were made by monitoring the produced twitches on the lower limb muscles,
so that the most rostral electrode was close to L2 cord segment. Electrodes were connected to an
external stimulator (Model 3625, Medtronic, USA) and stimulation pulses were applied with
monophasic pulses of 210 ms pulse width. To ensure the electrochemical stability of the electrodes,
a charge compensating phase was applied after each stimulus (Murg et al., 2000).
Figure 3.5 Implant location of the stimulation electrode in eSCS (Murg et al., 2000)
Recording Setup
Electromyographic responses were recorded from quadriceps (Q), adductor (A), hamstring (H),
tibial anterior (TA) and triceps surae (TS) muscles of both legs as well as trunk muscles like
paraspinal (Para) and abdominal muscles (Abd). Beckman recessed silver-silver electrodes were
36
bilaterally placed over the bellies of these muscles with 3 cm apart from each other. Before
electrodes were placed, the skin was gently abraded to reduce electrode impedance to less than
5kOhms in order to keep the artifacts as low as possible. Grass 12A5 amplifiers (Grass
Instruments, Quincy, MA, USA) with a gain of 5000 over a bandwidth of 50 ± 800 Hz (73dB) was
used to record the activity. Digitization was achieved by Codas ADC system (DATQ Instruments,
Akron, OH, USA) at 2k samples per second per channel at a bit depth of 12 bits. All recordings
were performed with the subject lying down in a comfortable supine position (Murg et al., 2000).
The stimulation intensity started at 1 V and gradually incremented in steps of 1 V until the
saturation of the neuromuscular responses were reached. Finally, stimulation frequency was
changed from 2 Hz to 100 Hz in each intensity step. Summary of stimulation protocol can be seen
table 3.4.
Table 3.4 List of Parameters used in Epidural Spinal Cord Stimulations
Subject ID Frequency (Hz) Intensity (V)
EP1 0-3+ 2.1 1
2.1 2
2.1 3
2.1, 10, 16, 21, 31, 40, 50, 85, 100 4
2.1, 10, 16, 21, 31, 40, 50, 85, 100 5
2.1, 10, 16, 21, 31, 40, 50, 85, 100 6
2.1, 10, 16, 21, 31, 40, 50, 85 7
EP1 3+0- 2.1, 10, 16, 21, 31, 40, 50, 85, 100 2
2.1, 10, 16, 21, 31, 40, 50, 85, 100 3
2.1, 10, 16, 21, 31, 40, 50, 85, 100 4
2.1, 10, 16, 21, 31, 40, 50, 85, 100 5
37
3.2.3 Data Analysis
3.2.3.1 Preparation of Epidural Spinal Cord Stimulation Datasets
Epidural spinal cord stimulation data that are used in this thesis were obtained from a previously
conducted study (Murg et al., 2000), in which recording of the data was done with WinDaq data
acquisition and playback software (DATAQ Instruments Inc, Ohio). Therefore, the format of
measurements first had to be changed to be processed in MATLAB R2015b. In order to achieve
that, continuously recorded EMG responses were observed with WinDaq software and manually
cut into their sections according to intensity and frequency changes in the continuous signals and
saved as spreadsheet print (CSV). The name of each section was formatted as:
An m-file was created to store the data in hierarchical format to make it easier to access the
intended sections. MATLAB R2015b function sorted the sections according to their recording
times and each section was then later retrieved in this order to gather and store the attributes as
well as the signal itself in h5 file. The attributes were determined as starting and ending index,
stimulation frequency, stimulation intensity, pulse width and positions of the cathode and anode
of each section.
3.2.3.2 Processing of the Data
In order to detect the muscle responses and make the further calculations correctly, stimulation
artifacts had to be detected and removed from the signals. This was especially important for the
stimulations with frequencies higher than 50 Hz, in which the reflex responses were overlapping
with the stimulation artifacts and therefore either altering the minimum-maximum values or
causing the false detection of the responses. Offset of the measurements were also removed. As a
last step of preprocessing, every measurement section was cut into 8 seconds length because this
was the length of the shortest measurement.
Artifact Detection
Although stimulation artifacts were low in amplitude, they could still cause miscalculation and
misinterpretation of the data, therefore they had to be removed. Paraspinal channel was used for
38
detection of the artifacts, since the stimulation artifact to response ratio were very high in
comparison to the other channels, therefore easier to detect.
In the dataset that was used, previously specified frequencies were not matching with the actual
frequency of the measurement. Therefore, a method was developed to detect the stimulation
artifacts correctly and to replace the real frequencies with old ones. Developed method takes
advantage of the abrupt changes in the values of the stimulation artifacts. The signals were
differentiated in the fifth order, as a result, artifact values, which obtain sharp peaks, were
incremented with a much higher ratio than the responses, that were not as sharp as stimulation
artifacts. Some of the frequencies were manually corrected and the actual values were entered to
start the search. An amplitude threshold is manually entered after observing the peaks and a range
is calculated with taking 80 percent of sampling frequency and manually corrected stimulation
frequency ratio. Indexes were detected according to these values. Differences between indexes
value were calculated in an array and the median of this array was taken and accepted as a mean
value to be used in further detection and control. Some of the artifacts were still missed, therefore
previously calculated mean value was used to detect the locations of the missed artifacts. Wherever
the differences of adjacent artifacts were higher than 1.5 times of the mean value due to the false
detection of the artifacts, the values corrected. This process repeated until all the artifacts are
correctly detected. At the end, real frequencies were calculated by dividing sampling frequency to
mean artifact difference and stored in an array.
Artifact Removal
After the detection of the artifact locations of one whole section, artifact removal applied. After
the application of several methods like deleting artifacts with highest correlation, or principal
component analysis (PCA) and independent component analysis (ICA), the decision was applying
interpolation on each artifact. Interpolation was applied between two data points before and six
data points after the artifact peak, as a result two data points were connected together with
appropriate values. Figure 3.6 shows examples of signals before and after artifact removal
procedure.
39
Figure 3.6 Muscle response to epidural stimulation with 4 V at 50 Hz recorded on right quadriceps of a subject. A) Recorded signal, small red squares identify locations of stimulation artifacts B) Shows the same section of the signal after detection and removal of stimulation artifacts. After removing stimulation artifacts, baseline was corrected by removing offset which was
determined as the mean noise of the signal where there were neither responses nor artifacts. Mean
noise was calculated from 3 V stimulation at 2.1 Hz because this was the intensity where the reflex
responses arose. As the next step quantification of the data was done by applying the same
procedure explained in transcutaneous data quantification.
3.3 Statistical Analysis
In order to compare the effect of Intensity (I), Frequency (F) and Muscle (M) factors on root mean
square of the evoked potentials, a three-way ANOVA was conducted. Furthermore, to see whether
Intensity and Muscle factors play a role on suppression frequency, a two-way ANOVA was
applied. ANOVA stands for analysis of variance, and variance refers to the variability of the data
around the mean. This method was used to find out whether the variability of RMS values and
detected suppression frequencies are due to the factors mentioned above or the normal variability
of the data. The confidence level was set to α=0.01, which means if the resulted P value was greater
than the confidence level, the observed factor does not affect the evoked responses and the activity
suppression frequency.
40
Three-way ANOVA was applied to each subject separately, in a way to observe the effect of
factors I, F, M both independently and combining one another. All the successful stimulation
responses were included into the test. In order to conduct two-way ANOVA, suppression
frequencies per stimulation, per muscle were detected with the help of the parameter mentioned in
3.1.4 Data Analysis section. Dependency of the detected suppression frequencies to stimulation
intensity and muscle factors were tested per subject.
41
4. Results
The results will be presented in two sections, which correspond to the methodology used to apply
the electrical stimulation, transcutaneous and epidural. This separation is due to the difference on
the stimulation type — current controlled for transcutaneous stimulation and voltage controlled
for epidural use different units and therefore the intensity levels are not comparable.
4.1 Transcutaneous Stimulation
The measurement protocol was successfully applied on the three subjects: P01, P07 and P08. In
the first part, the recruitment curve was identified based on the average responses to sustained
stimulation at 2 Hz. Figure 4.1 presents an example of the neuromuscular responses overlapped
(N = 8) for different stimulation intensities (subject P08). It is observed that the responses became
larger with the increasing of stimulation intensity. Responses from a fixed stimulation intensity
show similar shapes with a small amplitude variance.
42
Figure 4.1 Repeating single responses of each stimulation sequence of recruitment curve is plotted over each other. It can be observed that with increasing stimulation intensity, evoked potentials give higher amplitude responses. Following responses of each stimulation section shows similarity in response shape with a small variance in amplitude. Figure 4.2 shows the recruitment curve plotted with the Peak to Peak amplitude (mean ± standard
deviation) of evoked potentials versus the stimulation intensity for one subject (P08).
Figure 4.2 Recruitment curve from subject P08 showing the neuromuscular responses Peak to Peak amplitude (mean +- standard deviation) versus the stimulation intensity. The threshold intensity differs between ipsilateral and contralateral muscles. Muscles from left leg A) need higher intensities to have
43
activity compared to the right leg B) muscles. Triceps surae give the highest response and starts saturating at 50 mA while quadriceps can only start giving small responses at 70 and 85 mA respectively. It is shown that although the stimulation setup is defined to be symmetrical, the neuromuscular
responses were not perfectly symmetrical. In addition, it is observed that the electrical field
distribution along the segment of the spinal cord is different, recruiting the different motor pools
of the muscles in a non-homogenous way. These variations were observed among all the subjects,
as shown in Figure 4.3. The field strength across the different motor pool can significantly differ
between subjects. In this case, while in P01 sustain neuromuscular responses in all muscles can be
elicited by low-frequency (2 Hz) SCS at 30 mA in P08 the intensity thresholds for each muscle
are more distributed.
Figure 4.3 Intensity sweep of P01 (A) and P08 (B) demonstrate how responses are changing within different subjects. Our criteria for responses suggest that in subject P01 all the muscles shown start giving responses with 30 mA stimulation intensity, whereas in subject P08 the values differ. Response intensities for subject P08 are as follows, LTS at 50 mA LH and LTA at 60 mA and LQ at 70 mA Table 4.1 summarized the threshold intensities at which each muscle shows a sustain response to
a 2 Hz SCS. Similar to Figure 4.3, the data among the three subjects shows how the recruitment
of each muscle group vary within a single subject and between subjects.
44
It should be noted that criteria for detection of the muscle thresholds were hold the same for all
transcutaneous measurements however the minimum and maximum stimulation intensities were
defined differently for each subject depending on the discomfort induced by the stimulation. For
example, the maximum stimulation intensity for P07 was 75 mA, whereas the other subjects could
handle 90 mA and 95 mA.
Table 4.1 Thresholds (mA) of lower limb muscles of subjects P01, P07, P08 with 2 Hz stimulation
Subject ID
Muscles P01 P07 P08
LQ 30 60 70
LH 30 75 60
LTA 30 50 60
LTS 30 60 50
RQ 30 30 70
RH 30 50 55
RTA 30 65 60
RTS 30 60 50
Once a sustain response was achieved at low-frequency stimulation, the stimulation intensity was
fixed, and the frequency was gradually increased after 5 seconds of stimulation periods. Figure
4.4 shows the typical behavior observed when the frequency is increased. It is observed that at the
beginning of each frequency segment, there is a period of stabilization. Also, when the frequency
keeps increasing, a generalized reduction of the neuromuscular responses occurred.
45
Figure 4.4 Frequency sweeps of left leg muscles of subject P08 with stimulation intensity 95 mA. Each color represents the stimulation section with the corresponding frequency written above. Scales are not kept constant for better observation of the variation. Difference between the maximum and minimum amplitude within each section is the highest with 8 Hz stimulation frequency. This difference decreases with increased suppression. The quantification of the responses is summarized in figure 4.5, showing that such trend is present
at different stimulation intensities. Interestingly, it is also possible to observe that, although the
reduction of the responses occurs at all intensities, stronger stimulation pulses require higher
frequencies to completely suppress the responses. All the plots support that neuromuscular
responses evoked by the stimulation, which is here measured and represented as mean RMS value
of each stimulation section, decrease with increased frequency. However, this decrease shows
diversity amongst muscles depending on the intensity. As it can be seen on figures, at the
stimulations with 75 mA almost all the muscle activity is suppressed at 8 Hz. However, as the
intensity is increased to 85 mA and 95 mA, stimulation frequency also needs to be increased in
order to achieve suppression.
46
Figure 4.5 Frequency sweeps applied on subject P08 at 75 mA, 85 mA and 95 mA. Plots shows the mean RMS values of stimulation sections of right leg muscle at different stimulation frequencies. Evoked potentials are going down with increased stimulation frequency in all muscles, whose suppression frequencies vary. Amplitude of the responses and overall suppression frequency increase with increased intensity. The frequency required to suppress muscle activity at a given stimulation intensity is not fixed for
each muscle group but, as expected, it varies among the subjects. Figure 4.6 shows a comparison
between the intensity sweeps obtained from two subjects P01 and P08. Both stimulations were
conducted with the stimulation intensity of 95 mA and frequency increased from 2Hz to maximum
bearable limit which is 50 Hz for subject P01 and 80 Hz for subject P08. The results show a big
difference in terms of intensity of the response amplitudes, hence also affecting the suppression
frequency. RH of P01 had much larger response compared to the corresponding muscle of P08.
Nevertheless, suppression—mean RMS below 20% of the initial response—was produced by a
stimulation frequency as low as 25 Hz. On the other hand, although the initial response of RH on
P08 was small, the 20% of this value was not reached until applying a frequency of 80 Hz.
47
Figure 4.6 Comparison of frequency sweeps of subject P01 A) and P08 B) with 95 mA stimulation intensity. Overall summary of the suppression frequencies within measurements per subject are given in
table 4.2. These results clearly suggest that with increasing stimulation intensity, the stimulation
frequency should also be increased to suppress the evoked potentials of lower limbs.
Table 4.2 Suppression frequencies (Hz) of lower leg muscles of all transcutaneous measurement subjects
Subject ID P01 P07 P08
Intensity 70mA 95mA 75mA 90mA 75mA 85mA 95mA
LQ 30 50 5 5 8 10 20
LH 25 50 5 20 10 20 20
LTA 40 50 10 - 8 10 15
LTS 8 20 15 40 8 10 15
RQ 25 25 8 5 8 20 30
RH 8 25 20 8 8 20 30
RTA 30 25 20 40 8 10 15
RTS 50 20 25 40 8 15 15
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In addition to the reduction of the magnitude of the neuromuscular responses, the variability in
size of those responses was also affected by the increase of frequency. An example of this is shown
figure 4.7 which depicts the standard deviations of the RMS values for each stimulation frequency.
It is observed that, in general, the variability on the responses size was more remaked in the
frequency range of 8 to 15 Hz frequency range, and starts decayed with frequencies higher than
20 Hz.
Figure 4.7 Standard deviation of calculated RMS values from subject P08 stimulated with 95 mA stimulation intensity. Each bar represents the standard deviation calculated from each stimulation section. The circle in the middle of the bars represents the mean RMS value of the corresponding section. The values show an increase especially around 8-10 Hz and starts decreasing with 20 Hz or higher frequencies. Variations between the amplitudes of responses within the stimulation sections and how the
suppression occurs with increased frequency can also be seen in figure 4.4. Amplitudes are having
the highest difference with 8 Hz stimulation frequency in general. It should also be recognized that
within the stimulation section, amplitudes show decreasing trend from the beginning of the section
to the end.
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4.2 Epidural Stimulation
The dataset from an early eSCS protocol was retrieved and processed in a similar way to subject
EP1 data who went through two stimulation procedures with two electrode configurations 0-3+
and 3+0-. Figure 4.8 shows an example of the neuromuscular overlapped (N = 8) for different
stimulation intensities (subject EP1 0-3+) to show how the responses are quite similar in terms of
shape and intensity within each stimulation section, while the intensity of the responses increases
with increasing stimulation intensity.
Figure 4.8 Showing adjacent 8 responses of each stimulation section obtained from subject EP1 with 0-3+ electrode configuration. As it can be seen from the plots, EMG responses evoked to the stimulation, show similarity within each stimulation section. The amplitude of the responses shows an increase with increasing stimulation intensity. This increase varies within the muscles. Similar to transcutaneous stimulation, the first step was to calculate the recruitment curve with the
average size of the responses to stimulations at 2.1 Hz, in this case with the electrode configuration
0-3+ (Figure 4.9). On the plotted results quadriceps, hamstrings and adductors need 3 V
stimulation intensity to start giving responses, while TA and TS needed a higher stimulation
intensity (4 V and 5 V) to give significant evoked potentials. Consistent with the transcutaneous
stimulations results, the recruitment of the muscle motor pools by epidural stimulation were also
achieved in an uneven way.
50
Figure 4.9 Recruitment curve, or intensity sweep, of subject EP1 with electrode configuration of 0-3+. Muscles need different stimulation intensities to give considerable evoked potentials, which increase in amplitude with increasing stimulation intensity. In epidural spinal cord stimulation measurements, different electrode configurations were tested
Recruitment curves of these stimulations are plotted in figure 4.10, which compares the results of
two electrode set-up on left leg of the subject. This example shows us that recruitment of the same
motor neurons can differ with the electrode set-up, even though every other parameter kept
constant. Table 4.3 lists the threshold on different muscles per subject.
51
Figure 4.10 Recruitment curves obtained from EP1 with electrode configuration 0-3+ A) and 3-0+ B). All the parameters except electrode placement kept constant, however the results show that the recruitment order and Peak to Peak values of the elicited signals are different. Table 4.3 Response intensities (V) of lower limb muscles of subject EP1 to 2.1 Hz epidural spinal cord stimulation
Subject ID
Muscles EP1 0-3+
EP1 3-0+
LQ 3 3
LA 3 3
LH 3 3
LTA 4 3
LTS 4 3
RQ 3 2
RA 3 2
RH 3 2
RTA 5 3
RTS 5 3
52
After a sustain response of the muscles was succeeded with 2.1 Hz frequency, frequency sweeps
were generated at fixed intensity with gradually increase of frequencies. A behavior similar to the
tSCS is also observed with epidural stimulation. Figure 4.11 shows an example of such
observation. What is different than transcutaneous is, with epidural stimulations the stabilization
period occurring in the beginning of the stimulation section was not that obvious. Yet a generalized
reduction of the responses could still be observed.
Figure 4.11 Frequency Sweeps of leg muscles of the subject EP1 0-3+ with 7 V stimulation intensity. Clear observation of response reduction with increased stimulation frequency can be made. Each color represents a stimulation section with frequency written above. Responses are summarized in Figure 4.12, showing that the reduction trend is present at all
stimulation intensities applied. Plots are supporting the results obtained with transcutaneous
stimulation. Neuromuscular responses evoked by the stimulation decrease with increased
frequency, however this decrease is depending on the intensity that the stimulations are applied. It
can be observed that with increased intensity, suppression frequency also increases. Table 4.4
gives the list of the measurements used in this study and suppression frequencies detected per
stimulation section.
53
Figure 4.12 Frequency sweeps applied on subject EP1 0-3+ with 4, 5, 6 and 7 V stimulation intensity. Plots are depicting the mean RMS values of stimulation sections of the left leg muscles versus applied stimulation frequency. It can be observed that the evoked potentials are going through a reduction with increased stimulation frequency in all muscles, whose suppression frequencies are different. Table 4.4 List of detected suppression frequencies of epidural spinal cord stimulation sections
Subject
ID
EP1 0-3+ EP1 3-0+
Intensity 4V 5V 6V 7V 3V 4V 5V
LQ 16 21 16 21 16 40 21
LA 16 21 31 31 31 40 100
LH 16 21 31 31 21 50 100
LTA 2 50 50 40 21 21 21
LTS 10 21 21 16 16 21 21
RQ 21 21 21 21 21 21 21
RA 21 50 31 40 40 40 100
RH 31 21 31 31 21 21 21
RTA 0 2 16 21 16 50 100
RTS 0 2 16 21 16 16 21
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4.3 Statistical Results
A three-way ANOVA was applied to investigate the effect of intensity, frequency and muscles on
RMS values of individual responses. ANOVA tests were applied to each subject and each
stimulation set up separately due to the differences among the protocols. The results suggest that
all independent parameters have significant effect on the resulted responses (all P values are lower
than significance level α= 0.01). Statistical results obtained from each subject is as follows:
Table 4.5 Three-way ANOVA results Subject Intensity Frequency Muscle
P01WI F(1) = 9972.61, P = .000 F(9) = 3283.72, P = .000 F(7) = 6133.35, P = .000
P07HK F(1) = 529.94, P =.000 F(8) = 421.67, P = .000 F(7) = 453.92, P = .000
P08PS F(1) = 136.55, P = .000 F(8) = 2306.5, P = .000 F(7) = 2924.71, P = .000
EP1 0-3+ F(3) = 11984.7, P = .000 F(7) = 8924.47, P = .000 F(9) = 2039.21, P = .000
EP1 3-0+ F(2) = 16544.54, P = .000 F(8) = 22881.27, P = .000 F(9)=10746.14, P = .000
In order to evaluate the effects of intensity and muscle on suppression frequency, two-way
ANOVA test were applied to epidural and transcutaneous measurements. Detected suppression
frequencies were taken as dependent values while intensity and muscle were the independent ones.
Results of both stimulation techniques suggest that the intensity has a significant effect on
suppression frequency with results of F (4) = 5.02, P = 0.0021 for transcutaneous and F (4) = 5.14,
P = 0.0014 for epidural stimulation. On the other hand, our results suggest that the muscle type
does not have a significant effect on suppression frequency. Values are as follows for
transcutaneous stimulation F (7) = 0.46, P = 0.8576 and for epidural stimulation F (9) = 2.66, P =
0.012.
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5. Discussion
Motor control of the lower limbs is achieved by the complex interaction and regulation—
facilitation and inhibition—of afferent fibers, interneurons and descending drives from the
supraspinal centers. Although all these neurons are often described in separate systems like reflex
pathways and locomotor circuitry, all of them lead to a final common path, which is the
motoneuron (Brownstone & Bui, 2010). The motoneurons are responsible to integrate all the
signals and ultimately initiate the muscle contraction (Baldissera, Hultborn, & Illert, 1981).
When this input is modified by a spinal cord injury, it causes a distortion—reduction or
modification—in the ascending and descending pathways connecting supraspinal centers with the
spinal centers caudal to the lesion, which ultimately modify the inputs to be integrated by the
motoneuron. In many cases, there are fibers preserved and, even though their function has been
compromised, neuropathological (Kakulas & Kaelan, 2015) and neurophysiological (Sherwood,
Dimitrijevic, & Barry McKay, 1992) studies have shown evidences of supraspinal influence
through the injury level via these residual fibers, even in clinically complete SCI individuals. This
residual influence is demonstrated by assessing the volitional activation of spinal inhibitory
function to suppress spinal reflex responsiveness below the lesion, as well as the volitional
activation of motor units in paralyzed legs through reinforcement maneuvers (Milan R.
Various studies have shown cases of augmented function including, initiating stepping-like
movements, enhancing voluntary motor function and augmentation of voluntary locomotor
activity achieved by means of spinal cord stimulation both in complete and incomplete subjects
(Milan R. Dimitrijevic et al., 1984; Hofstoetter et al., 2015; K. Minassian et al., 2004). Possible
56
explanation of this phenomenon is enhancing the excitability of lumbar spinal cord circuits by
application of the tonic input through posterior root afferents and moving up the system to the
threshold needed to fire action potentials hence generating motor outputs in the target muscles.
Figure 5.1 depicts a simplified scheme of this phenomenon. Thanks to the spinal cord stimulation
posterior roots which consists of afferent fibers incoming from muscles, cutaneous tissues and
tendons of legs and hips are depolarized. This depolarization trans-synoptically recruit the spinal
interneurons and motoneurons leaving the spinal cord from specific levels of it (Fig. 5.3) and
innervating the target muscles (K. Minassian et al., 2004) hence resulting in evoked potentials.
Figure 5.1 Spinal cord stimulation provided tonic excitatory input is added up to normally insufficient supraspinal translesional input and the excitability of the central state is moved closer to the system threshold. As a result, action potentials are fired, and motor output is generated (Karen Minassian, McKay, Binder, & Hofstoetter, 2016). The locomotion can only be achieved by the synergetic coordination of all muscles and although
the whole system is interconnected, the activation of each motor pool is independent, as shown in
some reflex studies by reaching out different muscles with changing the stimulation electrode
positions (Krenn et al., 2013). The independence of the activation mechanism of different motor
pools is a special interest since traumatic SCI might end up effecting each motor pool differently.
5.1 Response to Low Frequency Stimulation
Low frequency stimulation mostly activates the reflex pathways, therefore the input from
descending pathways and interneurons are minimized. As a result, observed neuromuscular
responses are the consequences of the afferent activation due to the induced electrical field.
All the posterior root afferents which recruit the motoneurons leaving the spinal cord from specific
levels and innervating the target muscles (K. Minassian et al., 2004) are found close together in
57
the lumbosacral levels (Figure 5.2) and the stimulation electrodes cover this region over the
vertebrae. Yet the results interestingly have shown a huge variability on the responses not only
between subjects (see Fig 4.2) but in the muscle group responses within one subject (see Fig 4.3).
One possible reason for this could be the nonuniform change over the spinal cord through the SCI
which can affect each descending path, hence the conduction of supraspinal input differently.
Therefore, even if the stimulation intensity could be enough to evoke potentials on specific
muscles, it may need to be increased to evoke the potentials on the other ones.
Figure 5.2 Vertebrae and corresponding spinal cord levels are depicted as well as the innervating motoneurons of the lower limb muscles. Stimulation over the lumbosacral vertebrae recruits the motoneurons conducting signals to quadriceps, hamstrings, tibialis anterior and triceps surae (Adapted from (Kendall, Provance, Rodgers, & Romani, 2013) . It should also be noted that the distribution of the applied electric field along the spinal cord is
non-uniform, with differing magnitudes resulting between electrodes (Figure 5.3), which was
shown by different modelling studies (Parazzini et al., 2014) and (Bastos, et al., 2016). Since the
electrical field is directly related to voltage, the influence of the stimulation will vary along the
target regions.
58
Figure 5.3 Electric field magnitude distribution along the spinal cord tested for several electrode configurations and a non-uniform distribution of the electrical field is observed. Color scale on the righthand side is the electric field magnitude in V/m (Bastos, et al., 2016). In this study, transcutaneous spinal cord stimulation and was applied through the placement of the
electrodes over the vertebral levels T11 and L3. As seen in figure 3.2, these electrode placement
covers the lumbosacral segment of the spinal cord, which embeds the afferents innervating the
main lower limb muscles.
Considering the varying electric field distribution along the spinal cord and the spatial difference
of the motor pools controlling different muscles, it can be assumed that the application of constant
stimulation frequency through a fixed electrode position over the spine, recruits the motoneurons
distinctly hence the firing of the action potentials requires different stimulation intensities. This
deduction is supporting the results of our recruitment curves in which the evocation of
neuromuscular responses occurs at stimulations with different intensities (see Fig 4.2).
Furthermore, even if the motor outputs of different muscles start at the same intensity (see Fig
4.3.A), the evolution of them are strikingly different. Growing of the evoked potentials are faster
in some muscles than the others.
Non-uniformity of the recruitment curves within right and left limbs of a single subject and also
among the different subjects (see Fig 4.3) can be explained the asymmetric deformation of the
spinal cord caused by the SCI, which can possibly result in a change of the excitation thresholds
differently (Holsheimer, Barolat, S truijk, & He, 1995).
Epidural spinal cord stimulation recruitment curve outcomes (see Fig. 4.9) are showing similarity
to tSCS results in terms of non-uniformity of the intensities giving rise to evoked potentials among
59
the stimulations. Which is consistent with the idea that both techniques are able to depolarize and
activate common neuronal structures (Hofstoetter, Freundl, Binder, & Minassian, 2018).
In a computer modelling study regarding the epidural spinal cord stimulation of posterior roots
over the lumbosacral region, it was found that there is a strong relation between recruitment order
of the spinal cord and the position of the cathode because the depolarization of the fibers occurred
with lower thresholds when the cathode is placed closer to the entry of the posterior root fibers
into the spinal cord (Rattay et al., 2000), beneath T12 vertebrae. The same principles are also
mentioned in another study conducted by Ladenbauer (Ladenbauer, Minassian, Hofstoetter,
Dimitrijevic, & Rattay, 2010). Decrease in the stimulation intensity to recruit the muscle pools and
the change in the recruitment order (see Fig 4.10), when the polarity of the stimulation is changed
from 0-3+ to 3-0+ in case of our epidural stimulation can be explained by these study findings. As
it can be observed the intensity needed to activate tibialis anterior and triceps surae was lower with
3-0+ electrode configuration, in which the cathode is located more caudally and closer to the entry
of the fibers to the spinal cord. Furthermore, the electric field is stronger over this area where the
muscle pools of H, TA and TS are found, which can be a possible explanation for the higher
amplitudes of the evoked potentials compared to the other configuration.
5.2 Response to High Frequency Stimulation
The stimulation intensity was fixed to the value in which a sustain responses were reached at low-
frequency stimulation and then the frequency was increased step by step. As a result, a decrease
in the motor output was observed. Although the suppression frequency showed variety among the
muscles and the subjects, the general result remained the same for in most of the cases. For constant
stimulation set-up, it was observed that the output did not remain constant and it decayed through
the stimulation sequence (see Fig 4.4). These results are consistent with an early study explaining
the a change of pattern consisting of building up, fluctuation and diminishing of the muscle
responses to middle range of stimulation frequencies applied (M. R. Dimitrijevic & Nathan, 1970).
The alteration of the output obtained in our study is more visible within the 8-15 Hz frequency
range, which corresponds to middle range frequencies mentioned above.
In some studies, it has been observed that low frequency (2.2 Hz) stimulations resulted in
successive responses about constant EMG amplitudes. This is due to the fact that the posterior root
60
afferents are directly depolarized by electrical stimulation and they project directly to
monosynaptic reflex pathways at the lower frequency stimulations (K. Minassian et al., 2004).
Therefore, the role of the interneurons that are involved is significantly lower compared to
increased stimulation rates. This is the reason why the responses to the first three stimulus were
removed in the analyzed datasets, since they show examples similar to single responses rather than
motor behavior, which is the main focus of this work. However, as the stimulation frequency
increases, an inconstant and complex motor output pattern has been recognized. This difference
suggests that the as the stimulation frequency is increased the impact of interneuron are growing
and changing the output (K. Minassian et al., 2007).
The reduction of the neuromuscular responses due to a stimulation frequency increase could be
easily interpreted as a result of the depletion of neurotransmitters in the synapse. However an early
study showed that the a 4cm-displacement of the stimulation to another area could still activate
the motoneurons (M. R. Dimitrijevic & Nathan, 1970), which weakens these argument. At very
high stimulation frequencies, the refractory period could also be part of the suppression mechanism
of the muscle responses, however a few exceptions in our results showed increasing output with
high stimulation frequencies (85 Hz) (see muscle LTS on Fig 4.14). Although the refractory period
might play a role in the suppression, this finding strongly suggest that the inhibitory effect is
mainly driven by a different mechanism. All these interpretations lead us to a conclusion that the
processing of the spinal cord is playing the biggest role through the activation of the interneurons,
whose effect can be excitatory as well as inhibitory. The diminishing of the motor output with
increased stimulation frequency, suggests that the inhibitory effect of the interneurons dominates
the processing of the spinal cord in most of the cases.
5.3 Interaction of Intensity and Frequency on Motor Output
When frequency sweeps applied at different stimulation strengths are compared, the results suggest
that there is a direct relation between stimulation frequency and intensity in order to achieve the
suppression of the motor output (see Fig. 4.3). It has been shown that if the activity is suppressed
at a certain frequency with certain intensity, a further increase of the stimulation strength produces
an increase in muscle activity, and needs a higher frequency to be suppressed again. This statement
has been conducted from most our results including also a few exceptions. However, these
exceptions were not strong enough to affect the statistical outcome significantly.
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Spinal cord stimulation first depolarizes the large diameter afferents (with lower thresholds) and
recruits the motor pools over the lumbosacral spinal cord region. Gradual increase of the
stimulation strength result not only in a broadening of large fiber recruitment rootlets of adjacent
posterior roots (Rattay et al., 2000) but also in recruitment of additional fibers with smaller
diameters to some extent (Rattay et al., 2000; Struijk, Holsheimer, & Boom, 1993). This
simultaneous stimulation of different afferents will excite spinal interneurons by synaptically
evoked depolarization addition to the monosynaptic activation of motoneurons (Guru, Mailis,
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