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Looking beyond the motor cortex : examining the potential of the primary sensory cortex as a target for… Brodie, Sonia Mae 2013

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LOOKING BEYOND THE MOTOR CORTEX:  EXAMINING THE POTENTIAL OF THE PRIMARY SENSORY CORTEX AS A TARGET FOR REPETITIVE TRANSCRANIAL MAGNETIC STIMULATION TO ENHANCE RECOVERY AFTER STROKE by Sonia Mae Brodie BSc Honors Psychology, University of Alberta, 2010 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Neuroscience) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  December 2013 ? Sonia Mae Brodie, 2013 ii Abstract Stroke is the leading cause of chronic adult disability, and standard post-stroke therapies may not be sufficient for individuals to reach their full recovery potential. When paired with skilled motor practice, non-invasive brain stimulation techniques such as repetitive transcranial magnetic stimulation (rTMS) may enhance motor recovery by transiently modulating cortical excitability, effectively priming the brain to facilitate mechanisms of motor learning. Depending on the pulse frequency, rTMS may be used to increase cortical excitability in the damaged hemisphere, or decrease it in the undamaged hemisphere, with the goal of re-establishing a normal interhemispheric balance. While theoretically promising, the majority of studies considering the effects of rTMS over the primary motor cortex (M1) have shown relatively small effect sizes and high inter-individual variability. Improved effect sizes may be produced by 1) finding the optimal cortical target for stimulation, rather than defaulting to M1, and 2) choosing an appropriate sample that will optimally benefit from the intervention. In the following thesis, we will explore the potential of the primary sensory cortex (S1) as an alternative target for rTMS intervention, and the anatomical and physiological variables that may help to identify who may best benefit from this intervention. First, we describe a randomized, single blind experiment comparing the impact of active versus sham rTMS over S1 paired with practice of a skilled visuomotor reaching task in individuals with chronic stroke. Second, we describe a retrospective analysis of the participants from the first experiment, to determine whether individual differences in morphology of the underlying sensory cortex might be predictive of rTMS responsiveness. Third, we describe an exploratory study using a paired median nerve somatosensory evoked potential paradigm using electroencephalography in healthy individuals, to elucidate the neurophysiological mechanism of interhemispheric inhibition between S1s. We conclude that S1 should be considered as a viable target for future rTMS trials as an adjunct therapy to rehabilitation after stroke. iii Preface This thesis contains three experiments that have been conducted by the candidate Sonia M. Brodie, under the supervision of Dr. Lara Boyd, with assistance from Dr?s. Michael Borich and Sean Meehan. The collection, analysis, and documentation of all experiments were primarily the work of the candidate. All projects and associated methods were approved by the University of British Columbia?s Research Ethics Board (certificate # H09-03000 for Chapters 2 & 3; # H12-03611 for Chapter 4). A version of Chapter 2 has been submitted for publication [Brodie, SM., Meehan, SK., Borich, MR., Boyd, LA. 5 Hz repetitive transcranial magnetic stimulation over the ipsilesional sensory cortex enhances motor learning after stroke. (In review)].  This work was supported by the Canadian Institutes of Health Research [MOP-106651 to L.A.B.]. Support was also provided to L.A.B. by the Canada Research Chairs and the Michael Smith Foundation for Health Research. The Canadian Institutes of Health Research and Michael Smith Foundation for Health Research provided support for S.K.M. during the initial phases of this work.  The Heart and Stroke Foundation of Canada provided support to M.R.B. The authors would like to acknowledge Katharine Cheung and Dr. Nicole Acerra for assistance during portions of the data collection. The authors would also like to acknowledge Dr. Rick White for his statistical consultation.  A version of Chapter 3 will be submitted for publication [Brodie, SM., Borich, MR., Boyd, LA. Impact of 5Hz rTMS over the primary sensory cortex is related to white matter volume in chronic stroke. (In preparation).] A version of Chapter 4 will be submitted for publication [Brodie, SM., Boyd, LA. Exploring the specific time course of interhemispheric inhibition between the human primary sensory cortices. (In preparation).]  iv Table of Contents Abstract ............................................................................................................................................. iiPreface .............................................................................................................................................. iiiTable of Contents ............................................................................................................................ ivList of Tables ................................................................................................................................. viiiList of Figures .................................................................................................................................. ixList of Abbreviations ....................................................................................................................... . xAcknowledgements ......................................................................................................................... xiChapter  1: Introduction and Purpose ........................................................................................... 11.1! Introduction ........................................................................................................................... 11.2! Motivation, Aims, and Hypotheses ...................................................................................... 61.3! Rationale ............................................................................................................................... 71.4! Significance ........................................................................................................................... 8Chapter  2: 5Hz Repetitive Transcranial Magnetic Stimulation Over the Ipsilesional Sensory Cortex Enhances Motor Learning After Stroke ........................................................................... 92.1! Abstract ................................................................................................................................. 92.2! Introduction ......................................................................................................................... 102.3! Methods............................................................................................................................... 122.3.1! Participants ................................................................................................................... 122.3.2! Procedure ..................................................................................................................... 132.3.3! Serial Targeting Task ................................................................................................... 142.3.4! Transcranial Magnetic Stimulation (TMS) .................................................................. 162.3.5! Cutaneous Somatosensation ......................................................................................... 19v 2.3.6! Motor Function ............................................................................................................ 192.3.7! Statistical Analysis ....................................................................................................... 202.4! Results ................................................................................................................................. 212.4.1! Baseline Group Characteristics .................................................................................... 212.4.2! Motor Learning ............................................................................................................ 212.4.3! Cutaneous Somatosensation ......................................................................................... 23!2.4.4! Motor Function ............................................................................................................ 232.4.5! Motor Cortex Excitability ............................................................................................ 232.5! Discussion ........................................................................................................................... 252.6! Conclusion .......................................................................................................................... 282.7! Bridging Summary .............................................................................................................. 28Chapter  3: Impact of 5Hz rTMS Over the Primary Sensory Cortex is Related to White  Matter Volume in Individuals with Chronic Stroke ................................................................... 303.1! Abstract ............................................................................................................................... 303.2! Introduction ......................................................................................................................... 313.3! Methods............................................................................................................................... 343.3.1! Serial Targeting Task (STT) ........................................................................................ 343.3.2! Transcranial Magnetic Stimulation (TMS) .................................................................. 363.3.3! MRI Acquisition and Analysis ..................................................................................... 373.3.4! Statistical Analysis ....................................................................................................... 393.4! Results ................................................................................................................................. 413.4.1! Baseline Measures ........................................................................................................ 413.4.2! Correlation Analyses .................................................................................................... 41vi 3.4.3! Regression Analyses .................................................................................................... 443.5! Discussion ........................................................................................................................... 453.6! Conclusion .......................................................................................................................... 473.7! Bridging Summary .............................................................................................................. 48Chapter  4: Exploring the Specific Time Course of Interhemispheric Inhibition Between the Human Primary Sensory Cortices ............................................................................................... 494.1! Abstract ............................................................................................................................... 494.2! Introduction ......................................................................................................................... 504.3! Methods............................................................................................................................... 544.3.1! Experimental Procedure ............................................................................................... 544.3.2! Paired Median Nerve Somatosensory Evoked Potential (PMNSEP) Paradigm .......... 554.3.3! Statistical Analyses ...................................................................................................... 594.4! Results ................................................................................................................................. 604.5! Discussion ........................................................................................................................... 634.6! Conclusion .......................................................................................................................... 70Chapter  5: Conclusions and General Discussion ....................................................................... 715.1! Introduction ......................................................................................................................... 715.2! Summary of Findings .......................................................................................................... 715.2.1! High Frequency rTMS Over IL-S1 .............................................................................. 715.2.2! Morphological Predictors of rTMS Response ............................................................. 725.2.3! Mechanism of Somatosensory Interhemispheric Inhibition ........................................ 735.3! Synopsis .............................................................................................................................. 745.4! Limitations .......................................................................................................................... 74vii 5.5! Future Directions ................................................................................................................ 76Appendices ...................................................................................................................................... 93Appendix A Arm Fugl-Meyer Assessment .................................................................................. 93Appendix B Montreal Cognitive Assessment (MoCA) ............................................................... 96Appendix C Transcranial Magnetic Stimulation (TMS) Screening Form .................................. 97!Appendix D MRI Screening Form .............................................................................................. 98Appendix E Box and Blocks Test of Manual Dexterity ............................................................ 100Appendix F Adapted Edinburgh Inventory for the Assessment of Handedness ....................... 101References....................................................................................................................................... 78 viii List of Tables Table 2-1: Participant demographics ............................................................................................ 13Table 2-2: Participant lesion descriptions ..................................................................................... 18Table 3-1: Baseline group differences ........................................................................................... 42Table 3-3: Regression values for the IL-S1 and IL-M1 models .................................................... 44Table 4-1: Mean peak-to-peak SEP amplitudes ? SD ................................................................... 60ix List of Figures Figure 2-1: Experimental overview.............................................................................................. 15Figure 2-2: STT mean performance values and change scores................................................. 22Figure 2-3: Individual thresholds for 2-point discrimination at baseline and retention......... 23Figure 2-4: Individual resting motor threshold values at baseline and retention ................... 24Figure 3-1: . Experimental overview............................................................................................. 35Figure 3-2: Changes in response time from baseline to retention............................................. 36Figure 3-3: Representative image of automated segmentation and parcellation .................... 39Figure 3-4: Correlations between each volume of interest and response time  change........... 43Figure 4-2: The paired median nerve somatosensory evoNed potentiaO paradigm.................. 56Figure 4-3: Custom 29 electrode set-up........................................................................................ 57Figure 4-4: Peak-to-peak amplitudes were extracted manually as shown................................ 59Figure 4-5: Representative SEP traces recorded from a single subject.................................... 61Figure 4-6: Mean peak-to-peak amplitudes of the early cortical SEP components ................ 62Figure 4-7: Proposed mechanism for interhemispheric inhibition............................................ 65Figure 4-8: Possible transcallosal pathways for interhemispheric inhibition.......................... 67Figure 1-1: After stroke, increased inhibition on the ipsilesional cortex.................................... 2 Figure 1-2: The primary sensory cortex in parallel to the primary motor cortex..................... 6Figure 4-1: The primary sensory cortex is divided into 4 regions............................................. 52x List of Abbreviations 2PD: 2-point discrimination test APB: Abductor pollicis brevis BBT: Box and Blocks test CL: Contralesional / Undamaged hemisphere CS: Conditioning stimulus cTBS: Continuous theta-burst stimulation ECR: Extensor carpi radialis EEG: Electroencephalography EMG: Electromyography FM: Fugl Meyer test of upper extremity  fMRI: Functional magnetic resonance imaging GM: Grey matter IHI: Interhemispheric inhibition IL: Ipsilesional / Damaged hemisphere M1: Primary motor cortex/Precentral gyrus MEP: Motor evoked potential MN: Median nerve MoCA: Montreal cognitive assessment MRI: Magnetic resonance imaging PMNSEP: Paired median nerve somatosensory evoked potential RMT: Resting motor threshold RT: Response time (= reaction time + movement time) rTMS: Repetitive transcranial magnetic stimulation S1: Primary somatosensory cortex/Postcentral gyrus SD: Standard deviation SEM: Standard error of the mean SEP: Sensory evoked potential STT: Serial targeting task TCI: Transcallosal inhibition TMS: Transcranial magnetic stimulation TS: Test stimulus WM: White matter WMFT: Wolf motor function testxi Acknowledgements I would like to thank each quirky member of my lab, the ?BBL family?, for helping to create a fantastic, team-oriented work environment. In addition to helping out with this project and offering me constructive feedback, they each played a unique role in making my experience in the Brain Behavior Lab unforgettable. I offer special thanks to Dr. Lara Boyd for her supervision throughout this project. Her persistent questions, open mind, and genuine enthusiasm for her work are truly inspiring qualities. I also thank Dr. Michael Borich, my unofficial second supervisor, who was always willing to take the time to answer my questions, (often at length). He has all the makings of an outstanding principle investigator. I would also like to thank my committee members, Dr.s Sean Meehan, Romeo Chua, and Alex MacKay for their guidance and insight throughout this project.  Finally, I am forever grateful to my ?extracurricular? support, namely my partner, Fraser, and my family. Their unconditional love and constant encouragement has supported me immensely.   1 Chapter  1: Introduction and Purpose 1.1 Introduction Each year, approximately 50,000 Canadians are affected by stroke 1. The majority of those who survive will experience motor deficits 2, and 55-75% of them will be left with chronic functional limitations and reduced quality of life 3. As a result, stroke is currently the leading cause of chronic adult disability. Standard post-stroke rehabilitation, including physical and/or occupational therapy, is mainly focused on the sub-acute phase. During this time, the damaged brain can undergo dramatic neuroplastic changes 4, and the rate of motor recovery can be remarkably high for some individuals 5. However, the general consensus is that by 6 months, the majority of stroke patients will have plateaued in their recovery 5-7, and whatever impairment they may still have at this point is considered chronic. Despite their persistent neurological impairments, individuals with chronic stroke are still capable of learning new motor skills 8-10. Motor learning is considered to be the basis for neurorehabilitation 11, which promotes re-learning of lost motor abilities. Therefore it is plausible that individuals with ?chronic? motor impairments may still have some potential for further recovery. Unfortunately, the learning process can be very strenuous and time-consuming, requiring intensive repetitive practice 12. Essentially, the dose of treatment required to induce lasting behavioral change is not feasible in today?s healthcare setting. This has led to an interest in the development of adjunct therapies that may be paired with standard rehabilitation procedures to boost motor learning and enhance recovery. 2 An example of a potential adjunct therapy is transcranial magnetic stimulation (TMS). TMS is a safe, painless, and non-invasive technique that, by inducing a localized magnetic field at the surface of the skull, can alter the electrical activity of the underlying brain tissue by electromagnetic induction 13. A single TMS pulse applied over the skull induces a localized electrical field within the cortex 14 that can depolarize a subsection of neurons, depending on the geometry and orientation of the magnetic coil. When pulses are applied repetitively (rTMS) at different frequencies, cortical excitability and inhibition can be modulated 15,16. Specifically, high frequency (>5Hz) rTMS has been shown to increase cortical excitability 17, whereas low frequency (<1Hz) rTMS decreases it 18,19. These changes in excitability tend to outlast the period of stimulation for several minutes, depending on stimulation parameters 17,18,20-22. The ability to modulate cortical excitability/inhibition in the brain non-invasively is particularly applicable to individuals with neurological damage, such as stroke. Research has shown that, following stroke, the cortical excitability of the damaged (ipsilesional; IL) hemisphere is decreased 23, whereas the excitability of the unaffected (contralesional; CL) is increased. This is thought to occur due to a shift in interhemispheric inhibition (IHI). In the healthy brain, IHI is mediated by the corpus callosum ? a large bundle of more than 200 million axons divided into functionally and anatomically Figure 1-1: After stroke, increased inhibition is placed on the ipsilesional cortex through transcallosal inhibition.3 distinct areas that connect homologous regions of each hemisphere 24. While the specific function of the corpus callosum depends on many factors (including neurotransmitters, receptors, and interneurons) 25, overall it regulates lateralization of neural activity, such that activation in one hemisphere results in a mutual deactivation in the other 26. This IHI is increased during simple unimanual tasks, whereas it is decreased for complex bimanual tasks that require hemispheric cooperation 27,28. In individuals with chronic stroke, the IL hemisphere may not be able to inhibit the CL hemisphere as effectively 23,29. Meanwhile, the CL hemisphere continues to inhibit the IL hemisphere, possibly to an even greater degree, as it has been released from inhibition from the IL side. As a result, the laterality of the sensorimotor cortex is abnormally shifted 30-32 (Figure 1-1). These changes interfere with neuroplasticity in the IL hemisphere 33, and contribute to functional motor impairment after stroke 34-36.  The pattern of altered cortical excitability described above offers two targets for non-invasive stimulation.  Repetitive TMS may be used to excite the over-inhibited IL hemisphere, or alternatively to inhibit the over-excited CL hemisphere; theoretically, either approach could re-establish the balance of IHI after stroke 37,38. Repetitive TMS delivered in isolation has been shown to induce some functional improvements in individuals with chronic stroke 39-43. However, overall the benefits are short lasting, small, and inconsistent between individuals 44, which limits its clinical applicability. In order to induce longer lasting changes in motor function, some form of motor learning needs to occur. Basic motor learning is based on the Hebbian principle that ?units that fire together wire together?. In other words, recruiting the same functional network repetitively during practice of a motor skill will enhance the efficiency of that network, thereby making it easier to recruit during future performances of the same skill. This process may occur by 4  strengthening existing neural pathways or by developing new connections through neuroplasticity 45. In theory, by increasing the excitability of a cortical area, rTMS increases the likelihood that the neural population stimulated will fire action potentials. This explains its reported short-term behavioral benefits, particularly in individuals with damaged motor networks. However, longer lasting benefits should be observed when the application of rTMS is paired with repetitive motor training 46.  Indeed, converging evidence suggests that motor learning can effectively be modulated by rTMS in healthy individuals 47-51, and in individuals with acute 52 and chronic 53,54 stroke. However, recently two randomized, placebo-controlled clinical trials were published that challenged the value of rTMS as a clinical tool 55,56.    Seniow and colleagues (2012) paired 30 minutes of active low frequency (1Hz) rTMS or sham stimulation applied over the CL primary motor cortex (CL-M1) with 45 minutes of motor training 5 days/week for 3 weeks in 40 individuals in the subacute phase of stroke (3 months post). In their study, motor training consisted of a session of physiotherapy, including exercises with the affected hand, gait training, and practice of activities of daily living. These sessions were not controlled for level of difficult or type of exercise. Results revealed a lack of statistically significant differences between the experimental and control groups, and the authors conclude rTMS had an imprecise if any impact on improvement 55. Talelli and colleagues (2012) used theta burst stimulation (TBS), a variant of rTMS, at either excitatory or inhibitory frequencies over the IL and CL-M1, respectively, in 41 individuals with chronic (>1 year post) stroke. Each active stimulation group was compared to a group receiving sham stimulation. Similar to the study by Seniow et al. (2012) 55, TBS was paired with 5  a session of physical therapy 56. In this case, however, the intervention was focused on the hemiparetic arm, and intensity was held consistent, independent of individual differences in functional ability. Nevertheless, the authors concluded that: ?TBS did not [significantly] augment the gains from a retraining protocol for the upper limb? 56.  There are several factors that may be contributing to these two reports of negative results. First, technical limitations include the lack of a standardized stimulation location within and across sessions, and the use of different stimulation parameters between studies. Another issue is that neither study employed a well-controlled motor learning task. Studies of neuroplasticity in animal models have shown that simple repetitive movements do not induce plastic changes 57 in the same way as skilled learning does in humans 46,58. In fact Boyd et al. (2010) showed that simply increasing hemiparetic arm use did not induce motor learning or neuroplastic change in individuals with chronic stroke, whereas skilled motor practice both led to motor learning and significantly altered patterns of brain activity 8. As a counter argument, improvement on a specific learned motor task does not necessarily translate to improvements in general motor function 56, and a session of individualized physical therapy may be more clinically relevant. Despite their limitations, studies by Talleli et al (2012) 56 and Seinow et al. (2012) 55 aptly point out that the effects of rTMS are variable, and many issues need to be addressed before rTMS may be applied in a clinical setting.  One potential issue when considering past rTMS literature is that it has been almost exclusively focused on the primary motor cortex. M1 is a convenient target for stimulation, because its corticospinal output can be conveniently visualized and measured using electromyography (EMG). However, the production of voluntary movement involves a complex network of cortical activity much broader than M1 59-62. Furthermore, changes in brain activation 6 after stroke are not limited to M1 alone 63-65. Given the complexities of the sensorimotor network, it is possible that considering cortical targets beyond M1 for rTMS studies may be beneficial. Running in parallel to M1 on the lateral surface of each hemisphere, the primary sensory cortex (S1) also plays an integral role in the production of coordinated voluntary movements 66 and the acquisition of new motor skills 67 (Figure 1-2). Both M1 and S1 are organized somatotopically, and their activity is heavily interconnected 68. Post-stroke somatosensory deficits are common 69-71, and are associated with impaired motor control 72-74. S1 also possesses a high capacity for plastic change 75,76, making it a promising target for therapeutic interventions such as rTMS. However, studies examining the effects of rTMS over S1 are relatively scarce.  1.2 Motivation, Aims, and Hypotheses The primary motivation for this thesis was to explore whether S1 may serve as an alternative target for rTMS + motor learning interventions in individuals with chronic stroke. There were three major aims: Aim 1 was to measure the impact of high frequency rTMS applied over IL-S1 paired with motor practice on motor learning in individuals with chronic stroke. We also asked whether such an intervention would result in improved cutaneous somatosensation, and whether the benefits might generalize to improved motor function of the hemiparetic arm. We hypothesized Figure 1-2: The primary sensory cortex (S1) runs in parallel to the primary motor cortex (M1) on the lateral surface of each hemisphere.7 that active 5Hz stimulation over IL-S1 paired with practice would significantly enhance motor learning, somatosensation, and general motor function.  This experiment is described in Chapter 2. Aim 2 was to retrospectively explore whether the effectiveness of rTMS applied over S1 might be related to the morphology of the underlying cortex. We hypothesized that individuals with a greater neural reserve, that is, larger volume of grey and white matter in IL-S1, would have a larger response to the active 5Hz rTMS intervention described in Aim 1.  This experiment will be described in Chapter 3. Aim 3 was to take a closer look at the neurophysiological mechanism of interhemispheric inhibition between S1s using electroencephalography, to determine if it can be reliably measured in healthy individuals.  We hypothesized that a paired median nerve somatosensory evoked potential paradigm could be used to demonstrate direct transcallosal S1 inhibition.This experiment will be described in Chapter 4. 1.3 Rationale The use of rTMS as an adjunct therapy to standard neurorehabilitation techniques to enhance motor recovery after stroke is theoretically promising. However, thus far, results of clinical rTMS trials have been underwhelming. Improved effect sizes may be produced by 1) finding the optimal cortical target for stimulation, rather than defaulting to M1, and 2) choosing an appropriate sample that will optimally benefit from the intervention. The following experiments contribute to developing an understanding of the effects of rTMS over S1 paired with motor practice, and of the anatomical and physiological variables that may help to identify who may best benefit from this intervention. 8  1.4 Significance Lasting sensorimotor disabilities associated with chronic stroke are detrimental not only on an individual level, but also in terms of the significant costs to the healthcare system and society. An estimated $3.6 billion per year has been attributed to the costs of stroke to the Canadian economy, including medical services, lost wages and decreased productivity 77. Any intervention that may diminish such an impact would be valuable to all parties involved. Thus, the development of non-invasive brain stimulation techniques as adjunct therapies to conventional treatment will have benefits not only for stroke survivors, but for many other neurological conditions as well.  9 Chapter  2: 5Hz Repetitive Transcranial Magnetic Stimulation Over the Ipsilesional Sensory Cortex Enhances Motor Learning After Stroke 2.1  Abstract Sensory feedback is critical for motor learning, and thus to neurorehabilitation after stroke. Whether enhancing sensory feedback by applying excitatory repetitive transcranial magnetic stimulation (rTMS) over the ipsilesional primary sensory cortex (IL-S1) might enhance motor learning in chronic stroke has yet to be investigated. The present study investigated the effects of 5 Hz rTMS over IL-S1 paired with skilled motor practice on motor learning, hemiparetic cutaneous somatosensation, and motor function. Individuals with unilateral chronic stroke were pseudo-randomly divided into either Active or Sham 5 Hz rTMS groups (n=11/group). Following stimulation, both groups practiced a Serial Tracking Task (STT) with the hemiparetic arm; this was repeated for 5 days. Performance on the STT was quantified by response time, peak velocity, and cumulative distance tracked at baseline, during the 5 days of practice, and at a no-rTMS retention test. Cutaneous somatosensation was measured using two-point discrimination. Standardized sensorimotor tests were performed to assess whether the effects might generalize to impact hemiparetic arm function. The active 5Hz rTMS + training group demonstrated significantly greater improvements in STT performance [response time (F1,286.04=13.016, p<0.0005), peak velocity (F1,285.95=4.111, p=0.044), and cumulative distance (F1,285.92=4.076, p=0.044)] and cutaneous somatosensation (F1,21.15=8.793, p=0.007) across all sessions compared to the sham rTMS + training group. Measures of upper extremity motor function were not significantly different for either group. Our preliminary results suggest that, when paired with motor practice, 5Hz rTMS over IL-S1 enhances motor learning related change in individuals with chronic stroke, potentially as a consequence of improved cutaneous somatosensation, however no improvement in general upper extremity function was observed. 10  2.2 Introduction Motor recovery typically plateaus by 6 months after stroke 5, leaving 55%-75% of individuals with chronic functional impairments of the hemiparetic arm 78. Despite persistent neurological deficits after stroke, the capacity for motor learning persists 8-10. This has led to an interest in adjunct interventions to positively augment motor learning and further enhance functional recovery in chronic stroke.  Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive technique used to modulate local cortical excitability in a frequency-dependent manner 79, for a period of time that outlasts the duration of stimulation 80. Immediately following stimulation, the aftereffects may be capitalized on by pairing it with skilled motor practice to promote use-dependent neuroplastic change 81. As such, rTMS is a promising adjunct therapy for enhancing the sensorimotor benefits of motor skill practice. Past work has primarily considered the application of rTMS over the primary motor cortex (M1) in individuals with stroke. However, to date findings have been inconclusive, both when rTMS is delivered in isolation 41,42,82, and when it is paired with rehabilitation 55,56. Inconsistent results may stem from a number of factors, including non-standardized stimulation location within and across experimental sessions, a failure to pair rTMS with a well-controlled motor learning task, and an exclusive focus on the effects of rTMS on the descending motor system. Though often overlooked, the ascending somatosensory system also plays a crucial role in the acquisition of new motor skills 67. Early animal studies demonstrated that disrupting somatosensory feedback by selectively ablating the primary sensory cortex (S1) prevents motor learning 83,84. Similarly in humans, we have observed that disrupting somatosensation by applying inhibitory 1 Hz rTMS over S1 in healthy individuals prior to skilled motor practice 11  decreases motor skill acquisition 51. Further, we have shown that greater proprioceptive deficit predicts less motor learning related change after stroke 10. On the other hand, stimulation of the somatosensory system may be used to enhance motor learning. Electrophysiological studies using in vivo animal models have demonstrated that long-term potentiation could be induced in M1 pyramidal neurons using tetanic stimulation of S1, via reciprocal cortico-cortical afferents 85,86. In humans, peripheral somatosensory stimulation has been shown to induce cortical reorganization of M1 87, and when paired with motor practice, to enhance motor learning in individuals with chronic stroke 88.  These findings have led to the hypothesis that modulating the excitability of the somatosensory cortex may influence motor learning. More specifically, that increasing the excitability of S1 prior to motor practice may potentiate the formation and/or strengthening of sensorimotor connections critical for the development of lasting changes in motor performance. The ability to directly stimulate S1 in humans using rTMS, however, has not been widely explored. High frequency (5Hz) rTMS applied over S1 in healthy individuals induces sustained increases in cortical excitability as measured by sensory evoked potentials 89. In addition, preliminary results from our group suggest that when paired with skilled motor practice, continuous theta-burst stimulation (cTBS), an inhibitory variant of rTMS, applied over contralesional S1 (CL-S1) enhances aspects of motor learning in individuals with chronic stroke 54. Yet the effect of pairing excitatory rTMS over ipsilesional S1 (IL-S1) with skilled motor practice in individuals with in chronic stroke has yet to be investigated.  The primary objective of the current study was to determine whether 5 Hz rTMS over IL-S1 paired with skilled motor practice would result in improvements in motor learning compared to skilled motor practice paired with sham stimulation in individuals with chronic stroke. In 12  addition, we examined whether 5 Hz rTMS over IL-S1 was associated with persistent increases in cutaneous somatosensation of the hemiparetic hand, and if the stimulation effects would generalize to alter motor function of the hemiparetic arm.  2.3 Methods 2.3.1 Participants Fifteen individuals (4 females, mean age: 66.2 years) with first time, chronic stroke (>6 months post) were recruited from the local community (Table 2-1). Exclusion criteria included: (1) significant cognitive impairment (<20 on the Montreal Cognitive Assessment (MoCA)) 90, (2) severe upper extremity impairment (Fugl-Meyer (FM) score of <15 91), or (3) contraindication to TMS 92.  The research ethics board of the University of British Columbia approved all procedures. Informed, written consent was obtained from all participants according to the Declaration of Helsinki.  Participants were pseudo-randomized into either the Active (5 Hz) or Sham rTMS groups, using a custom software to evenly distribute age, gender, and level of physical impairment (FM score) 91.  Given that FM scores stabilize by 90 days post-stroke 6, we employed this measure to index baseline levels of motor impairment. Each individual was na?ve to group assignment. After a minimum washout period of 4 weeks 42,93, each individual was invited back to participate in the study a second time in the opposite group. However, due to experimental mortality only 7 of the 15 were able to return (6 Active -> Sham, 1 Sham -> Active), while 8 individuals participated only once (4 Active, 4 Sham). Thus, in total 11 individuals were assigned to each group.  13 Table 2-1:  Participant demographics [A = active group; S = sham group. M = male; F = female. R = right; L = left.] Divided cells indicate first and second time participating, respectively.  Note: No MRI was obtained for subject 11 due to a contraindication. 2.3.2 Procedure The experiment was conducted over seven sessions, each separated by no more than 3 days (Figure 2-1 A). On Day 1, one block of a Serial Targeting Task (STT) using the hemiparetic limb, 2-point discrimination (2PD), an abbreviated version of the Wolf-Motor Function Test (WMFT) 94,95, the Box and Block Test of manual dexterity (BBT) 96, and resting motor threshold (RMT) were assessed. On Days 2-6 participants received rTMS prior to completing six blocks (72 trials/block) of the STT. One group (Active) received 5 Hz rTMS over IL-S1. The other group (Sham) received sham stimulation that looked and sounded like active 5 14  Hz rTMS but did not induce a current. The interval between stimulation and initiation of motor practice was typically less than 5 minutes. To assess changes in motor learning, as well as cutaneous somatosensation, motor function, and cortical excitability, a no-rTMS delayed retention test was performed on Day 7. Similar to Day 1, this consisted of one block of the STT, 2-PD, the abbreviated WMFT, the BBT, and RMT assessment. 2.3.3 Serial Targeting Task Motor learning was assessed using a goal-directed, visuomotor task, the Serial Targeting Task (STT) 54 (Figure 2-1 C) Participants were seated in front of a computer monitor, holding a wireless mouse (Microsoft Wheel Mouse) in a custom frame with their hemiparetic hand. The goal was to move the cursor between sequentially appearing 28mm diameter targets in one of nine possible locations as quickly and accurately as possible. One target was in the center of the screen, and the other eight formed an equidistant circular array at a 96mm radius; the tangent distance between the azimuth locations was 75mm. Only one target was visible at any given time; to initiate the appearance of the next target, participants were required to hold the cursor within the current target for 500ms. After a 500ms inter-stimulus interval, the next target appeared. Vision of the hemiparetic hand was blocked to isolate the specific effects of somatosensation from visual feedback on motor performance 51. Cursor position was sampled at 200Hz, according to the Cartesian pixel coordinates (Labview v.8.1; National Instruments Co.), and then converted to distance offline by calculating the tangent between each subsequently sampled X, Y pixel coordinate. Pixel distance was converted to mm according to screen resolution (1280 ! 1050) and display size (42.25 mm ! 34.65 mm) giving a conversion factor of 3.3 pixels/mm. The resulting magnitude by time waveform was low-pass filtered at 5 Hz.  15 Figure 2-1:  (A) Experimental overview. At the baseline session on day 1 STT performance was assessed along with RMT, 2PD, WMFT and Box & Blocks performance. 5 sessions of rTMS paired with STT practice were completed on separate days (days 2-6). A delayed retention test designed to assess motor learning was administered on a separate day 7; all baseline measures were re-assessed.  (B) Example of target locations in BrainSightTM for M1 and S1.  (C) Schematic of the experimental motor learning task, the STT, showing the adapted mouse, a sample progression of targets and illustration of a path of movements between 2 targets.   [STT = Serial Tracking Task; RMT = Resting Motor Threshold; 2PD = 2 Point Discrimination; WMFT = Wolf Motor Function Test; rTMS = repetitive Transcranial Magnetic Stimulation.] 16  Each block of STT practice contained nine alternating repetitions of 8 element sequences (5 random, 4 repeated). Random sequences assessed changes in non-specific motor control, whereas repeated sequences allowed the evaluation of these effects on implicit motor sequence learning 97.  For uniformity of task difficulty, each participant practiced the same set of trials. For the 7 individuals who participated twice, each sequence was reversed; this enabled practice of a novel sequence of equal difficulty and prevented practice from the first part of the crossover to influence performance in the second.  Motor performance was evaluated at baseline, during practice days, and at retention. Three primary variables were extracted using custom Labview software: (1) Response Time (time from target appearance to the presentation of the next target, corrected for the 500ms stationary period and the 500ms inter-target interval), (2) Peak Velocity (maximum velocity reached during the initial ballistic component of the movement), and (3) Cumulative Distance (total distance in mm that the participant?s cursor travelled). For each variable, the average of the 8 elements within each sequence was derived. Sequences within each block were then averaged according to type (random or repeated). 2.3.4 Transcranial Magnetic Stimulation (TMS) Prior to the beginning of the experiment, a high resolution anatomical MRI (TR = 12.4ms, TE = 5.4ms, flip angle " = 8?, FOV = 256 mm, 170 slices, 1 mm thickness) was obtained for each participant, except for one individual with a contraindication to MRI. Image acquisition was conducted at the UBC MRI Research Centre on a Philips Achieva 3.0T whole body MRI scanner (Phillips Healthcare, Andover, MD) using an eight-channel sensitivity encoding head coil (SENSE factor=2.4) and parallel imaging. MRIcron software 98  was used to trace lesion volumes for each individual, and AFNI software 99 was used to locate the centroid of 17  each stroke lesion (Table 2-2). The anatomical images were imported into BrainSightTM TMS neuronavigation software [v2.0] for stereotactic guidance during rTMS (Figure 2-1 B). The MNII52 standard brain template was used for the one individual who had no MRI scan. Marking each trajectory in BrainSightTM ensured consistency in the application of stimulation both within and across sessions.  Individuals were seated in a reclined chair and instructed to keep their arms at rest. Surface electromyography (EMG) was recorded from the extensor carpi radialis (ECR) muscles. EMG activity was visually inspected online by two experimenters to ensure that the recording was not contaminated by background muscle activity. Single pulses were applied over the hand knob of M1 with the coil oriented tangentially to the scalp, and the handle at 45# to the midline in a posterior-lateral orientation. Motor evoked potentials (MEPs) were elicited at suprathreshold intensity in order to locate the ECR ?hotspot? in M1. RMT was then defined as percent stimulator output to produce a MEP of at least 50$V peak-to-peak, in five out of ten trials, respectively 100. On Days 2-6, 5Hz active or sham rTMS was applied over IL-S1 prior to STT practice. A 70-mm figure-of-eight air-cooled coil connected to a Magstim Super Rapid stimulator (Magstim Company, Ltd., Wales, U.K.) was used to deliver biphasic stimulation that produces a current flow in a posterior-anterior, then anterior-posterior direction, with a pulse width of 400$s. The TMS coil delivers stimulation to a relatively focal point of the cortex 14,100 specific enough to target specific areas of the cortex independently 101,102. S1 stimulation was delivered ~2cm posterior to the M1 ECR ?hotspot? 103,104 , directly over the crown of the postcentral gyrus using the T1 scan to guide placement (Figure 2-1 B) 51,54. Prior to administering rTMS, single 18 suprathreshold pulses, at ~110% of RMT were used to verify isolation of S1 from M1, as evidenced by a lack of MEP when S1 was stimulated above RMT 105. Table 2-2:  Participant lesion descriptions 19 The active rTMS protocol consisted of 24 trains of 5 Hz pulses at an intensity of 90% RMT for 10 seconds, with 5 seconds rest in between (1200 pulses in total). This stimulation protocol was selected based on our past work considering the effect of stimulation over the dorsal premotor cortex 50,106, and falls within safely defined rTMS limits 92. The Sham group underwent the identical procedure using a custom sham coil (Magstim Company, Ltd., Wales, U.K.). 2.3.5 Cutaneous Somatosensation Static, tactile 2PD was used to assess changes in cutaneous somatosensation in the hemiparetic hand 107. During testing, participants were at rest with forearms supinated and vision obscured. The two arms of an aesthesiometer (Baseline? Aesthesiometer) were simultaneously placed on the thenar eminence with enough force to depress the skin for one second; participants reported whether they felt one or two contacts. Sequential adjustments of the arms were made in 2 mm increments to a maximum of 30mm. Sensory threshold was the distance where participants correctly reported feeling two points of contact 7 of 10 times 107. Catch trials were randomly applied where only one arm of the aesthesiometer was used. One individual who participated in both groups had severe sensory loss in the hemiparetic thumb due to a previous mechanical hand injury (partial thumb amputation) prior to stroke, and was excluded from 2PD analysis. In addition, 2PD was not collected for two members of the Active group owing to clerical error, therefore group sizes for 2PD analysis were n=8 (Active) and n=10 (Sham).   2.3.6 Motor Function Three task-performance items were selected from the original version of the WMFT 95 to briefly assess affected upper extremity motor function: time to pick up can, pick up paperclip, and fold towel. Movement time for each task was averaged over three attempts, and this value 20 was used to calculate a projected task rate per minute of task performance, to ensure normality 108. In addition, grip strength 109 was assessed using a Jamar ? Hand Dynamometer (5030J1). An average of the three attempts was calculated. Finally, the BBT was used to measure unilateral manual dexterity 96. BBT score was the number of blocks transferred in one minute. 2.3.7 Statistical Analysis All analyses were performed with SPSS software (Version 20). Group demographics were compared using independent samples t-tests. Descriptive and Shapiro-Wilk statistics were used to evaluate normality. Nonparametric tests were used for assessing group differences in baseline 2PD thresholds due to unequal sample sizes. To compare the effects of active- to sham-rTMS interventions, univariate linear mixed effects models were constructed. This statistical model design has the benefit of accounting for subject effects in the partial crossover design employed and for missing data. Dependent measures of tracking performance (Response Time, Peak Velocity and Cumulative Distance), 2PD threshold, WMFT task performance, grip strength, BBT score, and RMT were assessed. Group, Day, and Sequence (for STT) were considered as fixed effects in the model. A Subject term was included in the random effects model. A variance components covariance structure was specified and an intercept term was included in the random effects model. Significance level was set at p<0.05 for Type III F tests of the fixed and interaction effects in the model. 21  2.4 Results 2.4.1 Baseline Group Characteristics  The Active and Sham groups did not differ significantly in mean age, time post stroke, FM score, or lesion volume (Table 2-1 & Table 2-2; p>0.4).  There were no significant group differences in baseline STT performance (p>0.7).  2.4.2 Motor Learning We examined the effect of 5Hz rTMS over IL-S1 paired with skilled motor practice of the STT across the 7 days of the experiment for both groups (Figure 2-2 A). There was no significant Group x Sequence x Day interaction observed for any of the three primary variables (p>0.7). A significant Group x Day interaction was found for Response Time (F1,286.04=13.016, p<0.0005), Peak Velocity (F1,285.95=4.111, p=0.044), and Cumulative Distance (F1,285.92=4.076, p=0.044). To assess group-specific motor learning (Active vs. Sham), we evaluated mean performance values from the no-rTMS baseline and the no-rTMS retention tests and did not include performance on the rTMS + practice days (Figure 2-2 B). A significant Group x Day interaction was observed for Response Time (F1,66.05=6.761, p=0.011), but not Peak Velocity (F1,65.87=2.456, p=0.122) or Cumulative Distance (F1,65.54=3.134, p=0.081). A significant main effect of Day was observed for Peak Velocity (F1,65.87=8.645, p=0.005) and Cumulative Distance (F1,65.54=13.341, p=0.001), suggesting that STT practice benefitted both groups.  22 Figure 2-2:  STT mean performance values (A) and change scores (B) from baseline to retention for Response Time (i.) Peak Velocity (ii.) and Cumulative Distance tracked (iii.) for the Active and Sham groups.  Negative change scores reflect performance improvements from baseline to retention, as reflected by reduced response times, lower peak velocities and less cumulative distance traveled, respectively.  * p<0.05; Error bars are SEM. 23 2.4.3 Cutaneous Somatosensation 5 Hz rTMS over IL-S1 paired with motor practice improved 2PD threshold of the hemiparetic hand (group median: 2.00cm at baseline, 1.25cm at retention) compared to sham stimulation paired with practice (group median: 1.15cm at baseline, 1.25cm at retention), as indicated by a significant Group x Day interaction (F1,21.15=8.793, p=0.007; Figure 2-3). The two groups did not differ significantly at baseline (p=0.27). Figure 2-3: Individual thresholds for 2-point discrimination at baseline and retention, by stimulation type. Lower values indicate better somatosensory discrimination (i.e., less distance between stimulation points). Solid lines indicate first time participation, dashed lines indicate second time (crossed over) participation. (n=8 Active; 10 Sham). * p=0.007. 2.4.4 Motor Function No significant Group x Day interaction was found for pick up can rate (p=0.71), pick up paperclip rate (p=0.59), or fold towel rate (p=0.72).  In addition, no significant Group x Day interaction was detected for dynamometer grip strength (p=0.96) or BBT score (p=0.93). 24 2.4.5 Motor Cortex Excitability To determine whether the changes observed with 5Hz rTMS over IL-S1 may be attributed to altered ipsilesional M1 cortical excitability, we also evaluated RMT at baseline and retention. No significant Group x Day interaction was observed (p=0.07; Figure 2-4). Figure 2-4:  Individual resting motor threshold (RMT) values at baseline and retention by stimulation type.  Values in the first column represent subject number. Values in the second and third columns represent percent stimulator output. 25  2.5 Discussion We demonstrated that 5 Hz rTMS over IL-S1 paired with skilled motor practice enhanced motor performance and learning of a novel skilled motor task in individuals with chronic stroke. The benefits of 5 Hz rTMS over IL-S1 paired with motor practice were also associated with significant improvements in cutaneous somatosensation, as measured by 2PD. However, a significant effect was not observed for measures of motor function (abbreviated WMFT) or manual dexterity (BBT). Our primary outcome measure was change in STT performance across 5 days practice and on a delayed, no-rTMS retention test. Over the course of the experiment, greater improvements were observed in the Active group across reaction time, peak velocity, and cumulative distance moved. At retention, a persistent reduced response time in the Active group suggests that motor learning was enhanced by 5Hz rTMS over IL-S1. This effect was noted regardless of sequence type (random or repeated). In other words, active stimulation over IL-S1 did not yield sequence-specific benefits, but rather led to a generalized improvement of motor performance that was evident in both repeated and random sequence tracking. This is consistent with our past work demonstrating a reduction in non-specific motor control after inhibitory 1Hz rTMS over S1 in healthy adults 51, as well as improved generalized motor learning following cTBS over CL-S1 in individuals with chronic stroke 54. The improvement in one aspect of STT performance, response time, was most pronounced at the no-rTMS retention test, suggesting that 5Hz rTMS over IL-S1 paired with STT practice influenced motor learning by facilitating offline motor memory consolidation mechanisms 50,110-112. Interestingly, in both groups the reduction in total response time and cumulative distance traveled occurred at the expense of peak velocity, which also decreased with repeated practice of 26  the STT. This pattern suggests that participants developed improved motor control by taking more direct, guided trajectories between the starting point and end target. This was more pronounced for individuals who received 5 Hz rTMS over IL-S1, which was intended to increase cortical excitability of S1. In contrast, individuals who received sham stimulation prior to practice did not show the same magnitude of behavioral change. Improvements in perceptual learning following 5Hz rTMS over the sensory cortex have been documented before 113, albeit with a slightly different rTMS protocol. To our knowledge the current study is the first to show improved motor learning associated with active 5Hz rTMS over IL-S1 paired with motor practice in a chronic stroke population. Five days of 5Hz rTMS over IL-S1 paired with STT practice also improved cutaneous somatosensation of the hemiparetic hand, as measured by 2PD. This observation corresponds with previous findings that a modified 5Hz rTMS protocol applied over the finger area of S1 decreases 2PD thresholds and enlarges the corresponding cortical representation in healthy individuals 104. Nevertheless, the improved somatosensory discrimination observed here demonstrated limited transfer to the abbreviated WMFT or the BBT. This is in contrast to our past work demonstrating that cTBS over CL-S1 paired with the same STT induced improvements not only in motor learning but also in the WMFT 54. It is possible that stimulation over the contralesional side imparts effects across a larger portion of the sensorimotor network, given the extensive transcallosal 114 and thalamic connections 115 between the hemispheres, leading to broader functional gains. However, given the preliminary nature of the current study and that of Meehan et al. (2011) 54, the underlying neural mechanisms remain unclear. Further work is necessary to determine the optimal site(s), and protocols of stimulation to promote transfer to functionally relevant domains.  27  In addition to examining changes in motor behavior and somatosensation, we assessed the excitability of the adjacent motor cortex at baseline and retention. Despite the observed increase in motor performance from baseline to retention with 5 Hz rTMS over IL-S1 plus motor practice, a single pulse TMS measure of ipsilesional corticospinal excitability (RMT) showed no significant changes in either group. It is possible that, given our small sample size, we were underpowered to detect subtle changes in M1 excitability. However, an alternative explanation may be that increased IL-S1 excitability following 5Hz rTMS paired with motor practice resulted in increased functional connectivity between IL-S1 and IL-M1 during sensory-guided movement.  Indeed, this is in line with current theories of motor learning suggesting that skilled behavior arises from a complex interaction between sensory and motor systems and gives rise to an internal model for movement 116. Given the relatively small sample size and pseudo-crossover design, the current work should be interpreted as a preliminary report. Our groups were matched on a number of characteristics, however there was a broad range of lesion locations. While this heterogeneity is representative of a clinical stroke population, and fMRI studies have shown that cortical and subcortical strokes behave similarly in terms of post stroke hemispheric activation imbalances in M1 and S1 32, there is evidence to suggest that measures of cortical excitability may manifest differently according to the cortical/sub-cortical nature of the infarct 23.  Having 7 of 15 participants cross over between groups had the benefit of reducing some between-group variability, and the potential crossover effects were taken into account statistically using mixed effects modeling. Finally, another limitation of the current study is that we did not directly assess excitability changes in S1. While we did measure cutaneous somatosensation, this is an indirect 28  assessment of S1. Further work is needed to better understand the neurophysiological mechanisms involved.  2.6 Conclusion The current findings suggest that 5 Hz rTMS over IL-S1 paired with skilled motor practice enhances motor learning in individuals with chronic stroke. This enhancement is concurrent with improvements in cutaneous somatosensation. Taken together with past work, these results reinforce the importance of sensory cortex activity in motor skill learning, and suggest that rTMS-based activity modulation may be effective in enhancing motor learning during post-stroke rehabilitation.  2.7 Bridging Summary Chapter two found that, when paired with skilled motor practice, 5Hz rTMS over IL-S1 enhanced general skill learning of a visuomotor serial targeting task in individuals with chronic stroke. However, it is important to note that despite mean group differences, not everyone improved to the same degree, or even at all.  In fact, two of the individuals in the active stimulation group showed increased response times from baseline to retention (Figure 3-2). We report statistically significant differences between the active and sham groups, yet the effect variable across individuals. This is reminiscent of what has been reported in many previous studies of rTMS over M1 39,55,56. Growing interest is therefore developing within the field of noninvasive brain stimulation in terms of defining ?responders? versus ?non-responders? based on individual biomarkers 117,118. The following chapter describes an experiment that 29  retrospectively considered regional cortical morphology as a potential biomarker for rTMS responsiveness in the sample from Chapter 2. 30 Chapter  3: Impact of 5Hz rTMS Over the Primary Sensory Cortex is Related to White Matter Volume in Individuals with Chronic Stroke 3.1 Abstract Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive brain stimulation technique that may facilitate mechanisms of motor learning. In a recent single-blind, pseudo-randomized study, we showed that 5Hz rTMS over ipsilesional primary sensory cortex (IL-S1) paired with practice of a skilled motor task enhanced motor learning compared to combined sham rTMS + practice in individuals with chronic stroke 119. However, the beneficial effect of stimulation was variable. The current study examined how differences in IL-S1 morphology might predict rTMS-related improvements in motor learning in these individuals. High resolution T1-weighted scans were acquired, and processed with the Freesurfer image analysis package, using a newly developed automated, whole brain parcellation technique based on morphometric landmarks and grey/white matter boundary surface information. Grey matter (GM) and white matter (WM) volumes of IL-S1 and IL-M1 (primary motor cortex) were extracted and normalized to total cortical GM and WM volumes, respectively. A significant positive association was observed between IL-S1 WM volume and motor learning related change, exclusively in the group that received active 5Hz rTMS over IL-S1 (r=0.728, p=0.017). Regression modeling using age, IL-S1 GM volume, and IL-S1 WM volume as predictors was significant for predicting motor learning related change in performance in individuals who received active stimulation (n=10; R2=0.721, p=0.042). IL-S1 WM was the best predictor, uniquely accounting for 47.6% of the variance (p=0.019). The same model was non-significant when IL-M1 volumes were considered (n=10; R2=0.260, p=0.208). We conclude that WM volume in the cortex underlying the TMS coil may be a novel predictor for behavioural response to 5Hz rTMS over IL-S1 paired with motor practice. 31  3.2 Introduction Rehabilitation and recovery of motor function after stroke rely heavily on neuroplastic changes induced by motor learning 8,11. However, despite the observation that following stroke skilled motor learning is possible even after spontaneous recovery has plateaued 8,10,54,120, 55-75% of individuals are left with some level of chronic motor impairment 78. As a result, stroke remains one of the leading causes of long-term adult disability. This has led to an interest in adjunct therapies, intended to complement traditional rehabilitation interventions to facilitate mechanisms of motor learning and maximize recovery.  Non-invasive brain stimulation techniques are an intriguing option for adjunct therapies, as they may be used to modulate cortical plasticity and thereby influence physiological learning mechanisms 46. It has been hypothesized that priming a cortical area using brain stimulation prior to rehabilitation could enhance an individual?s response to treatment 121. For example, following stroke, repetitive transcranial magnetic stimulation (rTMS) may be used to re-establish the altered balance of cortical excitability between the hemispheres 35,122, either by increasing cortical excitability in the ipsilesional (IL) hemisphere 56, or decreasing it in the contralesional (CL) hemisphere 55,56. However, the reported effects of rTMS have been small 123, and the impact on functional outcomes limited 46.   There are many factors that may contribute to the low effect sizes associated with rTMS trials in individuals with stroke. One possibility is that, while the majority of previous studies focused on applying rTMS over the primary motor cortex (M1), it may not be the optimal target for stimulation. Motor learning is a complex process involving a distributed network of brain areas 124-126. Therefore, targeting an alternative cortical area that is functionally and anatomically connected to M1 may be effective in strengthening synaptic connections between areas involved 32 in motor learning. For example, previous work showed that applying rTMS over the left dorsal premotor cortex, which has direct synaptic connections to M1, enhances off-line consolidation of new motor skills in healthy individuals 50,106. Moreover, the application of continuous theta burst stimulation (cTBS) over contralesional primary sensory cortex (CL-S1) enhanced aspects of motor learning and general functional ability in individuals with chronic stroke 54. In addition, we recently reported that excitatory 5Hz rTMS over ipsilesional primary sensory cortex (IL-S1) paired with motor practice led to a generalized improvement of task performance in individuals with chronic stroke 119. In this work our results were encouraging but the response to rTMS was highly variable in between individuals. The small effect size reported in studies pairing rTMS with motor learning or rehabilitation can be attributed at least in part to inter-subject variability. In turn, to better understand the capacity for neuroplastic change after stroke, the factors that contribute to variability in response to non-invasive brain stimulation need to be understood. The problem is multifaceted 123. First, there is a naturally occurring variation in individual motor learning ability, even within young, neurologically intact populations 127,128. In addition, the effectiveness of rTMS protocols aimed at inducing cortical plasticity is known to be highly variable both between and within individuals 123,129. These issues may be amplified by brain damage in clinical populations such as stroke, where factors such as local lesion anatomy 130,131  and diffuse injury 132  also contribute to individual differences in recovery potential 133,134  and learning ability 135.  Certain factors that contribute in part to inter-individual variability in rTMS response have been identified. For example, aging is linked with a reduction in learning and memory ability, and altered capacity for synaptic plasticity 136. In addition, age is negatively associated with the effectiveness of inducing cortical plasticity with rTMS 137-139. Another potential factor 33 that may contribute to inter-subject variability in response to rTMS is brain morphology, particularly within the region being stimulated. The electric field induced by TMS is relatively focal, extending only ~1-2cm below the center of the coil 14, thus its initial effects are primarily restricted to the cortex 140. There is a large amount of morphological variability in the healthy human cortex 141. Recent evidence suggests that individual differences in cortical anatomy may play a role in response to rTMS. Sensorimotor cortical thickness, for example, has been reported to positively influence the effectiveness of paired associative stimulation in young healthy subjects 142  as well as in healthy older adults 143. Whether these effects generalize to the effectiveness of other forms of non-invasive brain stimulation remains unknown. The current study aimed to explore the relationship between the effectiveness of 5Hz rTMS and the morphology of the underlying cortex, in individuals with chronic stroke. Specifically, we performed a retrospective analysis based on our recent report that 5Hz rTMS over IL-S1 paired with skilled motor practice enhanced motor learning. We asked whether grey matter (GM) and/or white matter (WM) volumes of IL-S1 might predict the effectiveness of 5Hz rTMS at enhancing motor learning in individuals with chronic stroke. Further, in order to determine whether the association is specific to the area of stimulation (IL-S1), we also considered the predictive value of GM and WM volumes of ipsilesional primary motor cortex (IL-M1). We hypothesized that individuals with a higher neural reserve in the underlying cortex would respond better to 5Hz rTMS over the IL-S1 paired with practice. We expected that: (1) for individuals who received active, 5 Hz stimulation, a higher volume of GM and/or WM in the IL-S1 would be associated with more motor learning related change, and (2) this association would not be noted in individuals who received sham stimulation.  34  3.3 Methods The University of British Columbia (UBC) research ethics board approved all aspects of the study protocol and informed, written consent was obtained from each participant in accordance with the Declaration of Helsinki. Individuals with chronic (>6 months post) stroke were recruited from the local community, and pseudo-randomly assigned into two groups: either to receive Active 5Hz rTMS, or Sham stimulation that looked and sounded exactly like rTMS but did not induce a current (n=11/group).  The experiment was conducted over seven sessions, each separated by no more than 3 days (Figure 3-1 A). 3.3.1 Serial Targeting Task (STT) The primary outcome measure for this study was change in performance on a goal-directed, visuomotor Serial Targeting Task (STT) 54. Holding a modified wireless mouse in a custom frame with their hemiparetic hand, participants were instructed to move a cursor between sequentially appearing 28mm diameter targets in one of nine possible locations as quickly and accurately as possible (Figure 3-1 C). Vision of the hand was blocked to isolate the specific effects of somatosensation from visual feedback on motor performance 51. After one day of baseline testing (1 block), individuals underwent 5 days of stimulation paired immediately with STT practice (6 blocks per day). This was followed by a final no-rTMS retention test (1 block) on the seventh day. One block consisted of 72 targeted movements. Each movement was quantified by response time (RT; reaction time + movement time) as a primary measure of motor performance. Reductions in RT from baseline over the five days of practice (negative RT change; indicative of improved motor performance) and at retention (indicative of motor learning) were observed in both the Active and Sham groups. However, the group that received 35 Active stimulation showed a significantly larger reduction in RT over the seven days of the initial experiment than the Sham group (Figure 3-2). Figure 3-1:  Experimental overview.  (A) A 3T T1 anatomical MRI  was obtained for each participant prior to the beginning of the experiment. At the baseline session on day 1, performance on one block of a visuomotor serial targeting task (STT) was assessed. This was followed by 5 separate sessions of active 5Hz or sham rTMS paired with 6 blocks of STT practice (days 2-6). A delayed, no-rTMS retention test of 1 block of STT performance was administered on a day 7, to assess motor learning.  (B) Example of target trajectories set in BrainSightTM for M1 and S1.  (C) Schematic of the experimental motor learning task, the STT, showing a sample progression of targets and illustration of a path of movements between 2 targets.  36 Figure 3-2:  Changes in response time (RT) from baseline to retention, indicative of motor learning. Grey bars represent individual subjects, black bars represent group means. The change in RT was found to be significantly greater in the Active group compared to the Sham group (F1,66.05=6.761, p=0.011; Brodie et al., in review 119). 3.3.2 Transcranial Magnetic Stimulation (TMS) During the application of rTMS, individuals were seated in a reclined chair and instructed to keep their arms at rest. Electromyography (EMG) was recorded from the extensor carpi radialis (ECR) muscle of the hemiparetic arm. A 70-mm figure-of-eight air-cooled coil connected to a Magstim Super Rapid stimulator (Magstim Company, Ltd., Wales, U.K.) was used to deliver biphasic stimulation that produces a current flow in a posterior-anterior, then anterior-posterior direction, with a pulse width of 400us. Coil position was guided stereotaxically using individual T1 anatomical MR images imported into BrainSightTM TMS neuronavigation software [v2.0]. In order to locate the ECR ?hotspot?, single suprathreshold pulses were applied 37 over the hand knob of M1 with the coil oriented tangentially to the scalp, and the handle at 45! to the midline in a posteriorlateral orientation. RMT was then defined as percent stimulator output to produce a motor evoked potential (MEP) of at least 50?V peak-to-peak, in five out of ten trials, respectively 100. In order to stimulate S1, the coil was shifted ~2cm posterior to the M1 ECR ?hotspot? 103,104, directly over the crown of the postcentral gyrus using the T1 scan to guide placement 51,54 (Figure 3-1 B). Single suprathreshold pulses, at ~110% of RMT were used to verify isolation of S1 from M1, as evidenced by a lack of MEP when S1 was stimulated above RMT 105. The active rTMS protocol consisted of 24 trains of 5 Hz pulses at an intensity of 90% RMT for 10 seconds, with 5 seconds rest in between (1200 pulses in total). The Sham group underwent the identical procedure using a custom sham coil (Magstim Company, Ltd., Wales, U.K.). 3.3.3 MRI Acquisition and Analysis A high resolution T1 anatomical MRI (TR = 12.4ms, TE = 5.4ms, flip angle " = 8?, FOV = 256 mm, 170 slices, 1 mm thickness) was obtained for each participant, except for one individual with a contraindication to MRI. Image acquisition was conducted at the UBC MRI Research Centre on a Philips Achieva 3.0T whole body MRI scanner (Phillips Healthcare, Andover, MD) using an eight-channel sensitivity encoding head coil (SENSE factor=2.4) and parallel imaging. Images were imported into Freesurfer for data processing and analysis.  Cortical reconstruction and volumetric segmentation was performed with the Freesurfer image analysis package 144,145. In brief, the processing pipeline involved motion correction of the T1 image, removal of non-brain tissue, automated Talairach transformation, segmentation of subcortical white matter and deep gray matter structures, intensity normalization, tessellation of 38 the gray/white matter boundary, automated topology correction and surface deformation. Each brain was inflated so that the whole cortical surface was visible. GM sulco-gyral cortical units were parcellated automatically according to curvature landmarks 146, and labeled according to conventional brain atlas nomenclature 147. WM underlying a given cortical region preferentially contains afferent and efferent fibres associated with that cortical region. Therefore, the cortical parcellations were subsequently used to label underlying cortically associated regional WM based on the nearest cortical label, using a newly developed, automated method in Freesurfer 148. A representative image of the GM and WM parcellation scheme is shown in Figure 3-3. The test-retest reliability of this method has previously been shown in young healthy individuals 148, however to our knowledge it has yet to be applied in older individuals with stroke. All automated segmentation analyses were performed with lesions left unmasked. Processed images were visually inspected for segmentation and lesion exclusion quality, and were overall deemed to be qualitatively accurate. That is, the lesion core was not included in the cortical parcellation, and modeling of the GM/WM and landmarks exterior to the lesion was unaffected by the presence of the lesion. One individual?s scan was excluded due to the large lesion volume and failed segmentation in the ipsilesional hemisphere. Subsequent analyses were performed in the remaining ten participants. Regional GM and WM volumes of IL-S1 and IL-M1 were extracted, and normalized to total volume of cortical GM or WM respectively, in order to account for individual differences in total brain size and the heterogeneity of lesion volumes. 39 Figure 3-3:  A representative image of the automated grey and white matter segmentation and volumetric parcellation technique, performed with the Freesurfer image analysis package 144,145. Cortical grey matter is outlined in red; cortical white matter is outlined in blue; each parcelated region is represented by a different color.  [IL-S1 = ipsilesional primary sensory cortex; IL-M1 = ipsilesional primary motor cortex] 3.3.4 Statistical Analysis All statistical analyses were conducted using SPSS software (SPSS 20.0). All data were assessed for normality and homogeneity of variance (Levene?s test). Fugl-Meyer scores and lesion volumes were non-normally distributed thus non-parametric statistics were conducted for baseline group comparison. In order to determine whether the two groups differed in any of the segmented volumes of interest, a multivariate analysis of variance (MANOVA) was performed using IL-S1 and IL-M1 GM and WM volumes as dependent variables, and stimulation group as a fixed factor.  In order to prioritize order of entry for regression analyses, Pearson?s correlation coefficient (r) was used initially to explore the relationships between cortical volumes of interest 40 and change in RT following intervention. Given the group difference in RT change, we examined the association between IL-S1 and IL-M1 GM and WM volumes and RT change for the Active and Sham groups separately. Significance level was uncorrected (p<0.05) for each test. Following the correlation analyses, hierarchical multiple linear regression analyses were performed to evaluate the capacity of IL-S1 and IL-M1 segmented volumes to predict variance in change in performance following rTMS + training. Our primary objective for the current study was to determine whether the neural reserve of the cortical area being stimulated (IL-S1) is associated with the effectiveness of rTMS at enhancing motor learning. Thus, regression analyses were performed exclusively for the group that received active 5Hz rTMS. Age was entered into the first block of the model based on previous reports of reduced cortical GM volume 149, reduced global WM volume 150 and integrity 151 associated with aging. GM volume was entered into the second block, given that TMS induces current flow changes transynaptically within cortical GM 152. In addition, regional grey matter volume in the area of epidural cortical stimulation (M1) has been associated with better physiologic integrity 153, and greater S1 cortical (GM) thickness has been linked with larger extent of functional plasticity 76 and TMS-induced plasticity 142,143. Finally, WM volume was entered into the third block, as a novel predictor variable. This order of entry allowed the assessment of whether individual variations in WM volume may explain a unique portion of the variability in rTMS effect, after accounting for age and GM volume.  For both the IL-S1 and IL-M1 regression models, the assumptions of normality and independence of the residuals were met, according to the Shapiro-Wilkes test (W(10)#0.85, p#0.06) and Durbin-Watson statistic (d=2.409 and 2.448), respectively. In addition, collinearity between predictors was acceptable for both models (variance inflation factor $ 1.475, tolerance 41 values >0.1). Each regression analysis was evaluated for overall significance of the final model, as well as the significance of the R2 change when adding new predictors. It is possible that a relationship between the cortical volumes of interest and rTMS effectiveness may arise due to a confounding variable of differing motor cortex excitability. Indeed, recent work has shown that lower cortical thickness is associated with higher motor cortical excitability in healthy older adults 143. Therefore, we also examined correlations between IL-S1 and IL-M1 GM and WM volumes and baseline RMT values for each individual. For this analysis, the two groups were combined, since baseline RMT was assessed prior to group assignment. 3.4 Results 3.4.1 Baseline Measures The two groups did not differ significantly in age, FM score, lesion volume, baseline STT response time, or RMT (p>0.63). No significant differences were observed between groups in IL-S1 or IL-M1 GM or WM volumes, or total cortical GM or WM volumes (p >0.384; Table 3-1).  3.4.2 Correlation Analyses No significant correlation was found between IL-S1 GM volume and RT change for the Active (r=-0.525, p=0.120) or the Sham group (r=-0.235, p=0.514; Figure 3-4 A). On the other hand, a significant correlation was observed between IL-S1 WM and RT change in the Active group (r=-0.728, p=0.017), but not in the Sham group (r=-0.305, p=0.392; Figure 3-4 B). To determine whether these observed effects were specific to the area being stimulated (IL-S1), we then performed the same analysis using IL-M1 as a control region of interest. No significant 42 correlation was found between IL-M1 GM volume and RT change for the Active (r=0.316, p=0.374) or the Sham group (r=-0.508, p=0.133; Figure 3-4 C). Similarly, no significant correlation was observed between IL-M1 WM and RT change for the Active (r=-0.285, p=0.425) or the Sham group (r=0.177, p=0.624; Figure 3-4 D). No significant correlations were observed between any of the GM or WM volumes of interest and baseline RMT (Table 3-2).  Table 3-1:  Baseline group differences Values are mean ? SD[FM = Fugl Meyer score; RT = Reaction time; RMT = Resting motor threshold; IL-S1 = ipsilesional primary sensory cortex; IL-M1 = ipsilesional primary motor cortex; GM = Grey matter; WM = White matter]Table 3-2:  Correlation coefficients between volumes of interest and motor cortex excitability [RMT = resting motor threshold; IL-S1 = ipsilesional primary sensory cortex; IL-M1 = ipsilesional primary motor cortex; GM = grey matter; WM = white matter] 43	 ?Figure	 ?3-??4:	 ?Correlations	 ?between	 ?each	 ?volume	 ?of	 ?interest	 ?and	 ?response	 ?time	 ?(RT)	 ?change,	 ?performed	 ?for	 ?the	 ?Active	 ?and	 ?Sham	 ?groups	 ?separately.	 ?Negative	 ?change	 ?scores	 ?indicate	 ?reduced	 ?response	 ?time	 ?from	 ?baseline	 ?to	 ?retention,	 ?indicative	 ?of	 ?improved	 ?motor	 ?performance.	 ?	 ?[IL-??S1	 ?=	 ?ipsilesional	 ?primary	 ?sensory	 ?cortex;	 ?IL-??M1	 ?=	 ?ipsilesional	 ?primary	 ?motor	 ?cortex;	 ?GM	 ?=	 ?grey	 ?matter;	 ?WM	 ?=	 ?white	 ?matter].	 ?44 3.4.3 Regression Analyses The overall model from the regression analysis examining the predictive value of age, IL-S1 GM volume, and IL-S1 WM volume was significant for predicting RT change in the ten individuals that received active 5Hz rTMS over IL-S1 (R2=0.721, p=0.042). However, when only age, or age + IL-S1 GM volume were included as predictors, the model was not statistically significant. Adding IL-S1 WM volume as a predictor significantly improved the model (!R2=0.476, p=0.019). The overall model from the secondary regression analysis examining age, IL-M1 GM and WM volumes was not statistically significant (R2=0.260, p=0.208). The model was not significant when using age alone, or age + IL-M1 GM volume as predictors. Adding IL-M1 WM volume improved the model, however it failed to reach statistical significance (!R2=0.352, p=0.084). Results from the two regression analyses are presented in Table 3-3. Table 3-3:  Regression values for the IL-S1 and IL-M1 models [IL-S1 = ipsilesional primary sensory cortex; IL-M1 = ipsilesional primary motor cortex; GM = grey matter; WM = white matter; *p<0.05] 45 3.5 Discussion Here we show a significant positive association between IL-S1 WM volume and motor learning related change, exclusively in the group that received active 5Hz rTMS over IL-S1. Regression modeling confirmed that, in individuals who received active stimulation over IL-S1, the volume of WM in IL-S1 explained a significant amount of the variance in motor learning related change as indexed by the reduction in RT from baseline to retention testing. Based on previous work, we expected to observe a relationship between IL-GM volume and response to active rTMS paired with motor skill training, however this was not the case in the sample studied. The current induced by a given TMS coil is thought to be restricted mainly to cortical GM, due to the relative depth and greater resistance of WM 154. Furthermore, the effectiveness of subthreshold TMS pulses at inducing I-waves is abolished after removal or cooling of cortical GM in non-human primates 155,156. Recent work in humans showing that greater cortical thickness in the sensorimotor cortex is associated with greater effectiveness of TMS-induced LTP-like plasticity 142,143 further supports the hypothesis that GM volume might predict the effectiveness of rTMS. However, our study included 5 sessions of 5Hz rTMS over IL-S1 paired with motor practice in individuals with chronic stroke 119. Thus, differences between past, published work and our data could be related to the delivery of repeated rTMS sessions and/or our focus on individuals with chronic stroke.  In contrast past work has largely focused on single sessions of rTMS and studied the response of healthy individuals 142,143. Given these differences in experimental design it is difficult to draw direct comparisons between studies. Motor learning relies on a functional integration of GM regions and the WM tracts connecting them 128. Structural properties of WM such as degree of myelination and axon 46 diameter will influence the efficacy of signal transmission within these circuits, thereby influencing behaviour. Diffusion weighted MRI is commonly used to assess the status of WM. Typically, fractional anisotropy (FA), a quantitative measure of the directionality of water diffusion, is reported as a measure of the microstructural integrity of WM tracts, as it may be influenced by axon density and/or axon diameter 157. Following stroke, WM is vulnerable to damage and degeneration both directly at the lesion site and indirectly in diffuse areas throughout the brain 132. Reduced FA of motor output regions is associated with poorer motor function 133,134,158,159, and motor learning 135, suggesting that there may be a minimum threshold of WM required for clinical improvement in individuals with chronic stroke 134. The majority of diffusion-based studies of WM integrity have focused on large white matter pathways such as the posterior limb of the internal capsule, for which directionality is an important indicator of integrity. However, when examining other brain areas such as the WM directly underlying the cortex, FA may not provide an accurate index of structural status due to the presence of crossing fibres and partial volume effects 160-162. Diffusion measures such as FA are not comprehensive measures of true white matter integrity, as they do not take into account fibre bundle orientation 163. Increased dendritic branching in various directions, for example, may reduce the FA of a given voxel.  In this case, assessing regional WM volume may provide an alternative approach to assess cortical WM structure. The mechanisms underpinning the effects of 5Hz rTMS over IL-S1 paired with motor practice on motor learning 119 are not fully understood. High frequency rTMS increases excitability in the underlying cotrex 20,22. When applied over S1, it increases the amplitude of sensory evoked potentials 89 and enhances tactile discrimination in the contralateral hand 119,164. It is possible, however, that by pairing 5 Hz rTMS over IL-S1 with repetitive motor practice, 47 we are not only improving somatosensation, but strengthening the connection between IL-S1 and IL-M1, potentially unmasking latent horizontal connections. Under that assumption, greater WM volume directly under the cortical area being stimulated (S1) may indicate the increased potential for trans-synaptic excitation between that area and corticospinal output neurons 165.  Due to the small sample size in the current study, we were unable to parse out other possible predictors of inter-individual variability in rTMS response, such as gender, handedness, or stroke topography. Also, given the relatively narrow age range of our sample, the predictive value of age may have been underestimated in our regression model. Despite these limitations we report a novel factor, regional WM volume of the cortex underlying the rTMS coil, as a significant predictor of rTMS responsiveness in individuals with chronic stroke. Future work is required to determine whether the same relationship between response to rTMS and underlying cortical volumes might be observed when stimulating other areas. 3.6 Conclusion The present study utilizes a newly developed automated segmentation and parcellation technique to examine the relationship between rTMS response and morphological characteristics of the brain regions being stimulated. Our results indicate that regional cortical WM volume is associated with behavioural response to 5Hz rTMS over IL-S1 paired with motor skill training in chronic stroke. Exploring the factors involved in variability of response to rTMS may help elucidate the mechanism behind the beneficial effects of stimulation, and optimize the use of plasticity-inducing TMS techniques in a therapeutic context. 48 3.7 Bridging Summary One of the major assumptions of rTMS studies in individuals with stroke is that the balance of cortical excitability between the IL and CL hemispheres is abnormal, and thus modulating it with excitatory or inhibitory rTMS should be beneficial. This assumption is based heavily on common measures of TCI between M1s that have indeed reported that the interhemispheric excitability balance is abnormal following stroke, and that this imbalance correlates with poorer motor function 35. However, while a few studies in healthy individuals suggest that somatosensory IHI can also be effectively modulated with rTMS 105,166-168, the neurophysiological mechanism behind S1 IHI is relatively ambiguous, and a well-defined, temporally specific technique to quantify it is currently lacking. Recently, a paired median nerve stimulation technique was described by Ragert and colleagues (2011) 169, which identified a critical time window in which direct S1-S1 IHI occurred. Given the promising potential of S1 as a target for rTMS interventions described in Chapter 2, such a measure would be a valuable tool for comparing S1 IHI in healthy individuals and individuals with stroke, to guide the design of future rTMS over S1 studies. Chapter 4 describes an experiment that, using a modified version of the paired median nerve stimulation technique described by Ragert et al. (2011) 169, explores the neurophysiological mechanisms of direct S1 IHI in healthy human subjects. 49 Chapter  4: Exploring the Specific Time Course of Interhemispheric Inhibition Between the Human Primary Sensory Cortices 4.1 Abstract The neurophysiological mechanism of interhemispheric inhibition (IHI) between the human primary sensory cortices (S1s) is poorly understood. Recently, Ragert and colleagues (2011) 169 used electroencephalography (EEG) and a paired median nerve somatosensory evoked potential protocol to demonstrate direct transcallosal inhibition between S1s. They report that the amplitude of the N20 potential, the earliest component of the cortical somatosensory evoked potential (SEP) recorded over the left S1 after a test stimulus (TS), was depressed when it was preceded by a conditioning stimulus (CS) to the right S1 within a critical interstimulus interval (ISI) of 20-25ms. Here, we sought to reproduce and refine this protocol to see if a similar effect might be observed. In ten healthy individuals, we compared peak-to-peak amplitudes of SEP components (P14/N20, N20/P25, P25/N30, N30/P40, and P40/N60) recorded over the right S1 after synchronous versus asynchronous median nerve stimulation. Asynchronous CS+TS were delivered at ISIs of 15, 20, 25, 30, and 35ms. We found that when the CS to the left S1 preceded the TS to the right S1 at shorter ISIs (15 and 20ms), the N20/P25 complex was inhibited (p<0.009), whereas at longer intervals (25, 30, and 35ms), inhibition was observed for the thalamocortical P14/N20 (p<0.037) and the cortical N20/P25 components (p<0.046). We conclude that the degree of S1 IHI appears to depend on the temporal asynchrony of bilateral inputs, and the specific timing is reflective of a transcallosal mechanism. Developing a method by which direct S1 IHI may be reliably quantified may provide a novel tool to assess potential IHI imbalances in individuals with neurological damage, such as stroke. 50 4.2 Introduction The ability to produce skilled, coordinated movements relies on the dynamic interactions between the two hemispheres of the brain. For example, in the motor system it is well known that the activation of one hemisphere during a simple task results in decreased activation of the other hemisphere 170. As discussed in Chapter 1, this interhemispheric inhibition (IHI) is increased during one-handed movements and is thought to prevent unwanted mirror movements of the opposite hand. Alternatively, during tasks that require the movement of both hands simultaneously, IHI is decreased 171. Individuals who specialize in bimanual coordination, such as musicians, tend to have overall reduced IHI 28,172. However, after unilateral brain damage such as stroke the lesioned hemisphere may no longer be able to effectively inhibit the healthy hemisphere. Meanwhile, the healthy hemisphere continues to inhibit the lesioned hemisphere, potentially even more than before, as it has been released from inhibition from the lesioned hemisphere. As a result, IHI becomes over exaggerated in one direction 35 (Figure 1-1). This imbalance in IHI after stroke is associated with poorer motor function 34,173,174. The ability to measure IHI provides a valuable tool for predicting individual motor outcome, recovery potential, and targets for intervention after stroke 38. The mechanism of IHI in the motor system has been thoroughly investigated. The primary motor cortices (M1) of each hemisphere are connected by a distinct segment of the corpus callosum 114 ? a large bundle of axons connecting homologous areas of the two cerebral hemispheres. The neurons of the corpus callosum are mainly excitatory; their functional effects depend on the nature of their target 25,172. Activation of M1 in one hemisphere sends an excitatory signal transcallosally, which excites inhibitory interneurons in the contralateral M1, decreasing its net excitatory output175, thereby preventing unwanted mirrored activity 176. This 51 transcallosal inhibition (TCI) can be systematically measured using transcranial magnetic stimulation (TMS), a form of non-invasive brain stimulation that uses a magnetic field to induce a brief electrical current in a localized area of the cortex. Upon applying a TMS pulse over M1 in one hemisphere as a conditioning stimulus (CS), the extent of TCI in the contralateral M1 can be measured in two ways: (1) the paired pulse approach, applying an appropriately-timed (~10ms post-CS) test stimulus (TS) TMS pulse over the M1 contralateral to the CS and measuring the change in motor evoked potential (MEP) amplitude from that hemisphere 177,178, or (2) the single pulse approach, recording a transient, involuntary suppression of ongoing muscle activity from the inhibited side (referred to as the ipsilateral silent period) ~35ms after the TS 114,179. These methods are both used to study TCI between M1s in healthy and neurologically damaged populations 34,180,181. The somatosensory system is tightly linked to the motor system, and is also critical for coordinated movement. However, the mechanism of IHI between sensory cortices is not as well understood. An accumulating body of evidence suggests that, similar to the motor system, activation of S1 in one hemisphere can modulate the activity of S1 in the contralateral hemisphere. For example, functional magnetic resonance imaging (fMRI) studies in monkeys 182 and in humans 166,183-186 describe a corresponding increase in activation in the contralateral S1, and transient decrease in activation in the ipsilateral S1 during peripheral hand stimulation. This decrease in ipsilateral S1 activation correlates with reduced sensory perception in the opposite hand 184. Likewise, animal studies have shown that disruption of function of S1 in one hemisphere by cooling resulted in an augmentation of neural activity and enlarged receptive fields of neurons in the homologous S1 187. In humans, studies using repetitive TMS (rTMS) to 52 inhibit S1 in one hemisphere have shown an enhanced sensory response in the contralateral S1 167, which may also correlate with improved somatosensation 166. Despite the evidence that somatosensory IHI may occur, few studies have examined the precise neurophysiological mechanisms involved. One of the major limitations of fMRI is its poor temporal resolution. Similarly, studies applying rTMS and subsequently measuring sensory thresholds are not temporally specific enough to elucidate the precise neural pathways involved. In the studies described above, it is not possible to conclude whether IHI between S1s occurs directly via the corpus callosum (similar to TCI between M1s), indirectly via secondary cortical or subcortical regions, or as some combination of both pathways.  The primary sensory cortex is comprised of 4 cytoarchitechtonically and functionally distinct areas: Broca?s areas 1, 2, 3a, and 3b 188 (Figure 4-1). Afferent signals from cutaneous stimulation are transmitted first to area 3b (sometimes referred to as ?S1 proper? 189), and then to the other areas of S1 and secondary sensory areas for higher cortical processing. Callosal connections between S1s have been described in animals 190,191, however direct connections between area 3b are described as sparse, especially between representations of distal body parts such as the hand 190,191. In humans, post-mortem anatomical analyses 192 and in vivo diffusion weighted imaging 114 have described a section of the corpus callosum connecting S1s, however the precise areas of Figure 4-1: The primary sensory cortex (S1) is divided into 4 regions: Broca?s areas 3a, 3b, 2, and 1. Area 3b is the first to receive afferent sensory transmission from the thalamus, and is therefore sometimes referred to as ?S1 proper?. 53 origin and termination within S1 are not described. In contrast, extensive transcallosal projections have been reported between homologous secondary somatosensory cortical areas, such as the posterior parietal cortex (PPC), and the parietal operculum (SII) of each hemisphere 193-198. Moreover, dense intracortical connections exist between SII and areas 3b and 1 of S1 199,200. Thus, it has been argued that somatosensory IHI must go through secondary sensory areas such as SII, rather than directly from S1 to S1. Indeed, IHI between SIIs has been reported using magnetoencephalography source analysis during asynchronous somatosensory stimulation of both hands 198. This SII IHI was initiated when stimuli were separated by 10ms, and was maximal when stimuli were separated by 40-60ms. Furthermore, it was determined to be mediated by callosal fibers, and to correlate with bimanual tactile task performance 198.  Another possible mechanism by which somatosensory IHI may occur is indirectly via the transcallosal M1 connections. The primary motor and sensory cortices are reciprocally connected 199,201, and sensory input is known to influence the ipsilateral motor cortex at a ~5ms delay 202. It is therefore possible that IHI between S1s may be mediated by a S1-M1-M1-S1 pathway, particularly during tasks involving sensorimotor integration. A recent study by Ragert and colleagues (2011) 169 used electroencephalography (EEG) to examine direct interhemispheric interactions between the S1s in humans. Using a paired median nerve somatosensory evoked potential (PMNSEP) protocol, the authors showed that the amplitude of the N20 potential, the earliest component of the cortical sensory evoked potential (SEP), recorded over the left S1 was depressed when a CS was applied to the left MN 20-25ms before a TS to the right MN 169. The authors concluded that this was ?direct evidence for transcallosal information transfer at an early stage of cortical processing in the human 54 somatosensory system? 169. In other words, the critical time window of 20-25ms was too short to have involved indirect transmission between M1s or SIIs. The suggestion that the two primary sensory cortices are directly linked is intriguing and warrants further investigation. Developing a method by which direct S1 IHI may be reliably quantified may provide a novel tool to assess potential IHI imbalances in individuals with neurological damage, such as stroke. Similar M1 TCI, S1-S1 IHI imbalances may be predictive of sensorimotor impairment, and may identify alternative targets for non-invasive brain stimulation interventions. Thus, the purpose of the current study was to reproduce and refine the PMNSEP paradigm described by Ragert and colleagues (2011) 169 to see if a similar direct S1 IHI effect might be observed. Given the reports of transcallosal fibers connecting homologous regions of S1 in each hemisphere 114,192, and the well-recognized importance of interhemispheric coordination for the production of skilled sensorimotor behaviors, we hypothesized that a direct S1-S1 transcallosal inhibitory influence would indeed be observed, and would take place in a similar time window as that described by Ragert et al. (2011) 169. 4.3 Methods 4.3.1 Experimental Procedure Ten healthy adults (mean age ? SD= 28.3 ? 5.4 years; 5 females) were recruited. All participants were right handed, according to an adapted version of the Edinburgh inventory for the assessment of handedness 203,204 (Augmented laterality index: mean ? SD = 83.33 ?17.21, over a range of -100 (fully left-handed) to +100 (fully right-handed)). The research ethics board of the University of British Columbia approved all procedures. Informed, written consent was obtained from all participants according to the Declaration of Helsinki.  55 The experiment was conducted over a single ~2hr session. The PMNSEP paradigm was adapted from that described by Ragert et al. (2011) 169. Briefly, a conditioning stimulus (CS) was delivered to the right median nerve (MN), followed by a test stimulus (TS) to the left MN, in a series of different inter-stimulus intervals (ISIs; Figure 4-2 B). The original study by Ragert et al. (2011) 169 compared 5, 10, 15, 20, 25, and 30ms ISI conditions, however their reported inhibitory effect was limited to the 20 and 25ms ISI conditions. Thus for the current study, we chose to eliminate the 5 and 10ms condition, and to consider ISIs of 15, 20, 25, 30, and 35ms instead. In addition, we added a 0ms ISI condition (i.e., the two MNs being stimulated at exactly the same time), in the interest of using it as an alternative baseline to compare with each of the asynchronous ISI conditions. It is well known that differences in attention can alter sensory processing and SEP amplitudes 205.  Therefore, we felt that the 0ms condition served as a more appropriate baseline for comparison, as the individual?s attention would be divided between the two hands. 4.3.2 Paired Median Nerve Somatosensory Evoked Potential (PMNSEP) Paradigm  Participants were seated comfortably upright in a chair, with arms resting in a supinated position on a pillow in their lap, and were instructed to remain relaxed with their eyes closed during stimulation. Surface electromyography (EMG) was recorded from the abductor pollicis brevis (APB) muscle in both hands. Standard bar electrodes were placed over the MN on the inside of the wrist, aligned with the wrist crease, with the cathode proximal. Electrical pulses were generated and triggered using LabChart7 software (ADInstruments, Colorado, USA ) via a Powerlab 8/35 data acquisition system (PL3508, ADInstruments, Colorado, USA), and were delivered to participants using two constant current stimulators (DS7 & DS7AH, Digitimer, Hertfordshire, U.K.). Stimulation was delivered at 2Hz, with a square wave, monophasic pulse  56 Figure 4-2:  The paired median nerve somatosensory evoked potential (PMNSEP) paradigm. A conditioning stimulus (CS) was delivered to the right median nerve (MN) followed by a test stimulus (TS) to the left MN at various interstimulus intervals. MN stimulation was adjusted online to maintain a 1mV peak-to-peak motor evoked potential (MEP), recorded from the abductor pollicis brevis (APB) muscle of each hand. Sensory evoked potentials (SEPs) were recorded from channel CP4, overlying the primary sensory cortex (S1) in the right hemisphere. (A) The average ipsilateral SEP response from CS alone (blue line) was subtracted from the average raw SEP response from the CS+TS conditions (redline). The plotted difference between CS and CS+TS (black line) was used to extract peak-to-peak amplitudes for each component. (B) Schematic of the experimental setup. Interhemispheric inhibition occurs from the left (dominant) hemisphere to the right (non-dominant) hemispher57 width of 0.1ms. Precise MN localization was based on individual reports of a tingling sensation in the MN distribution, including the thumb, index, and middle finger. The intensity of stimulation was then increased to produce a motor evoked potential (MEP) in the APB of ~1mV peak to peak (mean ? SD = 962.066?202.326mV for right hand, 1085.270?216.274mV for left hand). MEPs were visually monitored online throughout the experiment, and small adjustments in stimulation intensities (?1-2mA) were made when necessary to maintain consistent MEP amplitudes. Participants were asked to report any discomfort or fatigue throughout the experimental session. SEPs were recorded using a direct current full band electroencephalogram (EEG) system (NEURO PRAX? EEG, NeuroConn, Ilmenau, Germany) from 29 custom chosen electrode locations across the sensorimotor areas of both cortices (Figure 4-3), according to the International 10-20 system. An electrode on the right mastoid (channel TP10) was used as a reference during online recording, and the ground electrode was located on the skull, 1cm posterior and 1cm lateral to the head centroid (Cz). The skin-electrode impedance was kept below 5". EEG data were acquired with an online notch filter (60Hz), and digitized at a sampling rate of 1000Hz. Three hundred epochs of 300ms (100ms baseline and 200ms after TS delivery) were recorded for each condition (TS alone, CS alone, and CS+TS at 0, 15, 20, 25, 30, 35ms ISIs). The order of conditions was randomized for each individual. Figure 4-3:  Custom 29 electrode set-up. Recordings from the target channel CP4 (circled in red) were analyzed in the current study. EEG data was referenced online to channel TP10, and re-referenced offline to channel AFz. The ground electrode (GND) was located 1cm posterior and 1cm lateral to the centroid (Cz). 58  SEPs were analyzed offline using the open source EEGLAB software (version 13) 206 running under the Matlab (version 7.14) environment. Raw EEG data were re-referenced to AFz, digitally high pass filtered (cutoff: 1Hz), cleaned from line noise (60Hz plus harmonics removed using the Cleanline plugin) and the 300 epochs of 300ms duration were averaged for each condition. Epochs with significant noise and/or artifact were objectively identified and rejected using the default automated thresholding method in EEGLAB (~17?8 /300 epochs rejected per trial). After visual inspection, a secondary 15Hz high pass filter was applied to all datasets in order to eliminate pervasive signal drift.  An asymmetry in the strength of TCI has been reported in the human motor system, such that inhibition sent from the ?dominant? hemisphere to the ?non-dominant? hemisphere is more marked than ?non-dominant? to ?dominant?, particularly in right handed individuals 207. Consequently, we opted to examine the influence of the left (dominant) S1 on the right (non-dominant) S1, rather than right to left which differs from the Ragert study 169. Thus, for the purpose of the current study, analysis was restricted to electrode CP4, overlying S1 of the right (target) hemisphere. In order to eliminate the potential influence of an ipsilateral component from the initial CS (right MN stimulation) on the subsequent contralateral response to the TS (left MN stimulation), the average ipsilateral SEP response from right MN stimulation (CS) at electrode CP4 was subtracted from the average raw SEP response from each CS+TS condition (CS+TS raw ? CS alone at CP4; see Figure 4-2 A).   Peak to peak amplitudes of five components (P14/N20, N20/P25, P25/N30, N30/P40, and P40/N60) of the SEP recorded over CP4 were identified manually based on plots of these subtracted values for each individual under each condition, according to the description by Ragert et al. (2011) 169. Specifically, the P14/N20 amplitude was calculated as the difference 59 between the N20 onset (or the positive peak of the preceding P14 component, if present) and the first sharp, negative peak (observed 16-20ms after stimulus onset). From that negative peak, the maximum subsequent positivity was identified as P25, and the difference in amplitude between them was calculated as the N20/P25 complex. The P25/N30 component was measured as the difference between the P25 peak and the maximum subsequent negativity, the N30/P40 component was the difference between N30 and the maximum subsequent positivity, and finally, the P40/N60 component was the difference between P40 and the maximum subsequent negativity (Figure 4-4).  Figure 4-4:  Peak-to-peak amplitudes were extracted manually as shown. 4.3.3 Statistical Analyses Descriptive statistics were examined for the amplitudes of each SEP component at each ISI, and outliers >2 standard deviations were removed (2.3% of the values). First, a two-way 5x7 repeated measures analysis of variance (ANOVARM) was performed using Component (P14/N20, N20/P25, P25/N30, N30/P40, P40/N60) and ISI (TS alone, 0, 15, 20, 25, 30, 35ms) as 60 within-subject factors. Component amplitude was the dependent measure. Second, five one-way ANOVARM?s were performed for each SEP component, with ISI (TS alone, 0, 15, 20, 25, 30, 35ms) as the independent variable and component amplitude as the dependent measure. Bonferroni adjusted alpha levels of .01 were used (.05/5). Greenhouse-Geisser corrections for non-sphericity were applied when necessary (i.e. when the significance of the Mauchly statistic was <0.05). Hypothesis-driven paired samples t-tests were then performed to identify differences in specific SEP component amplitudes. Significance levels were left uncorrected for planned comparisons 208. 4.4 Results The distinct positive and negative peaks of the SEPs were considered visually distinguishable for each individual at each condition, except for the TS-only condition in one person. In that particular case the electrical line noise drastically masked the components of the SEP and the trial was excluded from the analyses. The mean peak-to-peak amplitudes for each component at each ISI are reported in Table 4-1. Table 4-1:  Mean peak-to-peak SEP amplitudes ? SD Values were recorded from channel CP4 over the right S1 for unilateral (TS alone) and bimanual (synchronous 0ms and asynchronous separated by 15-35ms intervals) median nerve stimulation. Values are mean ? SD. [*p<0.05; **p<0.01 relative to the 0ms condition] 61 A two-way ANOVARM revealed a significant ISI*Component interaction (F24,96=2.866, p=0.000). Separate one-way ANOVARM?s for each component revealed a significant effect of ISI for the short latency P14/N20 (F6,36=4.050, p=0.003), and N20/P25 (F2.067,14.471=8.155, p=0.004) components. A significant effect of ISI was not observed for any of the longer latency SEP components (P25/N30: F2.686,21.487=1.252, p=0.314; N30/P40: F2.472,17.304=2.006, p=0.158; P40/N60: F6,42 =2.000, p=0.087).  It is possible that the TS alone and 0ms conditions may have differed due to discrepancies in attention ? that is, an individual may be more likely to direct their attention to the hand being stimulated during the TS only condition, whereas their attention would more likely be divided when both hands were being stimulated simultaneously. Given this possibility, we wanted to compare the asynchronous CS+TS ISI conditions to the synchronous 0ms condition rather than the TS alone. Paired samples t-tests revealed no significant differences between any of the five SEP components in the TS alone condition compared to the 0ms condition (p>0.156). Therefore, the 0ms condition was used as the basis for all further comparisons. An example of these comparisons in a single subject is shown in Figure 4-5. Figure 4-5:  Representative SEP traces recorded from CP4 over right S1 from a single subject. The synchronous 0ms condition is plotted in blue, and the asynchronous CS+TS conditions at various ISIs are plotted in red.  62 Only the SEP components that demonstrated a significant main effect of ISI (P14/N20 and N20/P25) were considered for planned comparisons. The mean peak-to-peak amplitude of P14/N20 recorded at CP4 was significantly depressed at a CS+TS ISI of 25ms (t9=2.439, p=0.037), 30ms (t8=3.183, p=0.013), and 35ms (t8=2.987, p=0.017). No such changes were observed for CS+TS ISIs of 15 or 20ms (p>0.520; Figure 4-6 A). Moreover, compared to the 0ms condition, the N20/P25 component was significantly reduced at all CS+TS ISIs (15ms: t8=6.567, p=0.000; 20ms: t8=3.448, p=0.009; 25ms: t8=5.001, p=0.001; 30ms: t8=3.373, p=0.010; 35ms: t8=2.342, p=0.047; Figure 4-6 B). Figure 4-6:  Mean peak-to-peak amplitudes of the early cortical SEP components ? SD. (A) P14/N20 was significantly inhibited when the CS preceded the TS by 25-35ms relative to the 0ms condition (p=0.037 at 25ms, p=0.013 at 30ms, p=0.017 at 35ms). (B) N20/P25 was significantly inhibited at all asynchronous CS+TS conditions relative to the synchronous 0ms condition (p=0.000 at 15ms, p=0.009 at 20ms, p=0.001 at 25ms, p=0.010 at 30ms, p=0.047 at 35ms). 63 4.5 Discussion The main results of the current study were: (1) the mean peak-to-peak amplitude of the P14/N20 component was significantly decreased in CS+TS ISI conditions of 25, 30, and 35ms relative to 0ms, (2) the mean peak-to-peak amplitude of the N20/P25 component was significantly decreased in CS+TS ISI conditions of 15, 20, 25, 30, and 35ms relative to 0ms, and (3) the long latency SEP components did not appear to be influenced by the PMNSEP paradigm at any of the ISIs studied.  Ragert et al. (2011) 169 reported that a CS applied to the left MN attenuated the early cortical P14/N20 response of the left S1 to a subsequent TS applied to the right MN, but only at interstimulus intervals of 20 and 25ms. In the current study, we found a similar depression of comparable amplitude (~30% inhibition) of the P14/N20 response of the right S1 at an ISI of 25ms. Yet here we also report the novel finding that the inhibitory effect was extended to ISIs of 30 and 35ms as well. In addition, unlike Ragert et al. (2011) 169, we observed a clear attenuation of the N20/P25 complex at ISIs of 15, 20, 25, 30, and 35ms relative to 0ms.  While the short latency P14/N20 and N20/P25 components of the SEP are both believed to be generated by areas 3b of S1 209,210, they have slightly different origins. The subcortical P14 potential is evoked when an afferent sensory stimulus arrives at the thalamus, and the N20 occurs when the signal first reaches layer 4 of the cortex 209. The P25 component, on the other hand, is thought to be generated by the apical dendrites in cortical layers 2/3 of area 3b 209,211. Interestingly, neurons in layers 2/3 of the cerebral cortex are primarily involved in interhemispheric communication via the corpus callosum 212. If the mechanism underlying the somatosensory IHI reported in the current study is in fact occurring transcallosally, then it is not surprising that we observed an effect at the N20/P25 component in addition to P14/N20.  64 The time course of the inhibitory effect observed in the current study is of particular interest. We observed a robust depression of the N20/P25 complex by at least 20% (normalized to the 0ms condition) in all ten participants in the 15ms ISI condition, and this inhibition was consistently observed in the majority of them for the 20, 25, 30, and 35ms conditions. In contrast, the inhibition of the earlier P14/N20 component was not observed until the 25, 30, and 35ms ISI conditions. In other words, in the shorter duration ISI conditions (15 and 20ms), it appears that the CS had enough time to modify the later N20/P25 complex but not the earlier P14/N20. Thus, our data suggest that there is a minimum time window required for the influence of the CS to reach the opposite hemisphere. This observation is consistent with the hypothesis that an inhibitory signal is being transmitted between S1s via the corpus callosum (Figure 4-7). The transcallosal conduction time from one M1 to the other (short interval IHI) is approximately 6-13ms 178,213. Similarly, the transcallosal conduction time from one SII to the other can be as short as 10-16ms 197,198. There are few, if any, direct transcallosal pathways between areas 3b of S1 in each hemisphere, according to studies in non-human primates 190,191. Area 2 of S1, however, does have some reported callosal connections 190,195,214, and areas 3b and 2 are functionally interconnected within the same hemisphere 190,191. Transcallosal inhibition between S1s may therefore involve several synaptic steps (area 3b-2-2-3b), which may make it slightly slower and more variable than TCI between motor cortices. (See Figure 4-8 A for schematic of TCI pathways between S1s). Based on the current data and the findings of Ragert et al. (2011) 169, it seems that a CS+TS ISI of ~25ms is required before the P14/N20 complex is suppressed. The transmission time of the CS from the right MN to the contralateral left S1 (N20) is ~20ms. According to our proposed model, the signal would be transmitted from area 3b to 2, then across the corpus  65 Figure 4-7:  Proposed mechanism for the differential effects of interhemispheric inhibition on the short latency P14/N20 and N20/P25 somatosensory evoked potential (SEP) components, based on current observations. When the test stimulus (TS) was preceded by the conditioning stimulus (CS) by 15 or 20ms, the mean peak-to-peak amplitude of the cortical N20/P25 complex was significantly depressed (p=0.000 at 15ms, p=0.009 at 20ms). However when the TS was preceded by the CS by 25, 30, or 35ms, a significant depression was observed for both the thalamocortical P14/N20 complex (p=0.037 at 25ms, p=0.013 at 30ms, p=0.017 at 35ms) and the cortical N20/P25ms (p=0.001 at 25ms, p=0.010 at 30ms, p=0.047 at 35ms). This temporal pattern suggests that a minimum of ~15ms interhemispheric transfer time is required for inhibition to occur. [*p<0.05 uncorrected; ISI = Interstimulus interval] 66 callosum to activate inhibitory interneurons in the homologous area of right S1, causing an inhibitory effect prior to the onset of the N20 from the TS (which will arrive 45ms after the CS onset in the 25ms ISI condition). In that case, the transcallosal conduction time between S1s is estimated to be ~15-20ms. Interestingly, early anatomical studies estimated that the interhemispheric transfer time between primary somatosensory areas was likely between 13 and 26ms, based on data from the occipital system 215-217, and the comparable axonal diameter and distances 218. In the current study, we also report a novel finding that the N20/P25 complex is inhibited at a CS+TS ISI of 15ms. In the 15ms ISI condition, once the CS has evoked an N20 in the left S1 (20ms), and crossed the corpus callosum (~15-20ms), its inhibition in the right S1 will presumably take effect ~35-40ms after CS onset. However, by 35ms the N20 from the TS in the right S1 will have already been evoked, making it immune to the inhibitory effect. The P25 potential may still be susceptible, though, as it occurs 5ms later (Figure 4-7). It is important to note, however, that the mechanism proposed above is a hypothesis that requires additional testing. Furthermore, we have by no means ruled out alternative mechanisms by which somatosensory IHI may also occur. For example, after its initial arrival at the contralateral S1, suprathreshold MN stimulation reaches the adjacent M1 4ms later 202; therefore it is possible that some somatosensory IHI occurs via this S1-M1-M1-S1 pathway. However, IHI transmitted by this pathway would take 36-80ms 169, and is therefore outside of the scope of the ISIs studied here. Equivalently, despite the known intrahemispheric connections between S1 and SII, and the transcallosal connections between SII of each hemisphere, the SEP evoked in SII by MN stimulation occurs at least 40ms after that of S1 197. Therefore, the design of the current experiment does not allow us to draw conclusions about the potential S1-SII-SII-S1 IHI pathway. 67 Figure 4-8:  (A) Possible transcallosal pathways by which interhemispheric inhibition (-) of area 3b in the right S1 may occur. A conditioning stimulus (CS) delivered to the right median nerve is transmitted to area 3b of the contralateral left primary sensory cortex (S1) via the spinothalamic pathway (thick, single headed arrows). Direct callosal connections between the hand representations of area 3b in each hemisphere are sparse 190, thus it is likely that the signal is transmitted intrahemispherically prior to crossing the corpus callosum. The shortest pathway is via area 2 of S1; however it is possible that multiple pathways may be involved. Thin double headed arrows represent known intrahemispheric connections, and curved lines crossing the midline represent known transcallosal connections. (B) A drawing of the corpus callosum ? the largest commissural tract in the brain, connecting homologous areas of each hemisphere and regulating laterality of cortical activity. 68  One other possibility that has not been ruled out is that S1 inhibition may be mediated in part by the thalamus. All somatosensory signals entering the brain from the periphery synapse in the thalamus prior to reaching the cortex ? this generates the subcortical P14 potential of the SEP observed at S1. While it would be very informative to compare the amplitudes of P14 across conditions, this far field potential is widely distributed over the scalp 219 and is typically of very small amplitude (<0.5#V). In order to accurately record it, a non-cephalic reference is recommended 219, which we did not include in the current study design. Nevertheless, the observation that the N20/P25 complex was inhibited at shorter ISIs than the P14/N20 implies that the source of inhibition is more likely transcallosal rather than thalamic. The PMNSEP paradigm used here was very similar to that used by Ragert et al. (2011) 169, however the results of the current study are not identical. Certain methodological differences may have contributed to these differences. For example, we targeted the non-dominant right hemisphere whereas Ragert et al. targeted the dominant left hemisphere. As mentioned in the introduction, IHI in the motor system is reported to be stronger from the dominant to the non-dominant hemisphere; therefore we may have detected a stronger and longer-lasting inhibitory effect in our experiment. In addition, our MN stimulation intensities may have been stronger and more consistent throughout the experiment. Ragert et al. (2011) 169 report evoking a small but visible twitch in the thumb, and they did not change the intensity of stimulation once it had begun. On the other hand, we monitored MEPs online and made adjustments as necessary to maintain consistent 1mV peak-to-peak amplitudes in both hands throughout every trial in the experiment. Each of our trials contained more data, as we recorded 300 stimuli per condition, whereas Ragert et al. (2011) 169 recorded 150. The two experiments also differed in the specific placement of the reference and ground electrodes. There is currently no gold standard for where 69  the reference and grounds should be for EEG recording, but it is possible that using different locations may change the relative amplitudes of an evoked potential 220. Another difference between the studies was that we chose 0ms rather than TS alone as our basis for condition comparisons. This was justified by a non-significant difference between the SEPs evoked by the TS alone versus CS+TS simultaneously (0ms). Traditionally, it was considered unlikely that S1 neurons received input directly from ipsilateral stimulation 221. However, this issue has been reexamined of late 105,222,223. Single-cell recording studies in non-human primates have used unilateral hand stimulation to show that certain areas in S1 have bilateral hand receptive fields 214,222. In humans, some ipsilateral S1 activation has been observed using intracranial recordings 224, and magnetoencephalography 225-227. However, these smaller amplitude ipsilateral responses were only produced in a small number of participants, and occurred at longer latencies than the contralateral short latency S1 responses. Therefore, we did not expect that the potential ipsilateral response to MN stimulation would have a significant impact on the contralateral response when MN stimuli were presented simultaneously. The current study has limitations. Measuring peak-to-peak amplitudes of evoked cortical responses at a single channel is a simple, yet relatively crude way of inferring cortical processing mechanisms. However, we employed this method consistently and across all conditions.  Future work may analyze independent components and to localize their anatomical sources in effort to circumvent this issue. In addition, adding any type of filter to the raw data can alter the precise latencies of the peaks, which is not ideal for a study that considers very specific temporal windows. Nonetheless, we assume that since all raw data were filtered under the same conditions, it should not have resulted in a systematic difference. Other limitations of this study include the lack of behavioral data ? IHI in the motor system is known to correlate with 70  bimanual coordination and motor function. Whether this is also the case for somatosensory IHI has yet to be elucidated.   4.6 Conclusion In sum, the current study sought to elucidate whether direct transcallosal inhibition between homologous S1s may occur. Using a similar PMNSEP paradigm as described by Ragert et al. (2011) 169, we found that a conditioning stimulus presented to the left S1 depressed the early cortical SEP components of a subsequent test stimulus presented to the right S1. At shorter interstimulus intervals (15 and 20ms), the later N20/P25 was inhibited, whereas at longer intervals, both the thalamocortical P14/N20 and the cortical N20/P25 components were inhibited. We conclude that, analogous to the motor system 178, the degree of S1 IHI appears to depend on the temporal asynchrony of bilateral inputs, and the specific timing is reflective of a transcallosal mechanism. Future studies may consider not only whether this IHI has behavioral or perceptual correlates in healthy individuals, but also whether it may be used in neurological disorders such as stroke to predict functional impairment and potential benefit from different therapeutic techniques such as rTMS. 71 Chapter  5: Conclusions and General Discussion 5.1 Introduction The purpose of this thesis was to begin to probe into whether S1 might be an effective alternative target for rTMS + motor training interventions to enhance motor learning and recovery after stroke. First, we conducted a randomized, single blind experiment comparing the impact of active versus sham 5Hz rTMS over IL-S1 paired with practice of a skilled visuomotor reaching task in individuals with chronic stroke. Second, we performed a retrospective analysis of the participants from the first experiment who received active rTMS, to determine whether individual differences in morphology of the underlying cortex might be predictive of rTMS responsiveness. Third, we conducted an exploratory, paired median nerve sensory evoked potential (PMNSEP) paradigm in healthy individuals, to elucidate the neurophysiological mechanism of interhemispheric inhibition between the primary sensory cortices. The following chapter will summarize and discuss the major findings of each experiment, address the limitations, and provide recommendations for future investigations. 5.2 Summary of Findings 5.2.1 High Frequency rTMS Over IL-S1 Previous studies applying various high frequency (5Hz) rTMS parameters over the primary sensory cortex (S1) in healthy individuals have shown that that S1 excitability can be transiently enhanced with stimulation, as measured by increased amplitudes of early somatosensory evoked potential (SEP) components 89 which corresponds to enlarged cortical somatosensory maps and improved tactile perception 104,164. These findings coincide well with 72 our report that five sessions of 5Hz rTMS over the IL-S1 paired with skilled motor practice enhanced motor learning and improved cutaneous somatosensation in individuals with chronic stroke. While improvements were noted in several measures of motor performance over the course of the experiment, the specific change from baseline to retention (a measure of motor learning) was statistically significant for response time ? the mean sum of the participant?s reaction time + movement time for each targeting motion (Figure 2-2 B) Impaired response time is common after stroke, particularly when the stroke affects the basal ganglia 120. The majority of the participants in our study had lesioned basal ganglia (Table 2-2). Thus, the demonstration of significant reductions in response time in our sample is encouraging. We were surprised, however, that the benefits of active rTMS did not appear to generalize to measures of general motor function (abbreviated WMFT) or manual dexterity (BBT). While our functional tests used may not have been specific enough to detect subtle improvements in motor function, it is also possible that the benefits of our intervention were in fact limited to the learned motor task. Ultimately, while our results were promising, the effects were variable and non-transferable. This is a common theme in rTMS literature, and emphasizes the importance of understanding the factors that contribute to inter-individual variability in rTMS response. 5.2.2 Morphological Predictors of rTMS Response Given the considerable variability described in Chapter 2, the experiment described in Chapter 3 sought to establish a predictive model for responsiveness to 5Hz rTMS over IL-S1 based on individual variations in morphology of the underlying IL-S1 cortex. Using automated GM and WM segmentation and parcellation techniques to measure specific cortical areas from individual T1 anatomical MRI images, we found that the volume of WM in IL-S1 was positively 73 associated with motor learning related change in response time. This association was only observed in the group that received active stimulation. Furthermore, this association was observed specifically for the cortical area being stimulated (IL-S1), and not the neighboring IL-M1. Interestingly, no associations between GM volumes of IL-S1 and IL-M1 and response time change were observed. These findings highlight the importance of WM integrity to motor learning, which has been previously suggested in work from our lab 135. Furthermore, the observation that the association was specific to the cortex being stimulated sheds light on the potential mechanism behind the benefits of 5Hz rTMS over IL-S1. We propose that, by increasing IL-S1 excitability prior to practice of a motor task that requires repetitive sensory-motor integration, we may be facilitating the strengthening of connections and/or the formation of new connections between sensory and motor regions.  5.2.3 Mechanism of Somatosensory Interhemispheric Inhibition The motivation behind applying rTMS over M1 in individuals with stoke is highly influenced by the observation of an imbalance of cortical excitability between the ipsi- and contralesional hemispheres that correlates with poorer motor function 35. However, the interhemispheric balance between S1s is poorly defined, even in healthy individuals. Thus, in Chapter 4 we conducted an experiment comparing synchronous versus asynchronous sensory stimuli delivered to each hand, using EEG to measure differences in cortical S1 responses. Similar to a recent report by Ragert et al. (2011) 169, we found that the mean peak-to-peak amplitudes of short latency, cortical components of the SEP were reduced at select interstimulus intervals (ISIs). In particular, the cortical N20/P25 component was reduced at shorter ISIs, whereas the thalamocortical P14/N20 component reduced at longer ISIs, which is suggestive of a 74  transcallosal inhibitory mechanism. The rapid conduction time (~15ms) proposed in this experiment would suggest that the inhibition is occurring directly between S1s, rather than indirectly between secondary sensory or motor areas. Whether this method may be used in individuals with stroke to assess S1 IHI impairments similar to M1 has yet to be elucidated.  5.3 Synopsis The global message of this thesis is that S1 should be considered as a viable target for future rTMS trials as an adjunct therapy to rehabilitation after stroke. The term ?sensorimotor? is often used to describe the system involved in the voluntary production of coordinated movements. However, while they are heavily interconnected, the sensory and motor systems are anatomically and functionally distinct, and the consequences of stimulating one vs. the other may result in different behavioral outcomes. Given the heterogeneity of lesion type, size, and topography after stroke, perhaps different individuals may benefit from different types and target of stimulation. Developing the skills and knowledge to predict an individual?s potential to respond to stimulation based on biomarkers such as cortical morphology or physiological measures of IHI will be valuable to the field of neurorehabilitation.  5.4 Limitations Choosing S1 as a target for rTMS introduces some new challenges. First of all, there is an issue with identifying the precise target for stimulation. In the motor system, the ?hotspot? in M1 can easily be defined by identifying the area that elicits the largest motor evoked potential (MEP) in the muscle of interest at the lowest stimulator intensity. This process can be refined by using neuronavigation software (e.g. BrainsightTM) for stereotaxic guidance in order to ensure 75  stimulation consistency within and across sessions, as we do for our studies. However, many researchers employ the rather basic method of marking the M1 ?hotspot? directly on the skull or a tightly fitted cap with a pen, and holding the TMS coil over the markings. While that may have some use for M1, it becomes much more difficult to employ when attempting to simulate alternative cortical targets, such as S1. Using this method, some researchers will simply shift the coil ~2cm posterior and assume that they are over S1 89. Considering the differences in individual skull shape and size, and variations in the underlying cortex 141, optimal coil position can vary up to 2cm between individuals 228. This method is clearly not ideal. In our experiment, we used individual anatomical images imported into BrainsightTM to guide coil placement. However, without fMRI data to identify the hand representation within S1 for each individual, precise placement is not guaranteed. The use of fMRI is expensive and time-consuming, and was beyond the scope of the current study. Another challenge of studying S1 in this context is measuring changes cortical excitability. Using EEG to assess changes in SEP amplitudes is the method most commonly used, however it is currently not feasible to record SEPs while stimulating the cortex with TMS. EEG is also a fairly labor-intensive process that is prone to contamination by muscular artifacts and electrical line noise. Furthermore, SEPs may simultaneously be influenced by other factors besides rTMS, such as attention 205 and task relevance 167. Thus, they are not the most convenient measure of changes in S1 excitability. One alternative is to measure changes in peripheral somatosensation ? reflected either by decreased sensory threshold or increased sensory detection 105. However, individual reports of somatosensation are prone to subjectivity.  A general limitation of the current thesis is that, due to the small sample size in Chapter 2, we were unable to parse out other factors that may have contributed to some of the inter-76  individual variability. For example, there have been some reports of certain sex differences in neuroplasticity mechanisms 229 and in the effects of TMS on inducing cortical plasticity 230,231. Other factors such as attention 232,233, previous motor activity 234,235, and genetics 236 have also been reported to have some impact on the effectiveness of TMS to some degree 123.  5.5 Future Directions Considering S1 as a target for rTMS interventions, future studies are needed to determine optimal stimulation parameters for the rTMS paradigm. Specifically, stimulation intensity, duration, frequency, direction of current flow are all factors that should be considered. The stimulation parameters chosen for the experiment described in Chapter 2 were selected based on our past work showing a beneficial effect of stimulation over the dorsal premotor cortex in healthy individuals 50,106. We report a significant effect when it was applied over IL-S1 in individuals with chronic stroke, however it is possible that changing the parameters may change the observed results 237. In addition, the effects of applying an inhibitory frequency of rTMS over contralesional S1 should be investigated, especially since published preliminary results suggest that it may also be beneficial 54.   Once the effects of rTMS over S1 have been better established, a direct comparison between M1 and S1 stimulation should be conducted in order to parse out their potentially different mechanisms of action. Of course, S1 is just one of many cortical areas that may be considered for rTMS intervention. 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