Medicine, Faculty of
DSpace
UBCV
Aceves Serrano, Lucero Guadalupe
Doctor of Philosophy - PhD
University of British Columbia
Repetitive transcranial magnetic stimulation (rTMS) has been proposed as a therapeutic tool to alleviate symptoms of neurological and psychiatric disorders. Although the therapeutic potential of rTMS has been widely explored, the neurobiological basis of its effects is still not fully understood. This thesis used in vivo imaging techniques such as positron emission tomography (PET) and magnetic resonance imaging (MRI) in parallel with post-mortem evaluations to investigate the effects of a clinical course of theta burst stimulation (TBS) – a patterned form of rTMS – at the molecular and functional level in non-human primates (NHP). These techniques were employed to investigate rTMS-induced modulation of dopaminergic and glutamatergic neurotransmission, its effects on brain activity and connectivity, and glial reactivity modulation. Specifically, we evaluated the effects of rTMS in the healthy brain of NHP. Neuroimaging evaluations and cortical excitability assessments were performed before and one day after a clinical course of intermittent (iTBS), continuous (cTBS), or sham stimulation over the left motor cortex. Dopaminergic assessment using PET was also acquired immediately after the first stimulation session. Neurotransmission assessment revealed a decrease in dopamine release in the left and right putamen immediately after cTBS delivery, while no changes in neurotransmission were found in the striatum after multiple cTBS, iTBS, or sham sessions. Functional MRI revealed modulatory effects of cTBS and iTBS, but not sham delivery, between the regions of the cortico-striatal-thalamo-cortical motor loop. We found increased connectivity between the stimulated and the contralateral motor cortex. Furthermore, we found that baseline connectivity measurements were correlated to changes in dopamine release after a single stimulation session. Assessment of metabolic connectivity with PET revealed a brain-wide effect post-iTBS with no effects observed after cTBS and sham delivery. Finally, evaluation of glial reactivity with PET-PBR28 and MRS-myoinositol suggested no significant changes in glial activation after stimulation that would suggest neuroinflammation. Overall, this work suggests TBS induced long lasting changes in cortical excitability, functional and metabolic connectivity in the absence of neuroinflammatory response and lasting changes in striatal dopamine and glutamate.
Neuromodulatory effects of Theta Burst Stimulation, a molecular and functional assessment by Lucero Guadalupe Aceves Serrano B.Sc., Tecnologico de Monterrey, 2016 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Neuroscience) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) April 2023 © Lucero Guadalupe Aceves Serrano, 2023 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: Neuromodulatory effects of Theta Burst Stimulation, a molecular and functional assessment submitted by Lucero Guadalupe Aceves Serrano in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Neuroscience Examining Committee: Dr. Doris Doudet, Professor, Department of Neurology, UBC Supervisor Dr. Lara Boyd, Professor, Department of Physical Therapy, UBC Supervisory Committee Member Dr. Martin McKeown, Professor, Department of Neurology, UBC Supervisory Committee Member Dr. Jon Stoessl, Professor, Department of Neurology, UBC University Examiner Dr. John Kramer, Professor, Department of Anesthesiology, Pharmacology and Therapeutics, UBC University Examiner Additional Supervisory Committee Members: Dr. Vesna Sossi, Professor, Department of Physics and Astronomy, UBC Supervisory Committee Member Dr. Alex Mackay, Pofessor, Department of Physics and Astronomy, UBC Supervisory Committee Member iii Abstract Repetitive transcranial magnetic stimulation (rTMS) has been proposed as a therapeutic tool to alleviate symptoms of neurological and psychiatric disorders. Although the therapeutic potential of rTMS has been widely explored, the neurobiological basis of its effects is still not fully understood. This thesis used in vivo imaging techniques such as positron emission tomography (PET) and magnetic resonance imaging (MRI) in parallel with post-mortem evaluations to investigate the effects of a clinical course of theta burst stimulation (TBS) – a patterned form of rTMS – at the molecular and functional level in non-human primates (NHP). These techniques were employed to investigate rTMS-induced modulation of dopaminergic and glutamatergic neurotransmission, its effects on brain activity and connectivity, and glial reactivity modulation. Specifically, we evaluated the effects of rTMS in the healthy brain of NHP. Neuroimaging evaluations and cortical excitability assessments were performed before and one day after a clinical course of intermittent (iTBS), continuous (cTBS), or sham stimulation over the left motor cortex. Dopaminergic assessment using PET was also acquired immediately after the first stimulation session. Neurotransmission assessment revealed a decrease in dopamine release in the left and right putamen immediately after cTBS delivery, while no changes in neurotransmission were found in the striatum after multiple cTBS, iTBS, or sham sessions. Functional MRI revealed modulatory effects of cTBS and iTBS, but not sham delivery, between the regions of the cortico-striatal-thalamo-cortical motor loop. We found increased connectivity between the stimulated and the contralateral motor cortex. Furthermore, we found that baseline connectivity measurements were correlated to changes in dopamine release after a single stimulation session. Assessment of metabolic connectivity with PET revealed a brain-wide effect post-iTBS with no effects observed iv after cTBS and sham delivery. Finally, evaluation of glial reactivity with PET-PBR28 and MRS-myoinositol suggested no significant changes in glial activation after stimulation that would suggest neuroinflammation. Overall, this work suggests TBS induced long lasting changes in cortical excitability, functional and metabolic connectivity in the absence of neuroinflammatory response and lasting changes in striatal dopamine and glutamate. v Lay Summary Repetitive transcranial magnetic stimulation (rTMS) is a form of a non-invasive brain stimulation. It produces electrical currents in the brain that can modify brain activity. This technique has shown promise as an adjunct treatment to several brain disorders, but there is still much we don't know about what rTMS does to the brain. Here, we use two forms of non-invasive brain imaging techniques, positron emission tomography (PET) and magnetic resonance imaging (MRI), to evaluate the consequences of multiple sessions of rTMS on brain chemistry, the relationships between brain regions, and evaluate their possible negative side effects on brain tissue such as inflammation. vi Preface The work presented in the current thesis is based on unpublished work, two journal publications and collaboration between multiple researchers. The publications have been modified and expanded to make the dissertation more coherent. The author participated in the data collection process and was in charge of the analysis, the evaluation of the methods, and the production of the manuscripts. All NHP experiments were conducted following the guidelines and regulations from the Canadian federal government on animal welfare and were approved by the Committee on Animal Care at the University of British Columbia under the certificate number: A14-0318. Chapter 1 is based on: • Aceves-Serrano L, Neva JL, Doudet DJ. Insight Into the Effects of Clinical Repetitive Transcranial Magnetic Stimulation on the Brain From Positron Emission Tomography and Magnetic Resonance Imaging Studies: A Narrative Review. Front Neurosci 2022;16:1–22. https://doi.org/10.3389/fnins.2022.787403. The author collected and summarized the literature and drafted the manuscript. Dr. Doris Doudet and Dr. Jason Neva provided feedback and edited the manuscript. The study in Chapter 2 is based on: • Aceves-Serrano L, Neva JL, Munro J, Parent M, Boyd LA, Doudet DJ. Continuous but not intermittent theta burst stimulation decreases striatal dopamine release and cortical excitability. Exp Neurol 2022;354:114106. https://doi.org/10.1016/j.expneurol.2022.114106. The author participated in the data collection and was in charge of the analyses of the in vivo assessment and writing the manuscript. Dr. Doris Doudet designed the experiments with input vii from Dr. Lara Boyd. Jonathan Munro performed the immunofluorescence staining experiments and analysis in the laboratory of Dr. Martin Parent at Laval University. Drs. Jason Neva, Doris Doudet and the author performed cortical excitability measurements. Chapter 3 is based on unpublished work. The author conducted and designed the analysis and participated in the data acquisition and experiment implementation. Sharisse Lin aided in the preprocessing of the data. Dr. Justin Andrushko, Drs. Martin McKeown and Soojin Lee provided feedback on the analysis methods. Chapter 4 is based on unpublished work. The author contributed to the performance of experiments and in vivo image acquisition. The author carried out data analysis with input from Dr. Yilong Ma and Dr. Shichun Peng from the Feinstein Institute for Medical Research, New York. Chapter 5 is based on: • Aceves-Serrano L, Neva JL, Munro J, Vavasour I, Parent M, Boyd LA, Doudet DJ. Evaluation of neuroinflammation following a clinical course of TBS: a non-human primate study. Brain stimulation (under review). The author participated in the data collection and was responsible for data analysis and writing of the manuscript. Dr. Doris Doudet designed the experiments with input from Dr. Lara Boyd. Jonathan Munro performed immunofluorescence staining experiments and analysis in the laboratory of Dr. Martin Parent at Laval University. Dr. Irene Vavasour aided in the analysis of magnetic resonance spectroscopy data. Additionally, the analysis for Positron Emission Tomography images for Chapter 5 images was based on: viii • Aceves-Serrano, L., Sossi, V., & Doudet, D. J. (2021). Comparison of Invasive and Non-invasive Estimation of [11C]PBR28 Binding in Non-human Primates. Molecular Imaging and Biology, 0123456789. https://doi.org/10.1007/s11307-021-01661-6 The author participated in the data collection and was in charge of the analyses of the in vivo assessment and writing the manuscript. This work also included previously published data provided by Dr. Richard Carson from Yale. Dr. Doris Doudet and Dr. Vesna Sossi provided guidance during the image analysis processes and aided in the interpretation of the results. Finally, daily stimulation delivery was carried out by Chenoa Mah, Rick Kornelsen, and the author, supervised by Dr. Doris Doudet. Positron emission tomography was acquired with help from Carolyn English, and magnetic resonance images were acquired with the help of Laura Barlow. Chenoa Mah, Dr. Doris Doudet and the author performed animal preparation for the imaging sessions. The current work was supervised by Dr. Doris Doudet who designed the overall study, obtained funding and contributed to the interpretation of the results and editing of the manuscripts. ix Table of Contents Abstract ......................................................................................................................................... iii Lay Summary .................................................................................................................................v Preface ........................................................................................................................................... vi Table of Contents ......................................................................................................................... ix List of Tables .............................................................................................................................. xiv List of Figures ...............................................................................................................................xv List of Abbreviations ................................................................................................................ xvii Acknowledgements ......................................................................................................................xx Dedication ................................................................................................................................... xxi Chapter 1: Introduction ............................................................................................................... 1 1.1 A brief introduction to repetitive Transcranial Magnetic Stimulation ........................ 1 1.1.1 Repetitive Transcranial Magnetic Stimulation background ................................... 1 1.1.2 A brief history of TMS and rTMS .......................................................................... 3 1.1.3 Repetitive TMS procedures .................................................................................... 4 1.2 Clinical applications of rTMS ..................................................................................... 9 1.2.1 Major depressive disorder ....................................................................................... 9 1.2.2 Addiction............................................................................................................... 10 1.2.3 Schizophrenia ........................................................................................................ 10 1.2.4 Post-traumatic brain disorders .............................................................................. 11 1.2.5 Parkinson's disease ................................................................................................ 11 1.2.6 Stroke .................................................................................................................... 12 1.2.7 Chronic pain .......................................................................................................... 12 x 1.2.8 Clinical limitations ................................................................................................ 13 1.2.9 Repetitive TMS safety .......................................................................................... 14 1.3 Neuroimaging mechanism of action of rTMS .......................................................... 15 1.3.1 Neuroimaging introduction ................................................................................... 15 1.3.1.1 Positron emission tomography studies of neurotransmission ....................... 15 1.3.1.2 Magnetic resonance spectroscopy ................................................................. 17 1.3.1.3 In-vivo imaging of neural activity and functional connectivity.................... 17 1.3.2 Modulation of dopaminergic neurotransmission .................................................. 18 1.3.2.1 Healthy participants ...................................................................................... 18 1.3.2.2 Clinical populations ...................................................................................... 20 1.3.3 Modulation of glutamatergic and GABAergic activity ........................................ 22 1.3.3.1 Healthy participants ...................................................................................... 22 1.3.3.2 Clinical populations ...................................................................................... 23 1.3.4 Brain activity and rsFC modulation ...................................................................... 24 1.3.4.1 PET studies ................................................................................................... 24 1.3.4.1.1 Healthy subjects ...................................................................................... 24 1.3.4.1.2 Clinical populations................................................................................. 24 1.3.4.2 rsFC assessments .......................................................................................... 26 1.3.4.2.1 Healthy participants................................................................................. 26 1.3.4.2.2 Clinical populations................................................................................. 27 1.4 Lessons and limitations from rTMS neuroimaging studies ...................................... 30 1.5 Research Objectives and Thesis Outline................................................................... 31 Chapter 2: Evaluation of neurotransmission and cortical excitability post stimulation ........... 37 xi 2.1 Introduction ............................................................................................................... 37 2.2 Materials and Methods .............................................................................................. 40 2.2.1 Animals ................................................................................................................. 40 2.2.2 Stimulation and imaging timeline ......................................................................... 41 2.2.3 RMT measurement and TBS delivery .................................................................. 43 2.2.4 PET data acquisition and analysis......................................................................... 45 2.2.5 Responder and non-responder classification ........................................................ 47 2.2.6 Magnetic resonance spectroscopy ......................................................................... 48 2.2.7 Post-mortem analysis ............................................................................................ 51 2.2.8 Statistical analysis ................................................................................................. 52 2.3 Results ....................................................................................................................... 53 2.3.1 RMT changes ........................................................................................................ 53 2.3.2 Changes in raclopride BPND .................................................................................. 53 2.3.3 Responder and non-responder classification ........................................................ 54 2.3.4 Glutamate assessment ........................................................................................... 56 2.3.5 Post-mortem analysis ............................................................................................ 57 2.4 Discussion ................................................................................................................. 58 2.4.1 TBS modulation of cortical excitability ................................................................ 58 2.4.2 Acute TBS modulation of dopamine release ........................................................ 60 2.4.3 Chronic TBS modulation of dopamine release ..................................................... 62 2.4.4 Chronic TBS modulation of glutamatergic activity .............................................. 64 2.4.5 NHP in the study of rTMS and the effects of anesthesia ...................................... 64 2.5 Conclusion ................................................................................................................ 68 xii Chapter 3: Evaluation of functional connectivity ..................................................................... 69 3.1 Introduction ............................................................................................................... 69 3.2 Methods..................................................................................................................... 71 3.2.1 Functional MRI acquisition .................................................................................. 71 3.2.2 Image preprocessing ............................................................................................. 72 3.2.3 Seed-based analysis .............................................................................................. 73 3.3 Results ....................................................................................................................... 74 3.4 Discussion ................................................................................................................. 77 3.4.1 CSTC connectivity modulation............................................................................. 78 3.4.2 Interhemispheric connectivity ............................................................................... 80 3.4.3 Study limitations ................................................................................................... 81 3.5 Conclusion ................................................................................................................ 83 Chapter 4: TBS-specific metabolic patterns, a pilot study ....................................................... 85 4.1 Introduction ............................................................................................................... 85 4.2 Methods..................................................................................................................... 87 4.2.1 FDG acquisition .................................................................................................... 87 4.2.2 Image processing .................................................................................................. 89 4.2.3 Pattern Identification ............................................................................................. 89 4.2.4 Pattern expression assessment .............................................................................. 90 4.3 Results ....................................................................................................................... 90 4.4 Discussion ................................................................................................................. 92 4.4.1 Post iTBS metabolic pattern ................................................................................. 93 4.4.2 Sham and cTBS results ......................................................................................... 95 xiii 4.4.3 Methods for metabolic connectivity assessments ................................................. 96 4.5 Conclusion ................................................................................................................ 97 Chapter 5: Evaluation of markers for glial activation and cellular damage ............................. 99 5.1 Introduction ............................................................................................................... 99 5.2 Methods................................................................................................................... 102 5.2.1 Positron emission tomography ............................................................................ 102 5.2.2 Magnetic resonance spectroscopy ....................................................................... 103 5.2.3 Post-mortem evaluation ...................................................................................... 104 5.2.4 Statistical analysis ............................................................................................... 105 5.3 Results ..................................................................................................................... 105 5.3.1 [11C]PBR28 quantification .................................................................................. 105 5.3.2 NAA and mI concentrations ............................................................................... 108 5.3.3 Post-mortem evaluation ...................................................................................... 109 5.4 Discussion ............................................................................................................... 109 5.5 Conclusion .............................................................................................................. 114 Chapter 6: Conclusion and Future Work ................................................................................ 115 6.1 Findings summary ................................................................................................... 116 6.2 Future directions ..................................................................................................... 121 6.3 Conclusion .............................................................................................................. 122 Bibliography ...............................................................................................................................124 xiv List of Tables Table 5.1 Summary of Total Volume of Distribution................................................................. 106 Table 5.2 Summary of [11C]PBR28 distribution volume ratios. ................................................. 107 xv List of Figures Figure 1.1. Representation of the different frequencies and pattern of rTMS stimulation. ............ 5 Figure 1.2 TMS coils and the induced electric fields. .................................................................... 8 Figure 1.3 PET Radiotracers used in the evaluation of dopamine neurotransmission. ............... 16 Figure 1.4 Thesis overview ........................................................................................................... 31 Figure 1.5 Cortico Basal ganglia-thalamocortical circuits. .......................................................... 33 Figure 1.6 Overview of study design. ........................................................................................... 36 Figure 2.1 Chair and pole set up for awake theta burst stimulation. ............................................ 40 Figure 2.2 PET-raclopride evaluation. .......................................................................................... 43 Figure 2.3 Set up for RMT measurement. .................................................................................... 44 Figure 2.4 Representative motor-evoked potential response to TMS in a non-human primate. .. 45 Figure 2.5 Set up for magnetic resonance imaging and spectroscopy acquisition. ...................... 49 Figure 2.6 MRS voxel placement on putamen.............................................................................. 50 Figure 2.7 Resting motor threshold (RMT) measurements before and after stimulation. ............ 53 Figure 2.8 [11C]Raclopride binding potential in putamen before and after stimulation ............... 54 Figure 2.9 [11C]Raclopride striatal binding potential (BPND) in cTBS responders. ..................... 55 Figure 2.10 Glutamate concentration in putamen before and after stimulation. .......................... 56 Figure 2.11 In vivo and post-mortem markers for dopamine neurotransmission. ........................ 58 Figure 3.1 Coronal view of 112RM-SL atlas with the seed's mask. ............................................. 73 Figure 3.2 Functional connectivity modulation. ........................................................................... 75 Figure 3.3 RM ANOVA assessment of functional connectivity. ................................................. 76 Figure 3.4 Relation of acute dopamine modulation and baseline connectivity. ........................... 77 Figure 4.1 Intermittent TBS-specific metabolic pattern ............................................................... 91 xvi Figure 4.2 First principal component from cTBS and iTBS evaluation ....................................... 95 Figure 5.1 PET and post-mortem measurements of TSPO ......................................................... 108 Figure 5.2 Metabolite concentration in Putamen ........................................................................ 109 Figure 6.1 Summary of results .................................................................................................... 115 xvii List of Abbreviations ACC Anterior Cingulate Cortex AMT Active Motor Threshold CBF Cerebral Blood Flow Cr Creatine CSF Cerebrospinal Fluid CSTC Cortico-Striatal-Thalamic-Cortical loop cTBS Continuous Theta Burst Stimulation D2R D2 receptor DLFPC Dorsolateral Prefrontal Cortex DVR Distribution Volume Ratio EEG Electroencephalography FOV Field of View FDG [18F]-2-deoxy-2-fluoro-D-glucose FSL FMRIB Software Library GABA Gamma-aminobutyric Acid Glx Glutamate and Glutamine GM Grey Matter HF High-frequency ICA Independent Component Analysis IM Intramuscular IRCA Interregional Correlation Analysis iTBS Intermittent Theta Burst Stimulation xviii IV Intravenous LF Low-frequency MEP Motor Evoked Potential mI Myoinositol MRI Magnetic Resonance Imaging MRS Magnetic Resonance Spectroscopy MSO Maximal Stimulator Output NAA N-acetyl-aspartate NAAG N-acetyl-aspartate and N-acetyl-aspartate glutamate NHP Non-human Primates NMDA N-methyl-D-aspartate PCA Principal Component Analysis PCr Phosphocreatine PET Positron Emission Tomography PTSD Post-traumatic Stress Disorder QPS Quadripulse Stimulation RMT Resting Motor Threshold ROI Region of Interest rsFC Resting-state Functional Connectivity rTMS Repetitive Transcranial Magnetic Stimulation SSM Scale Sub-profile Model TBS Theta Burst Stimulation TMS Transcranial Magnetic Stimulation xix TR Repetition Time TSPO Translocator Protein VT Total Volume of Distribution WM White Matter xx Acknowledgements First and foremost, I would like to express my deepest gratitude to Dr. Doris Doudet, my supervisor, for her unwavering support throughout my PhD journey. I am particularly grateful for her mentorship and her genuine interest in both my professional and personal development. Thank you for opening doors for me and for being so generous with your time. Your dedication to the advancement of research and your support in the development of young researchers is truly admirable. I would also like to extend my sincere gratitude to Drs. Vesna Sossi and Lara Boyd for welcoming me into their laboratories and providing me with the opportunity to enhance my research experience. My thanks also extend to the other members of my committee, Dr. Martin McKeown and Dr. Alex Mackay, for their valuable time, feedback and encouragement. I would like to extend my appreciation to Joyce Lam and Jessie Fu for the memorable lunches and chats. My gratitude also goes to Chenoa Mah and Rick Kornelsen for their invaluable support during the data acquisition process. Additionally, I would like to thank the members of the UBC PET and the UBC MRI imaging group for their support. Lastly, I am forever grateful to family. To my mom for teaching me and my brothers to always keep moving forward. To my dad, for encouraging me to keep studying. To my brothers, for opening paths for me. Finally, I’m thankful to my husband, for always cheering me up, believing in me and supporting me. xxi Dedication Dedicated to my mom, the exemplification of perseverance and strength. 1 Chapter 1: Introduction 1.1 A brief introduction to repetitive Transcranial Magnetic Stimulation 1.1.1 Repetitive Transcranial Magnetic Stimulation background Transcranial magnetic stimulation (TMS) is a non-invasive brain stimulation technique that induces an electrical current in the brain by delivering rapidly-changing magnetic field pulses. Briefly, electric pulsed are delivered through the TMS coil that, in turn, produces a fluctuating magnetic field perpendicular to the plane of the coil. These magnetic pulses pass through the scalp and skull and reach the brain cortex inducing an electrical current that flows through the tissue (Hallett 2000; Fitzgerald et al. 2006). Ultimately, the generated current can depolarize cell membranes and produce action potentials. The power of the delivered magnetic field decreases exponentially as the distance to the coil increases, generating a stronger current closer to the coil. Thus, most available TMS coils have a penetration restricted to the brain cortex and reach as deep as 1.5 to 2 cm from the scalp (Deng et al., 2013). However, the development of newer coils that enable the stimulation of deeper structures (Harmelech et al. 2021). Single and paired-pulse TMS can be used to study intracortical, cortico-cortical, and cortico-subcortical interaction, assess motor function, and evaluate the relation between brain activity and behaviour (Rotenberg 2010; Horvath et al. 2011). When single pulses of TMS are delivered over the motor cortex, a motor response is induced and is recorded as a motor-evoked potential (MEP) using electromyography (EMG) in a peripheral muscle corresponding to the stimulated motor cortex region. Similarly, phosphenes (which are sensations of flashes of light) are produced when a single TMS pulse is delivered over the primary visual cortex. MEP and phosphenes are often used to determine the stimulation intensity needed for cortical activation by TMS pulses (Merabet et al. 2003; Rotenberg et al. 2014). Cortical reactivity can also be assessed 2 using electroencephalography (EEG) to measure TMS-evoked potentials (Ahn and Fröhlich 2021). TMS can be used to determine corticospinal excitability by identifying the motor threshold, assessed in a muscle at rest (resting motor threshold, RMT) or during voluntary contraction (active motor threshold, AMT). RMT is defined as the minimal intensity of a single pulse of TMS required to elicit an MEP with a peak-to-peak amplitude ≥ 50 µV in at least 5 out of 10 consecutive trials (Boroojerdi et al. 2001). AMT is recorded during an isometric contraction of 5-20% of the maximal voluntary contraction, and a threshold is established when a peak-to-peak MEP amplitude ≥ 200 µV in at least 5 out of 10 consecutive trials is recorded (Berardelli et al. 2008; Boyd et al. 2014; Auriat et al. 2015). Similar to single-pulse TMS, paired-pulse TMS provides a non-invasive method to evaluate cortical excitability, specifically the excitability of cortico-cortical connections (Di Lazzaro et al. 1998; Kossev et al. 2003). Paired-pulse TMS consists of two sequential pulses separated by a variable interstimulus interval (ISI). This pair of stimuli can activate inhibitory and facilitatory cortico-cortical depending on the ISI used. Repetitive TMS (rTMS) consists of a train of TMS pulses delivered at the same intensity over a single cortical region. The frequency of the delivered pulses typically ranges between 1 and 50 Hz. Repetitive TMS can modulate cortical excitability and its effects can last beyond the stimulation period which makes it an appealing therapeutic tool for neuropsychiatric and neurophysiological disorders (Fitzgerald et al. 2006; Wassermann and Zimmermann 2012; Rehn et al. 2018; Rossi et al. 2021). 3 1.1.2 A brief history of TMS and rTMS In 1831 Faraday described the relationship between electrical energy and magnetic fields, describing the electromagnetic induction phenomenon (Faraday 1839). Faraday's Law of Induction states that a current is induced in a conductor exposed to a changing magnetic field. Using this principle, Tony Barker created a focal electromagnetic stimulation device that induces current down to the spine when placed on top of the scalp, the first TMS device (Barker et al. 1985). TMS stimulation induced movement of the leg by delivering a single pulse of magnetic stimulation, showing for the first time TMS-induced modulation of activity in regions distal from the targeted area. Work from Barker prompted the development of TMS devices and protocols such as paired-pulse TMS in 1993 (Kujirai et al. 1993) and rTMS in 1997 (Chen et al., 1997). Early paired-pulse studies targeted the motor cortex and found that delivering two pulses with an interstimulus of 1 to 15 milliseconds could either suppress or potentiate motor response (Kujirai et al., 1993; Sanger, Garg, & Chen, 2001; Ziemann, Corwell, & Cohen, 1998). The first rTMS study demonstrated that repeated pulses could induce cortical excitability depression that lasted 15 minutes after the end of stimulation (Chen et al., 1997). The interest and applicability of rTMS quickly grew, prompting the development of improved TMS equipment and new stimulation protocols (for review, see (Lefaucheur et al., 2020; Platz, 2016; Rotenberg et al., 2014; Ziemann, 2017). In the last 20 years, other paradigms that can alter local cortical excitability such as Theta burst stimulation (TBS) and quadripulse rTMS (QPS) (Hamada et al. 2007, 2008) have been developed. QPS was described by Hamada et al. (Hamada et al. 2008; Hamada and Ugawa 2010) as four equal monophasic TMS pulses delivered with an interstimulus interval of 1.5 to 1250 4 milliseconds. When delivered at a repeated rate, QPS can modulate cortical excitability. TBS was first used in 2005 (Huang, Edwards, Rounis, Bhatia, & Rothwell, 2005); its primary distinction from other rTMS protocols is its high frequency (50 Hz) and speed of delivery. TBS stimulation was derived from rodent studies where theta burst discharges (4-7 Hz) were recorded from the hippocampus during exploratory behaviour (Diamond et al. 1988). These theta-burst-patterns were initially used to induce plasticity in animal brain slices and were ultimately adjusted to match the capabilities of the then-available TMS machines. Other approaches, such as the individualization of rTMS parameters (Padberg et al. 2017) and delivery of intense rTMS (accelerated rTMS) (Holtzheimer et al. 2010), were later investigated in hopes of optimizing rTMS treatment efficacy. The development of newer protocols and research regarding their putative mechanisms has prompted the use of rTMS as a therapeutic intervention, and its applicability continues to grow to date. 1.1.3 Repetitive TMS procedures The diversity of rTMS protocols has enabled wide applicability in the study and treatment of multiple brain disorders (Fig. 1.1). Unlike single and paired-pulse TMS, rTMS can induce cortical effects that outlast the stimulation duration. Several rTMS parameters can be modified depending on the target population, including the stimulated area, stimulus frequency, intensity, and the total number of stimuli. In addition, rTMS can induce facilitative or suppressive effects in the cortex depending on the stimulation frequency and, in the case of TBS and QPS, the inter-train interval (the “pattern”). Conventionally, low-frequency rTMS (LF-rTMS, ≤1 Hz) is considered to decrease cortical excitability, while high-frequency rTMS (HF-rTMS, ≥5 Hz) is considered to increase it (Houdayer et al. 2008). 5 Figure 1.1. Representation of the different frequencies and pattern of rTMS stimulation. Left panner shows the "conventional" stimulation methods (i.e., low and high frequency). Right side illustrated the different available pattern forms of rTMS: continuous theta burst stimulation (iTBS), intermittent TBS, intermediate theta burst stimulation and quatripulse stimulation (QPS), and its different inter-stimulation interval (ISI). Reprinted with permission from (Rossi et al. 2009). In addition to the conventional HF- and LF-rTMS, there are several patterned protocols with more complex timings, such as TBS and QPS. TBS and QPS can increase and decrease cortical excitability by varying the interval between patterns of stimuli (i.e., bursts). TBS is delivered in bursts of 3 stimuli at 50 Hz every 2 seconds and can be delivered continuously (cTBS) or intermittently (iTBS), inducing a decrease or increase in cortical excitability, respectively. As its name indicates, cTBS involves the application of continuous TBS pulses for 20 to 40 seconds. In contrast, iTBS consists of the delivery of TBS pulses in a 10-second intertrain interval, with 2 seconds of stimulation and 8 seconds of no stimulation typically delivered for a total of 190 seconds (Huang et al., 2005). The main advantage of TBS is its 6 application speed, making it more tolerable for participants and easier to apply in awake animals. QPS consists of bursts of four monophasic magnetic pulses at 0.5-millisecond intervals for 30 minutes. Like TBS, QPS can induce an increase or decrease in cortical excitability depending on the inter-pulse interval; a short interval (smaller than 15 ms) increases excitability, while QPS delivered with larger intervals (between 15 and 100 ms) decreases it (Hamada et al. 2008). To date mechanisms behind the effects of rTMS in cortical excitability are still not clear. Single pulses of TMS can induce a current that last for about 200 microseconds, which is capable of depolarizing axons of neurons located in the cortex (Platz 2016). This pulse of stimulation can modulate activity of inhibitory and excitatory neurons underneath the coil. Thus, the effects of repeated pulses (rTMS) are the summation the modulation of inhibitory and excitatory neurons, as the excitability of neurons is altered due to a shift in the ionic balance of the stimulated neurons (Kuwabara et al. 2002) While the exact underpinnings of rTMS are still unclear, the effects of rTMS are thought to be related to synaptic plasticity since similar stimulation protocols of high and low frequency stimulation in vitro induce long-term potentiation (LTP) and long-term depression (LTD) of synaptic transmission (Bliss and Lømo 1973; Tsumoto 1992). LTP and LTD are forms of synaptic plasticity that can be experimentally achieved in brain slices through tetanic electrical stimulation (Dudek and Bear 1992; Bliss and Collingridge 1993). Similar to what is observed after rTMS, high frequency electrical stimulation induces LTP effects while low frequency electrical stimulation results in LTD. Thus, it is hypothesized that these synaptic changes are mediated through similar mechanisms. 7 Another similarity between LTP and LTD responses and plasticity induced by rTMS is the involvement of N-methyl-D-aspartate (NMDA) receptors. Studies of rTMS have shown that the cortical excitability modulatory effects of different forms of rTMS are related to NMDA receptor activity, as studies have reported NMDA receptor antagonist can block rTMS-induced plasticity (Huang et al., 2007; Stefan et al., 2002; Wolters et al., 2003). NMDA receptors are located in the post-synaptic membrane, they have a cationic channel that opens when the membrane is depolarized, allowing the entrance of calcium ions, eventually leading to the induction of LTP if the calcium flow is rapid, and LTD if the flow of calcium is slow (Cooke and Bliss 2006). In the case of patterned rTMS, the distinction between the synaptic plasticity effects of HF and LF stimulation is no longer present, making it distinct to the observations made from tetanic electrical stimulation. Thus, the effects of inhibitory and excitatory pattern protocols can not be derived from processes related to the stimulation frequency. Specifically in the case of TBS, its inhibitory and excitatory effects are thought to be derived from the capacity of TBS to induce short-latency facilitation with a concurrent longer-latency and weaker inhibition (Huang et al., 2011) Ultimately, the observed effect of TBS depends on whether the stimulation protocol favors the accumulation of fast-rising short-latency excitation or slow-rising long-latency inhibition. For example, the intermittent delivery of TBS bursts (i.e., iTBS) would promote the summation of the facilitatory effects enabling LTP-like effects. Continuous TBS delivers TBS bursts for long enough to allow the build-up of inhibitory effects, overcoming the facilitatory effect and inducing an LTD-like effect. There is still much to know regarding the underpinnings of rTMS effects, and while human studies are ethically and technically challenging and thus 8 limited, the availability of non-invasive assessments has enabled the expansion of current understanding of rTMS delivery outcomes. Repetitive TMS effects are also dependent on the coil used. There are multiple coils designs and sizes available for rTMS delivery. Using a different coil affects the size, shape, and depth of the induced electrical field in the brain (Fig. 1.2) (Deng et al. 2013). Current human studies mainly use a figure-eight coil, which reaches cortical stimulation depth ranging from 1 to 1.9 cm into the cortex and an area of approximately 2-3 cm2 (Deng et al. 2013). Circular coils can induce deeper stimulation and are used in cases where the depth of stimulation is more critical than focality. Deeper brain structures can also be targeted using specialized coils, such as an H-coil, enabling the targeting areas located > 2.4 cm into brain matter bilaterally (Deng et al. 2013). Figure 1.2 TMS coils and the induced electric fields. Simulation models of the induced electric fields from seven different TMS coils over a spherical model of the head. A quarter of the brain sphere is removed to visualize the electric field in depth. The electric field magnitude is 9 normalized to the peak electric field on the cortical surface (1.5cm), max (|E1.5cm|). a) 90 mm circular coil, (b) H1 coil, (c) crown coil, (d) 70 mm figure-8 coil, (e) iron core figure-8 coil, (f) double cone coil, (g) stretch C-core coil. Reprinted with permission from (Deng et al. 2014). 1.2 Clinical applications of rTMS Because rTMS can be applied non-invasively, it is an attractive intervention for psychiatric and neurophysiological disorders. Repetitive TMS can be delivered as an intervention for a given brain disorder to target: 1) affected region, 2) distant regions, or 3) distributed regions (Rotenberg et al. 2014). The direct targeting paradigm aims to modulate abnormal cortical excitability to bring it to "normal" levels. Distant region targeting aims to modulate activity in brain regions functionally connected to the dysfunctional area. Finally, rTMS delivery for distributed modulation aims to induce distributed modulation across the brain in a network-specific manner to normalize abnormal processes (Rotenberg et al. 2014). Depending on the therapeutic applicability and the disorder, different rTMS protocols can be selected. 1.2.1 Major depressive disorder Major depressive disorder treatment was one of the first therapeutic applications of rTMS. While the pathophysiology of major depressive disorder is still not fully understood, studies have shown that patients present hypoactivity in the left dorsolateral prefrontal cortex (DLPFC) (Alcaro et al. 2010). Facilitatory rTMS over the left or inhibitory rTMS over the right frontal cortex has been used to target abnormal cortical activity (Fitzgerald et al. 2009; George et al. 2010). In a controlled randomized crossover design, Pascual-Leone and colleagues demonstrated that delivery of 10-Hz rTMS significantly decreases depression scores in patients with drug-resistant depression (Pascual-Leone et al. 1996). This study led to the evaluation of 10 rTMS clinical applicability in patients with mood disorders and eventually deriving in a large-scale controlled study that supported the FDA approval of HF-rTMS as a treatment for drug-resistant depression (O'Reardon et al., 2007; George et al., 2010). To date, this is the only FDA and Health Canada approved therapeutic application of rTMS. The applications of rTMS discussed below cite experimental studies as rTMS has yet to be approved as a therapeutic intervention in disorders other than drug resistant depression. 1.2.2 Addiction Addiction is a complex disorder involving several neural pathways; the main implicated pathways are those from the meso-cortico-limbic system (Koob and Volkow 2010). This condition is characterized by the disruption and dysregulation of dopaminergic activity induced by exposure to addictive substances (Volkow et al. 2007). Studies in patients with alcohol and nicotine dependency and cocaine addiction have also shown abnormal cortical excitability (Ziemann et al. 1995; Boutros et al. 2001; Sundaresan et al. 2007; Lang et al. 2008; Nardone et al. 2010). Thus, the delivery of rTMS is thought to modulate connectivity between regions of the mesolimbic system and directly target cortical areas to alleviate symptoms by altering activity in relevant cortices, such as the hypoactive frontal cortex (Hu et al. 2019). 1.2.3 Schizophrenia Schizophrenia symptoms are typically divided into two categories: positive and negative. Pathophysiological models of schizophrenia have pointed to an imbalance in cortical excitability where sufferers of negative symptoms show reduced cortical activation (Reid et al. 2002), whereas positive symptoms are derived from hyperexcitability (Puri et al. 1996; Daskalakis et al. 11 2002; Fitzgerald et al. 2002). Repetitive TMS has been used to target these excitability imbalances directly. Studies have suggested that LF-rTMS and cTBS protocols might help treat auditory hallucinations, a positive schizophrenia symptom (Aleman et al. 2007; Plewnia et al. 2014; Koops et al. 2016; He et al. 2017). In the case of negative symptoms such as depression, HF-rTMS has been shown to induce significantly relevant improvement (Zhao et al. 2014; Quan et al. 2015). 1.2.4 Post-traumatic brain disorders Anxiety disorders such as post-traumatic stress disorder (PTSD) are characterized by intrusive thoughts, nightmares, flashbacks, and withdrawal. Imaging studies have shown faulty communication between the amygdala, hippocampus, and the anterior cingulate cortex of individuals with PTSD (Rauch et al. 2006), as well as other regions from the default mode network, central executive network, and the salient network (Kunimatsu et al. 2020). Thus, most rTMS interventions in patients with PTSD indirectly target these regions by stimulating the dorsolateral prefrontal cortex (DLFPC) (Rosenberg et al. 2002; Kozel et al. 2019; Kan et al. 2020; Wilkes et al. 2020). 1.2.5 Parkinson's disease Parkinson's disease is characterized by a progressive loss of dopaminergic neurons in the substantial nigra, disrupting the activity in regions withing the basal ganglia-thalamo-cortical motor loop and related regions (Burciu and Vaillancourt 2018). Parkinson's patients manifest various motor symptoms, such as bradykinesia, tremors, rigidity, and gait difficulties (Moustafa et al. 2016). While Parkinson's motor symptoms are the most clinically evident, non-motor signs 12 such as cognitive dysfunction and depression are also prominent in Parkinson's patients (Lefaucheur 2005; Helmich et al. 2006). Thus, studies have targeted several cortical regions with rTMS, such as the motor and premotor cortex, the DLPFC, and the cerebellum, to alleviate motor and mood affections (Huang et al. 2012; Chou, Hickey, et al. 2015; Brys et al. 2016; Makkos et al. 2016; Lefaucheur et al. 2020). 1.2.6 Stroke Studies have suggested a shift in sensorimotor cortical excitability in both hemispheres (Dijkhuizen et al. 2003; Ward et al. 2003; Altman et al. 2019), where excitability decreases in the affected region and increases in the unaffected homolog (Huynh et al. 2016). Thus, LF-rTMS delivery over the unaffected hemisphere has been used to improve motor performance by rebalancing the excitability of the hemispheres (Lefaucheur 2006a). While fewer studies have delivered HF-rTMS over the lesioned hemisphere, beneficial results using this method have also been reported (Lefaucheur et al. 2014). 1.2.7 Chronic pain Chronic pain research suggested that the disorder might be associated with maladaptive plastic changes in the central and peripheral nervous system (Fregni et al. 2007). Several areas, including limbic, thalamic, and cortical regions, such as the sensorimotor, insular, parietal, and prefrontal cortex, have been suggested as regions contributing to a state of over-reactivity (May 2007; Zippo et al. 2011; Goossens et al. 2018; Ong et al. 2019). Researchers have explored the potential of rTMS when applied over the motor cortex to target pain-modulating areas such as the thalamic and limbic regions (Lefaucheur et al. 2012, 2020; Ma et al. 2015; Moisset et al. 13 2016). Based on positive results from epidural motor cortex stimulation (Tsubokawa et al. 1991), the motor cortex has been mainly targeted in studies of the effects of rTMS on pain, and several studies have confirmed its analgesic effects (Lefaucheur et al. 2001; Khedr et al. 2005; Lefaucheur 2006b). 1.2.8 Clinical limitations As a non-invasive and relatively easy-to-deliver intervention, rTMS has shown promise in treating multiple neuropsychiatric and neurological disorders, as discussed in the previous section. However, despite increasing research efforts, important limitations still exist. The major drawback to wide acceptance of rTMS in more clinical contexts is its variability. Indeed, both clinical and non-clinical studies have reported large variability in response across individuals, with some experiencing symptomatic improvement while others do not (Hildesheim et al. 2022; Gogulski et al. 2023). The origin of this variability is unclear (please see Discussion) and this poses a challenge in predicting treatment outcomes and determining appropriate stimulation protocols. In an effort towards standardizing rTMS protocols, guidelines for the clinical delivery of rTMS have been proposed (Lefaucheur et al. 2020) but the optimal stimulation parameters for different disorders are still not determined. While parameters for drug-resistant depression have been established and approved by the FDA and Health Canada, there is no consensus on the optimal rTMS treatment (i.e., frequency, intensity, and duration) for other disorders. Establishing such parameters from a litterature review can be particuarly challenging as studies are heterogenous, using different protocols and including patients at different disorder stages, limiting the comparability of results. 14 Thus, much research is still needed before rTMS can be accepted as an effective clinical intervention for disorders other than drug resistant depression, but the potential and advantages of the intervention prompt further research as its benefits outweight the limitations. 1.2.9 Repetitive TMS safety As illustrated in the previous sections, rTMS is a promising therapeutic tool and has the potential as an intervention in a wide range of brain disorders. Furthermore, rTMS stimulation is well tolerated by patients, and given its non-invasiveness, it presents limited safety risks compared to invasive stimulation methods such as deep brain stimulation. The risk of seizure is the most severe acute adverse effect of rTMS delivery. Several cases of seizure induction were reported in early rTMS studies, but the number of studies compared to the small number of seizures suggests the risk is low (Rossi et al. 2009). The propensity for seizures has decreased since the definition of safety limits (Rossi et al. 2009, 2021). Other acute risks of rTMS delivery are mild and mostly related to patient discomfort, such as neck pain and headache, which tend to be derived from head posture and pressure on the scalp. While reports on participant discomfort and seizure incidence agree that acute rTMS delivery is generally safe and there are no demonstrated permanent adverse events, there are limited studies of the physiological effects of multiple sessions of rTMS and long-term follow-up studies evaluating the rTMS safety. In addition, as rTMS technology and paradigms are developed, researchers must stay vigilant as there might be unexpected and still unknown risks (Rossi et al. 2021). 15 To address this concern, a few animal studies have evaluated the impact of stimulation on neuroinflammation by evaluating markers for glial activation (Liebetanz et al. 2003; Zorzo et al. 2019). While these studies have shown rTMS does not induce neuroinflammation, as a rodent study, the interpretation of their findings is limited. Furthermore, the authors employed rTMS protocols that are not typically delivered in a clinical setting. Thus, further studies are necessary to investigate the safety of multiple sessions of rTMS, especially as clinical courses of stimulation are being delivered to vulnerable patient populations, including the elderly. 1.3 Neuroimaging mechanism of action of rTMS 1.3.1 Neuroimaging introduction Non-invasive neuroimaging allows for the assessment of neurophysiological processes in vivo and has greatly advanced the field of neuroscience. Magnetic resonance imaging (MRI) and positron emission tomography (PET) have permitted the exploration of functional, structural, chemical, and molecular components of human and non-human neurophysiology. In the study of non-invasive stimulation, MRI and PET have been used to evaluate on-line, short-term, and long-term effects of these stimulation techniques, including rTMS. 1.3.1.1 Positron emission tomography studies of neurotransmission PET imaging relies on the detection and localization of molecules (e.g., receptor/transporter agonists or antagonists, enzymatic precursors, etc.) labeled with a radionuclide. Various radiotracers can be used to monitor specific proteins and neurochemical processes in the living brain non-invasively. PET studies of rTMS have been heavily focused on evaluating its effects on endogenous neurotransmitters, mainly dopamine (Fig. 1.3). The majority 16 of such studies use [11C]raclopride, a D2/3 receptor antagonist (Laruelle 2000), to assess dopamine D2/3 receptors density as well as changes in dopamine release in the striatum, while evaluation of extrastriatal dopamine can be assessed using higher-affinity receptor radioligands like [18F]fallypride (Hernaus and Mehta 2016), and [11C]PHNO (Wilson et al. 2005). Figure 1.3 PET Radiotracers used in the evaluation of dopamine neurotransmission. Reprinted with permission from (Szczupak and Martín 2015) TMS-induced perturbations in other neurotransmitters, such as serotonin and endogenous opioids, have also been evaluated using PET. Serotonin imaging is enabled by tracers such as [11C]αMtrp synthetic analog of the essential amino acid precursor to 5HT, L-tryptophan (Trp), which provides a proxy measure for serotonin synthesis capacity. Imaging of the endogenous opioid system has been monitored using [11C]carfentanil as a high-affinity μ opioid receptor agonist. 17 1.3.1.2 Magnetic resonance spectroscopy MRS allows non-invasively investigating metabolite concentrations in vivo and can thus be used to evaluate neurotransmitter and neurochemical changes. Usually, MRS is acquired from a volume of interest containing several voxels at a time, acquiring spectral components from N-acetyl aspartate (NAA), total NAA (tNAA), a combination of NAA and NAA glutamate (NAAG), creatine (Cr), phosphocreatine (PCr), choline, myoinositol, and the combined signal of glutamate and glutamine (Glx). Under specific acquisition and analysis conditions, recording spectral components of glutamate and glutamine separately and gamma-aminobutyric acid (GABA) is also possible. MRS measurements of GABA and glutamate concentration can be used to monitor inhibitory and excitatory neurotransmission, while the other metabolites present in the MRS spectra have been used as markers of other neurochemical processes. 1.3.1.3 In-vivo imaging of neural activity and functional connectivity PET evaluation of neural activity is enabled by measuring glucose metabolism and cerebral blood flow (CBF), processes that are coupled to neuronal activity (Raichle and Mintun 2006). Glucose metabolism can be assessed using [18F]-2-deoxy-2-fluoro-D-glucose ([18F]FDG), a glucose analog that is useful in the assessment of synaptic activity (Stoessl 2017), while flow and oxygen metabolism can be evaluated with [15O]H2O and 15O. CBF and glucose metabolism are tightly coupled in normal, healthy conditions (Raichle and Mintun 2006) but can become uncoupled in specific pathological cases. 18 Functional magnetic resonance imaging (fMRI) also enables the evaluation of brain activity by evaluating blood-oxygen-level-dependent signal (BOLD). Different from PET-CBF, BOLD measures changes in deoxyhemoglobin, which are driven by blood flow and oxygenation processes that are ultimately coupled to neuronal activity. When acquired at rest, fMRI can identify the correlation of spontaneous fluctuations in brain activity among spatially distributed brain regions, defined as resting-state functional connectivity (rsFC) (Biswal et al. 2010). In rTMS studies, rsFC evaluation is particularly useful as it allows the analysis of rTMS effects without accounting for connectivity modulation concomitant to a task or state. 1.3.2 Modulation of dopaminergic neurotransmission 1.3.2.1 Healthy participants Dopaminergic transmission is dysfunctional in several pathologies, such as Parkinson's disease, major depressive disorder, and addiction. Dopamine has also been suggested as one of the mediators of the therapeutic effects of rTMS (Strafella et al. 2001; Keck et al. 2002; Hayashi et al. 2004). An early study in healthy participants recorded a striatal decrease of [11C]raclopride binding in the ipsilateral caudate immediately after HF-rTMS over the left prefrontal cortex (PFC), indicating an increase in dopamine release (Strafella et al. 2001). The same research group later showed an increase in dopamine release in the ipsilateral putamen after HF-rTMS over the left motor cortex (Strafella et al. 2003). Dopamine imaging studies have also reported a decrease in dopamine release following rTMS administration. One study by Ko and colleagues (Ko et al. 2008) looked at the effects of 19 inhibitory cTBS over the left dorsolateral DLPFC before a planning and set-shifting task. Authors found that cTBS, an inhibitory form of rTMS, impaired performance and decreased dopamine release in the bilateral caudate and the putamen. Given the study design, it is unclear whether this bilateral effect resulted from the inhibitory nature of cTBS, the higher frequency (50Hz) compared to other rTMS protocols, the task at hand, or a combination of these factors. A later study also reported a bilateral dopamine decrease in the striatum of healthy subjects following inhibitory rTMS (Malik et al. 2018). LF-rTMS was delivered to the bilateral insular cortex, and increased uptake of [11C] PHNO – a D2 receptor agonist – in parts of the striatum, also suggesting a decrease in dopamine release. These findings suggest that conventionally inhibitory forms of rTMS (LF-rTMS and cTBS) decrease dopamine release in the striatum in accord with a hypothesized decrease in cortical excitability. Notably, the changes in striatal dopamine reported in these studies follow the distribution of known corticostriatal projections (Alexander et al. 1986), suggesting dopamine release might have been mediated by modulation of the corticostriatal projections. Delivery of HF-rTMS has also been shown to modulate extrastriatal dopamine. In work by Cho and Strafella (Cho and Strafella 2009), the authors found dopamine increases in the ipsilateral anterior cingulate cortex (ACC) and the orbitofrontal cortex following HF-rTMS over the left DLPFC. These changes were likely facilitated by the dense anatomical connections between the DLPFC and the cingulate cortex (Petrides and Pandya 2002) and illustrate one of the possible underpinnings of rTMS therapeutic effects. 20 1.3.2.2 Clinical populations PET studies confirmed tonic striatal dopamine release induced by rTMS in patient populations. In a study of unilateral parkinsonian patients, researchers showed increased dopamine release in the bilateral putamen after acute HF-rTMS delivery over the symptomatic motor cortex (i.e., hemisphere contralateral to the clinically affected hemibody) (Strafella et al. 2005). Work by Kim and colleagues reported similar findings and also reported that the increase in dopamine release was accompanied by motor symptom improvement after a single session of rTMS (Kim et al. 2008). Studies on participants with psychiatric conditions have been carried out using a clinical therapeutic course of stimulation. In subjects with depression, evaluation of [11C]raclopride and L-[β 11C]DOPA failed to detect changes in striatal dopamine release and dopamine synthesis the day after ten daily HF-rTMS sessions of the left DLPFC (Kuroda et al. 2006, 2010). It is unclear if the discrepancy in results was due to the time between rTMS application and the scan acquisition or the number of sessions delivered as stimulation parameters (i.e., RMT and frequency) were similar to previous studies. A study using single photon emission computed tomography (SPECT) addressed this knowledge gap. Pogarell et al. (Pogarell et al. 2006, 2007) used [123I] IBZM, a D2/3 receptor antagonist, and a bolus plus constant infusion scanning paradigm that allows measurement of the tracer and the changes in dopamine release over hours, in this case, before and after an rTMS session. The authors delivered rTMS daily on the left DLPFC of patients with depression for three weeks and acquired scans for the first and last sessions of rTMS. Evaluation of dopamine in the striatum before the first and before the last stimulation session (i.e., before the first rTMS session and minutes before the last session but 24 hrs after the previous session) was comparable, replicating the finding from PET studies (Kuroda 21 et al. 2006, 2010). In contrast, Pogarell and colleagues reported an increase in dopamine release immediately after the first and the last rTMS session. Three observations can be derived from these results: first, HF-rTMS over the left DLPFC in depression has consistently shown therapeutic effects, even when there are no sustained changes in dopamine. Second, measurable rTMS modulation of dopamine is transient and is not detectable within hours following the end of HF-rTMS stimulation. This is in line with results from a dialysis study in rats, where rTMS-induced dopamine release lasted about 140 minutes (Kanno et al. 2004). Third, acute dopamine modulation is similar in response to HF-rTMS when delivered for the first time and after multiple daily sessions (Pogarell et al. 2006, 2007). However, these studies were conducted in a small sample of patients with depression, and it is unclear to what degree neuropathology influenced these results. In summary, PET studies in healthy subjects and patient populations have shown that HF-rTMS delivery increases dopamine in the ipsilateral striatum. Dopamine modulation is localized in areas that correspond to the distribution of the stimulated corticostriatal projections. Patients with Parkinson's disease and mood disorders have shown bilateral changes in striatal dopamine transmission, which highlights how differences in the neurochemical and functional state (disease compared to healthy control) may influence rTMS effects (ipsilateral vs. bilateral) (Ko and Strafella 2012). A significant limitation of some of the studies presented here is the lack of a control condition (Strafella et al. 2005; Kuroda et al. 2006, 2010; Pogarell et al. 2006, 2007; Cho and Strafella 2009), which is specifically relevant in studies of dopamine release modulation. Such study design may make measurement susceptible to expectation, which in itself can induce dopamine release (De la Fuente-Fernández et al. 2001). 22 1.3.3 Modulation of glutamatergic and GABAergic activity Glutamate and GABA are key components in the maintenance and induction of neuroplastic processes, including long-term potentiation (LTP)- and depression (LTD)-like effects observed after rTMS stimulation. MRS evaluation of these neurotransmitters provides valuable insight into rTMS mechanisms. 1.3.3.1 Healthy participants In healthy participants, rTMS has been shown to modulate GABA and glutamate concentrations in the stimulated area of healthy participants (Michael et al. 2003; Stagg et al. 2009; Iwabuchi et al. 2017), as well as regions structurally connected (Michael et al. 2003; Iwabuchi et al. 2017). In the case of glutamate, these changes in metabolite concentrations have been shown to be related to baseline concentrations, as changes in Glx in the stimulated area were shown to correlate negatively with baseline levels (Michael et al. 2003). A cTBS study also reported an increase in GABA concentration in the primary visual cortex accompanied by a decreased cortical excitability (Allen et al. 2014). Similarly, LF-rTMS also led to increased GABA in the stimulated left motor cortex, accompanied by a GABA decrease in the contralateral motor cortex (Gröhn et al. 2019), observable after 20 minutes post-stimulation. Studies of HF-rTMS have also reported a change in the relation between GABA and Glx levels after stimulation, measured as changes in GABA/Glx ratios (Iwabuchi et al. 2017) and the correlation between GABA and Glx values across subjects (Stagg et al. 2011; Stoby et al. 2022). Notably, this correlation was observed even when there was no significant difference between baseline and post-stimulation metabolite values. 23 1.3.3.2 Clinical populations In participants with mood disorders, HF-rTMS has been shown to increase GABA concentration in the target area after a clinical course of stimulation over the left DLPFC (Levitt et al. 2019). Similarly, Erbay and colleagues reported an increase in Gln/Cr ratio on the left DLPFC after 10 sessions (Erbay et al. 2019). Several MRS studies in major depressive disorder participants have also reported a relationship between metabolite concentration and rTMS therapeutic effects (Croarkin et al. 2016). Furthermore, an increase in GABA concentration was reported to be greater in patients that showed an improvement after rTMS delivery (responders) compared to those that did not (non-responders) (Dubin et al. 2016; Baeken, Lefaucheur, et al. 2017; Levitt et al. 2019). Lower baseline glutamate concentration has also been found to be related to therapeutic improvement following rTMS (Luborzewski et al. 2007). In patients with chronic pain, LF-rTMS induced analgesic effects accompanied by an increase in glutamate (Fregni et al. 2011). In contrast, in inpatients with upper dystonia, delivery of HF-rTMS induced a local decrease in both GABA and Glx, while no changes were observed in distal regions (Marjańska et al. 2013). In summary, studies of inhibitory rTMS protocols report a consistent increase of GABA concentration in the stimulated region, while excitatory forms of rTMS report both modulations of GABA and Glx in the targeted region. Overall, these evaluations illustrate the ability of rTMS to modulate GABAergic and glutamatergic activity in various populations. They also suggest a relation between metabolite changes with plasticity induction (i.e., changes in cortical 24 excitability) as well as symptom alleviation, highlighting the relevance of GABAergic and glutamatergic activity evaluation. 1.3.4 Brain activity and rsFC modulation 1.3.4.1 PET studies 1.3.4.1.1 Healthy subjects Early PET studies in healthy subjects showed that both HF- (Paus et al. 1997) and LF-rTMS (Fox et al. 1997) increased CBF in the stimulated region. Similar results were reported in later studies (Paus et al. 2000; Siebner, Peller, et al. 2000; Siebner et al. 2001; Speer et al. 2003a; Takano et al. 2004; Knoch et al. 2006), illustrating how both HF- and LF-rTMS can increase CBF locally. These studies also suggested rTMS modulates CBF in a dose, frequency and intensity-dependent manner as a greater number of pulses (Paus et al. 1997, 1998), a higher rTMS frequency (Siebner et al. 2001; Knoch et al. 2006) and stronger stimulation intensity (Speer et al. 2003a, 2003b) induced greater CBF change. Furthermore, reports on LF-rTMS modulation of metabolism in the targeted area have shown conflicting findings, with studies reporting both increased (Siebner et al. 1998, 1999, 2001; Cho et al. 2012; Lee et al. 2013) and decreased (Cho et al. 2012; Lee et al. 2013) metabolism after LF-rTMS, thus illustrating the complexity of effects of different rTMS protocols. 1.3.4.1.2 Clinical populations Studies in clinical populations have shown the relation between rTMS-induced metabolism modulation and symptomatic improvement. Baeken and colleagues showed that 25 symptom improvement after HF-rTMS (Baeken et al. 2009) and accelerated HF-rTMS (Baeken et al. 2015) was accompanied by glucose metabolism changes in the anterior cingulate. These results were replicated by other research groups, which reported that HF-rTMS (Li et al. 2010; Takahashi et al. 2013) and iTBS (Li et al. 2018) induced a decrease in glucose metabolism and CBF in patients with symptomatic improvement. The authors also found a significant correlation between the degree of symptom improvement and the decrease in cingulate cortex metabolism (Baeken et al. 2015). Further findings suggested TMS anti-depressant effects could be dependent on the pre-stimulation metabolism in the anterior cingulate, as higher pre-stimulation metabolism was recorded in responders (Baeken et al. 2009, 2015; Li et al. 2010). A study in patients with levodopa-induced dyskinesia reported improvement in motor symptoms accompanied by a decrease in metabolism in the cerebellar cortex and deep cerebellar nuclei following cerebellar stimulation (Brusa et al. 2012). Similarly, in post-stroke hemiplegic patients, rTMS delivery combined with physical therapy decreased metabolism asymmetry between the lesional and contralesional areas and improved motor function (Horimoto et al. 2021). In subjects with obsessive-compulsive disorder, glucose metabolism of the bilateral orbitofrontal cortex decreased after LF-rTMS, along with a reduction in clinical symptoms (Nauczyciel et al. 2014). In fibromyalgia subjects, increased metabolism in the medial temporal lobe after HF-rTMS over the left motor cortex was accompanied by improved quality-of-life assessment (Parkitny et al. 2014). These studies show rTMS activity modulation of activity locally as well as in distally connected regions. They also illustrate how the "inhibitory" and "excitatory" effects of rTMS, as reported in cortical excitability assessments, are not as clearly observed in evaluating CBF and glucose metabolism. In patient populations, the changes in activity have seemed to not only be 26 accompanied by symptomatic improvement (Baeken et al. 2009, 2015; Li et al. 2010; Brusa et al. 2012; Nauczyciel et al. 2014) but also to be correlated to the degree of improvement (Baeken et al. 2015; Horimoto et al. 2021) 1.3.4.2 rsFC assessments 1.3.4.2.1 Healthy participants In healthy controls, studies have evaluated the rsFC effects of HF- and LF-rTMS, TBS and QPS delivered mostly over the prefrontal and motor cortices. HF-rTMS over the DLPFC has been shown to increase connectivity between DLPFC and the anterior cingulate cortex (Tik et al. 2017; Xue et al. 2017). Similarly, stimulation of the frontopolar cortex with HF-rTMS has increased connectivity between the targeted area and the amygdala (Riedel et al. 2019). The same study also reported a decrease in connectivity between those two regions following LF-rTMS. Adding to these findings, Zhang and colleagues (Zhang et al. 2020) reported changes in connectivity observed after HF to be more widespread, while LF-rTMS modulated connectivity was mostly found in regions within the stimulated hemisphere. This suggests that HF- and LF- rTMS can induce different directional effects and distinct topological changes. Similar to the effects of HF and LF rTMS, inhibitory and excitatory QPS have been reported to induce distinct effects (Watanabe et al. 2014). Excitatory QPS decreased rsFC between the stimulated left motor cortex and the contralateral motor cortex, while inhibitory QPS increased it, illustrating the bidirectional capacity of rTMS in rsFC. Distinct directional effects have been reported after LF-rTMS and cTBS delivery, both inhibitory forms of TMS stimulation. Stimulation of the supplementary motor area using LF-rTMS increased rsFC within the motor network, while cTBS decreased it (Ji et al. 2017). 27 Interestingly, these two stimulation paradigms had similar topographical and temporal effects, with effects being observed 6 to 10 minutes post-stimulation. A different cTBS study showed a decrease in connectivity within the motor network after delivery over the somatosensory cortex (Valchev et al. 2015). The effects of rTMS stimulation on functional connectivity appear dependent on the number of stimuli delivered. Nettekoven et al. (Nettekoven et al. 2014) showed that iTBS delivery over the left motor cortex, increased connectivity between the stimulated area and the ipsilateral dorsolateral premotor cortex. The increase in connectivity was higher after 1800 pulses compared to changes after 600 and 1200 pulses. Finally, a cTBS study suggested that recorded changes in functional connectivity might depend on the time they are evaluated (Mancini et al. 2017). The authors measured rsFC at 5- and 15-minute post-stimulation and reported a decreased functional connectivity of the temporal lobe at 5 minutes and a change in precuneus connectivity at 15 minutes. 1.3.4.2.2 Clinical populations Studies in patients with major depressive disorder have reported modulation of connectivity in the anterior cingulate after HF-rTMS delivery over the DLPFC (Baeken et al. 2014; Salomons et al. 2014; Baeken, Duprat, et al. 2017; Taylor et al. 2018; Weigand et al. 2018; Ge et al. 2020). Modulation of connectivity between the subgenual cingulate and the orbitofrontal cortex (Baeken, Duprat, et al. 2017; Taylor et al. 2018), the inferior parietal cortex (Taylor et al. 2018), the occipital cortex (Ge et al. 2020) and the caudate (Salomons et al. 2014) was shown to be associated with symptomatic improvement. Similarly, an iTBS study reported increased connectivity between the target area (dorsomedial PFC) and regions from the default 28 mode and the salience network. This increase in connectivity was predictive of symptom improvement (Persson et al. 2020). Pre-rTMS connectivity between the anterior cingulate and areas of the prefrontal (Baeken et al. 2014; Salomons et al. 2014; Baeken, Duprat, et al. 2017; Weigand et al. 2018; Ge et al. 2020) and parietal cortices (Ge et al. 2020) have been shown to predict therapeutic response, as higher baseline connectivity was observed in responders. Connectivity changes have been also been associated with improvement of motor impairments. In patients with Essential Tremor, symptomatic improvement after LF-rTMS was accompanied by increased connectivity within the cerebello-thalamo-cortical circuit (Popa et al. 2013). In participants with Multiple System Atrophy, stimulation of the motor cortex improved motor symptoms and modulated rsFC in the cerebellum and regions from the limbic system and the default mode network (Chou, You, et al. 2015). In stroke patients, motor improvement following iTBS delivery and physiotherapy was linked to changes in interhemispheric connectivity rsFC (Volz et al. 2016). In Parkinson's patients, LF rTMS over the superior temporal gyrus increased connectivity between the stimulated area and the parahippocampal gyrus, improving dysarthria symptoms (Brabenec et al. 2019), while HF delivery modulated rsFC but did not induce symptom improvement. Flamez and colleagues (Flamez et al. 2021) reported that the effect of rTMS on rsFC might be different in Parkinson's patients with different symptomatic profiles. They found LF-rTMS over the supplementary motor area increased connectivity between the target area and the putamen in patients with levodopa-induced dyskinesia while decreasing connectivity in participants without dyskinesia. 29 In patients with obsessive-compulsive disorder, a decrease in rsFC in regions of the cortico-striatal-subthalamic circuit correlated with symptomatic improvement after LF (Mantovani et al. 2021) and bilateral HF (Dunlop et al. 2016). A study also reported that responsiveness to rTMS might depend on disease severity, as patients with more significant impairment showed no improvement following rTMS and showed the strongest baseline connectivity within the cortico-striatal-thalamo-cortical circuit (Mantovani et al. 2021). In stroke patients, improved cognitive impairment after HF-rTMS correlated to increased functional connectivity of the right medial prefrontal cortex and the ipsilateral ventral anterior cingulate (Yin et al. 2020). In addition, iTBS-induced spatial neglect improvement has been linked to greater rsFC modulation within attention network regions (Cao et al. 2016). Similarly, increased rsFC between the DLPFC and the inferior parietal lobule after iTBS accompanied craving reduction in patients with methamphetamine cravings (Su et al. 2020). Overall, rsFC-rTMS studies illustrate the complex effect of stimulation and have revealed rsFC changes do not always follow the frequency-dependent convention of inhibitory and excitatory rTMS (Ji et al. 2017) as high and low-frequency rTMS elicit distinct topological effects in rsFC (Zhang et al. 2020). These studies have also reported the relation between rs-FC and rTMS therapeutic effects, where modulation of rsFC has been related to symptomatic alleviation and serves as a predictor for treatment responsiveness. These studies also show that rTMS effects on rsFC modulation differ between healthy participants and patient populations (Liston et al. 2014) and that rsFC modulation may be distinct depending on clinical characteristics such as disease stage (Flamez et al. 2021). 30 1.4 Lessons and limitations from rTMS neuroimaging studies Repetitive TMS is a tool with the potential as an intervention for multiple brain disorders. Its non-invasiveness and ease of delivery make it a convenient tool that patients tolerate well, despite the burden of daily visits to the administering center. Neuroimaging studies have shed light on some of the neurobiological effects of rTMS, providing researchers with information about the possible underpinnings of its therapeutic effects. These studies also emphasized the complexity of rTMS effects illustrating the modulation of molecular, cellular, and functional processes. While these studies have provided information regarding the brain-wide effects of rTMS, interpreting the results across studies is complicated. The heterogeneity of rTMS parameters and the difference between participant populations limits the comparability of results. Evaluations in healthy controls tend to investigate the acute effects of rTMS delivery (i.e., immediately after a single stimulation session), while studies in clinical populations are mainly concerned with the chronic effects of rTMS, further limiting the translation. Thus, studies that employ more than one imaging technique (for example, PET and MRI) in a single population provide a valuable opportunity to understand the functional and molecular effects of rTMS and how those effects interact. Finally, a relevant gap in current rTMS research exists regarding glia, a cell population that has been shown to participate in the modulation of signal transmission and plasticity (Araque and Perea 2004; Bennay et al. 2008; Perea and Araque 2010). The characteristics of glial cells and their ability to respond to electrical stimuli (Lenz and Nelson 2018) make glial cells potential mediators of rTMS effects. PET and MR techniques for evaluating glial activity markers are available, enabling in vivo evaluation. 31 1.5 Research Objectives and Thesis Outline This dissertation aims to advance the current knowledge of the overall neurobiological effects of rTMS by investigating molecular, functional, and metabolic markers with a multimodal imaging approach (Fig. 1.4). Figure 1.4 Thesis overview Non-human primates (NHPs) were chosen as subjects to facilitate the acquisition of multiple neuroimaging sessions, especially those that require an injection of radioactive tracers. Using animal subjects with similar brain anatomy and close genetic similarity to human subjects provides a unique opportunity to study rTMS as it permits to more easily control for subject characteristics such as age, sex, disease stage and lifestyle. As such, NHPs are valuable subjects in studying the brain and assessing the neural mechanisms involved in non-invasive brain stimulation techniques. Specifically, in the evaluation of rTMS effects, NHPs have several advantages compared to other animal models. Their large brains and comparable neuroanatomy 32 to humans facilitate the translation of the methods with only slight adjustments and even permit the use of standard coils and facilitate the use and comparison of neuroimaging data from PET and MR imaging (Ohnishi et al. 2004; Salinas et al. 2013, 2015). Furthermore, NHPs can be trained to sit in a monkey chair (McMillan et al. 2014) and receive rTMS daily while awake. This study investigates the effects of rTMS in the healthy brain to ensure observations are not affected by diseased-derived effects. The current dissertation was designed to mimic the clinical course of stimulation using TBS (Blumberger et al. 2018), which, given its short delivery time, allowed for delivery on awake animals. We stimulated the motor cortex, given its accessibility in the NHP, as cortices such as DLPFC lays under a thick layer of facial muscles and a thicker part of the skull. The evaluation of the motor cortex will also facilitate the assessment of cortical activity effects, as it permits the evaluation of cortical excitability through motor response assessments. Finally, stimulation of the motor cortico-striatal-thalamo-cortical (CSTC) loop, through motor cortex, will be used as a prototypical example of the responses induced by TBS in a parallel CSTC loops (Alexander et al. 1986) (See Fig. 1.5) 33 Figure 1.5 Cortico Basal ganglia-thalamocortical circuits. Circuits as proposed by Alexander et al. in 1986. Motor loop is highlighted. Abbreviations: APA, arcuate premotor area; CAUD, caudate nucleus (b) body (h) head; DLC, dorsolateral prefrontal cortex; EC, entorhinal cortex; FEF, frontal eye fields; GPi, internal segment of globus pallidus; HC, hippocampal cortex; ITG, inferior temporal gyrus; LOF, lateral orbitofrontal cortex; MC; motor cortex; MDpl, medialis dorsalis pars paralamellaris; MDmc, medialis dorsalis pars magnocellularis; MDpc, medialis dorsalis pars parvocellularisl PPC, posterior parietal cortex; PUT, putamen; SC, somatosensory cortex; SMA, supplementary motor area; SNr, substantia nigra pars reticulata; STG, superior temporal gyrus; VAmc, ventralis anterior pars magnocellularis; VApc, ventralis anterior pars parvocellularis; VLm, ventralis lateralis pars medialis; VLo, ventralis lateralis pars oralis; VP, ventral pallidum; VS, ventral striatum; cl-, caudolateral; cdm-, cudal dorsomedial; dl-, dorsolateral; l-, lateral; ldm-, lateral dorsomedial; m-, medial; mdm-, medial dorsomedial; pm, posteromedial; rd-, rostrodorsal; rl-, rostrolateral; rm-, rostromedial; vm-, ventromedial; vl-, ventrolateral. Image reprinted with permission from (Poston and Eidelberg 2012) as a modification from (Alexander et al. 1986). The current work focused on the following objectives: Objective 1. Evaluate the effects of TBS on neurotransmission and cortical excitability. In Chapter 2, we aim to provide information on the effects of TBS on the dopaminergic and glutamatergic systems. As mentioned previously, studies of dopamine transmission have found opposing results when evaluating acute and chronic effects. Thus, experiments were designed to evaluate dopaminergic neurotransmission after single and multiple stimulation sessions. We used PET-Raclopride as a surrogate marker for dopamine release that allows 34 assessment of striatal neurotransmission. We evaluated the striatum specifically, as in other rTMS studies, given that it is densely connected to the cerebral cortex through corticostriatal pathways. Additionally, changes in glutamatergic neurotransmission in the putamen are evaluated with MRS. Post-mortem immunofluorescence assessments of D2 receptors were carried out to support in vivo measurements. Objective 2. Evaluate changes in functional connectivity within regions of the motor corticostriatal-thalamo-cortical loop after chronic TBS Evaluation of resting state functional connectivity changes following rTMS protocols provides information on the effects of stimulation on the intrinsic functional organization of the brain. In Chapter 3, using rsfMRI, we investigated the effects of a clinical course of TBS on connectivity within the motor loop. Objective 3. Evaluate changes in metabolic connectivity in the awake animals In Chapter 4, we present a pilot study to evaluate the changes in metabolic connectivity induced by TBS stimulation. PET images of glucose metabolism were used in conjunction with a covariate analysis method to find stimulation-specific metabolic networks. Objective 4. Assess the effects of a clinical course of TBS in glial cells through neuroinflammation markers Chapter 5 investigates the impact of multiple stimulation sessions in markers for neuroinflammation, mainly glial cell activation. PET and MRS were used to evaluate in vivo molecular markers related to microglia and astrocyte activation. Furthermore, given the tight connection between neuroinflammation processes and injurious effects, an MRS molecular 35 marker for cellular damage was also used. Post-mortem immunofluorescence assessments of glia activation markers were carried out to support in vivo measurements. Evaluations in objectives 1 to 4 were carried out in the same subjects. Animals underwent multiple neuroimaging sessions per stimulation trial. The different images were evaluated and are discussed in the current dissertation. Figure 1.6 illustrates the timeline of image acquisition and stimulation procedure. The current work is relevant to understanding of human responses to rTMS given that, as illustrated in this chapter, the effects of rTMS are brain wide, altering multiple aspects of neuromodulation. The parallel assessment of neuromodulation, glial activation and functional and metabolic connectivity will provide valuable information on the relation of multiple rTMS modulatory effects. 36 Figure 1.6 Overview of study design. The data in the different chapters were based on multiple neuroimaging assessments carried out in a single animal group that underwent a clinical course of theta burst stimulation. This image generally describes the sequence of image acquisition and stimulation delivery, further details can be found in the following chapters. Scans were acquired as follows: Day -25 to Day -1, Acquisition of baseline PET-FDG, PET-PBR28 and MRI assessment; Day 1, First RMT measurement and stimulation delivery in the anesthetized animal accompanied by a pre (baseline) and post (acute) PET-raclopride (PET-RAC) assessment; Day 2, start of the clinical course of stimulation in the awake animal. Sessions carried from Monday to Friday; Day 24, approximate day of last chronic stimulation session, the day number varied depending in PET and MRI scan availability; Day 25 to Day 27, approximate days of chronic evaluations. On day 25, PET-RAC and PET-PBR28 were acquired, and an additional awake stimulation was delivered. On day 26 PET-FDG was acquired followed by an awake stimulation delivery. On day 27, MRI was acquired immediately followed by euthanasia. 37 Chapter 2: Evaluation of neurotransmission and cortical excitability post stimulation In this chapter, we evaluate the effects of TBS in neurotransmission in the striatum, a region densely connected to the cortex through corticostriatal projections. Specifically, in vivo markers for dopaminergic and glutamatergic activity are investigated. Here, we describe for the first time the subjects and stimulation protocols that were evaluated and discussed throughout the current dissertation. Part of this chapter was published in: Aceves-Serrano L, Neva JL, Munro J, Parent M, Boyd LA, Doudet DJ. Continuous but not intermittent theta burst stimulation decreases striatal dopamine release and cortical excitability. Exp Neurol 2022;354:114106. https://doi.org/10.1016/j.expneurol.2022.114106 2.1 Introduction The non-invasive nature of rTMS makes it a convenient therapeutic tool, especially for neuropsychiatric disorders such as drug-resistant depression and obsessive-compulsive disorder(George et al. 2013; Haghighi et al. 2015; Rehn et al. 2018). In addition, its therapeutic potential for other psychiatric and neurophysiological conditions is actively being investigated (Lefaucheur et al. 2020). Given that dopamine is an important component for the induction and maintenance of neuroplasticity and is involved in movement, cognition, mood, motivation and sleep (Cousins and Salamone 1996; Nieoullon 2002; Jay 2003; Volkow et al. 2007; Lanza et al. 2022), researchers have hypothesized that rTMS therapeutic effects might be facilitated by modulation of dopamine release. Several PET studies have reported striatal dopamine modulation following 38 acute rTMS delivery in healthy non-human primates (Ohnishi et al. 2004), healthy human subjects (Strafella et al. 2001, 2003; Cho and Strafella 2009) and in patients with Parkinson's disease (Strafella et al. 2000, 2005) and depression (Pogarell et al. 2006, 2007). While changes in dopamine release have been observed after an acute, single session of rTMS or TBS, it is less clear that multiple sessions of rTMS delivery in clinical populations affect dopamine concentrations in the long term. Studies by Kuroda and Pogarell reported no change in dopamine release the day after two to three weeks of 10 Hz rTMS in participants with depression (Kuroda et al. 2006, 2010; Pogarell et al. 2006, 2007). It is uncertain if the discrepant results between acute and chronic studies stem from different disease-derived responses or blunted responses due to repeated stimulation sessions. It is also important to note that the comparison between acute and chronic studies is problematic, given that there are several factors known to influence rTMS effects, including coil type and shape, induced current direction, number of pulses and specific population characteristics (Ridding and Ziemann 2010; Goldsworthy et al. 2021) . Thus, the differences in the observed effects after acute and chronic bouts of stimulation may be influenced by the heterogeneity in stimulation protocols and subject populations. Another relevant neurotransmitter in the study of rTMS effects is glutamate, the primary excitatory neurotransmitter of the central nervous system. Not only is glutamate likely a mediator of rTMS-induced dopamine modulation – through corticostriatal projections – it is also a key component in the maintenance of neuroplastic processes (Bono et al. 2020). The relevance of glutamate in rTMS-mediated plasticity was illustrated in work by Huang and colleagues, who showed memantine, an antagonist of the glutamate N-methyl-D-aspartate (NMDA) receptor, can suppress the cortical facilitatory and inhibitory effects of iTBS and cTBS, respectively (Huang et 39 al. 2007). Similarly, in a rodent study, ketamine, an NMDA antagonist, abolished iTBS-induced plasticity (Labedi et al. 2014). MRS studies have reported rTMS modulation of glutamate to be related to therapeutic effects (Fregni et al. 2011; Croarkin et al. 2016) and behavioural and physiological changes such as changes in ipsi- and contra-lateral cortical excitability (Allen et al. 2014; Gröhn et al. 2019) Given that some of rTMS therapeutic and behavioural effects are thought to be facilitated through the modulation of efferent glutamatergic and afferent dopaminergic connections (i.e., corticostriatal and mesolimbic pathway) (Keck et al. 2002; Strafella et al. 2005; Diana 2011; Diana et al. 2017) the study of the interaction of these two neurotransmitters is relevant to the understanding of the rTMS effects. In the current chapter, we investigated the effects of acute TBS on dopamine transmission and of chronic TBS on dopaminergic and glutamatergic neurotransmission. To do so, we stimulated the left primary motor cortex in healthy non-human primates (NHP) and evaluated dopamine release in vivo with PET and [11C]raclopride and glutamate concentration with MRS. Motor cortex was chosen as the stimulation target for the practicality of access in NHPs and as a blueprint of the cortico-subcortical connections and pathways (Alexander et al. 1986; Haber 2003). TBS was chosen as the form of rTMS due to its short duration of application but the prolonged effect as it provides easier delivery in awake animals. In parallel, we investigated and compared the effects of long-term, daily TBS on cortical excitability. In addition, a post-mortem analysis was also conducted to evaluate D2 receptor (D2R) immunoreactivity one day after the last session of TBS. 40 2.2 Materials and Methods 2.2.1 Animals All NHP experiments were conducted following the guidelines and regulations from the Canadian federal government on animal welfare and were approved by the Committee on Animal Care at the University of British Columbia. We used twelve healthy rhesus macaque monkeys (Macaca mulatta): 3 females and 9 males; 7.6 ±1.7 kg, 9 ± 2 yrs. The animals were housed in pairs and kept on a 12-hour light cycle. They were trained to the pole and collar method to handle awake animals (Bliss-Moreau et al. 2013; McMillan et al. 2014) before the start of the study (Fig. 2.1). One juvenile animal was excluded as he was experiencing epileptic attacks and upon MR anatomical scanning, we found shrinkage in the temporal lobe and amygdala. Figure 2.1 Chair and pole set up for awake theta burst stimulation. A) shows the chair used during awake delivery. During training sessions, animals were walked to the chair using a pole clipped to their collar (B); once the animals were secured to the chair, juice was provided as a reward. During awake stimulation and sham sessions (C), animals were walked and clipped by the collar to the chair. A juice reward was provided 5 to 10 minutes after delivery over the marked motor cortex (M1) location. 41 The remaining eleven animals were randomly assigned to receive sham, cTBS, or iTBS over the left primary motor cortex. To reduce the number of animals needed in this study, some animals were randomly assigned to undergo more than one stimulation or sham protocol, each separated by a minimum of 4.5 months (N=2) and a maximum of 12 months (N=4) (9 months on average) between the end of a study and the start of another. 2.2.2 Stimulation and imaging timeline This section briefly describes the succession of procedures as part of the general study. Further details of stimulation delivery, PET imaging, and MRS acquisition can be found in the following sections of this chapter. The animals underwent several days of pole and collar training refresher immediately before the start of the study. A few days before the first stimulation session, an anatomical T1 (TR/TE= 7.4/3.4 ms, flip angle θ = 8°, TI = 778 ms, TFE-shots = 202, TFE shot duration = 1530 ms, FOV= 200 x 200 mm, voxel size = 0.7 mm) was acquired to allow motor cortex localization and neuronavigation during resting motor threshold measurement (RMT) and to facilitate registration of PET data. Scans were acquired in a 3T Philips Achieva MRI using an 8-channel SENSE head coil. Additionally, a pre-stimulation (baseline) MRS assessment was acquired during the same magnetic resonance session. On the day of the first TBS administration and while the animal was under anesthesia, we used a neuronavigation system (BrainSight) to identify the motor cortex location and marked it with a water-proof marker on the shaved head of the animal. We measured the baseline RMT followed by the first stimulation or sham session in the anesthetized animal. Two PET scans were acquired on that day (see Fig. 2.2): the first before RMT measurement (baseline scan) and 42 the second within 5 min of TBS or sham delivery (acute scan). Baseline and acute scans were acquired at least 3 hours between tracer injections. Animals were under light anesthesia (isoflurane 1-1.5%) during RMT measurement, acute TBS delivery and PET scan acquisitions. The scan procedure is summarized in the following sections. Chronic TBS or sham stimulation delivery started the following day. Stimulation was administered daily from Monday to Friday to the awake animals. The number of sessions was adjusted based on PET and tracer availability (average iTBS = 17 ± 3; average cTBS sessions = 16 ± 3; average sham sessions = 16 ± 2). One animal underwent 22 iTBS stimulations due to a breakdown of the PET scanner that pushed the scans back by a week. During stimulation delivery, the trained animal sat in a primate chair under minimal restraint in their normal housing room to reduce separation stress. Prior to the stimulation, the animal was trained to jump from the housing pen into a squeeze cage to make it easier to lock onto the collar with the pole and administer drug if needed. All animals were accustomed to regular handling but as a precaution, on the first awake session, they received a low dose of a ketamine/xylazine mixture (7:3 mix, 0.1 to 0.2 mL of the mixture IM) as a mild tranquilizer while they got used to TBS administration. The dose used did not have a sedative effect but rather allowed the animals to relax during the initial sessions. Three animals had to receive doses for 2-3 sessions before fully acclimated to stimulation or sham delivery. During the session, the NHP sat quietly while restrained to the chair only by the collar. While gently stabilizing the head of the trained animal with one hand, TBS was delivered over the skin-marked motor cortex location on the left hemisphere (Fig. 2.1). After the end of TBS stimulation, the monkey sat quietly for at least 5 minutes and was then walked back using the pole and released directly in the housing pen. No abnormal behaviour was noticed in any animals after TBS or sham. 43 A third [C11]raclopride head scan was acquired for each animal within 24 hours of the last TBS or sham session to avoid contamination by acute stimulation effects. RMT was measured in the anesthetized animal before scan acquisition (see below). Once the animal had woken up from anesthesia, an additional TBS or sham session was delivered. The next day, a second MRS assessment was carried out. Figure 2.2 PET-raclopride evaluation. Length of the study and number of TBS or sham sessions slightly varied to accommodate radiotracer and scan availability. Icons created with biorender (biorender.com). 2.2.3 RMT measurement and TBS delivery RMT was measured twice in anesthetized animals (isoflurane; see PET preparation section for details on anesthesia) before the acute and chronic PET scans. To prepare for RMT assessment, the head of the monkey and the right shoulder were shaved, and EMG electrodes were placed on the right deltoid muscle. The anesthetized animal was positioned prone on the PET scanner bed, and the T1-weighted anatomical MRI was used to locate left motor cortex using a BrainSight™ neuronavigation system. Single TMS pulses were delivered using a Magstim Rapid2 stimulator 44 with a D702 figure-of-eight human coil (Magstim Co., UK), positioned over the left motor cortex. Figure 2.3 shows images of RMT measurements acquired at the PET suit (Fig. 2.3). Figure 2.3 Set up for RMT measurement. Measurements were acquired in the PET suite before [11C]-raclopride acquisition while the animal was under light anesthesia. Animals were kept comfortably warm with a heating pad and vital signs (heart rate and oxygen concentration) were monitored throughout the procedure. BrainSight™ neuronavigation system was used to establish motor cortex location using the animals T1-weighted image (A). Coil was positioned around the approximate motor cortex locations (B) while TMS pulses were delivered until the region that elicited the most consistent EMG response in the shoulder was found. Once the left motor cortex location that induced the largest and most consistent motor evoked potentials was identified, a water-resistant marker was used to mark the location on the shaved head of the animal. RMT was defined as the lowest % of maximal stimulation output (%MSO) to produce a MEP of at least 50 μV in the relaxed deltoid muscle in five out of 10 consecutive trials (Rossini et al. 2015). Figure 2.4 shows a representative MEP. Pre-cTBS RMT measurement in one subject was not reliable and cTBS was delivered at 45% MSO, a stimulation intensity used in other stimulation trials on the same subject. TBS parameters were chosen to match parameters in human studies closely: a total of 600 pulses, delivered in three-stimuli-bursts at 50 Hz, at a frequency of 5 Hz (Huang et al. 2005), were delivered over the left motor cortex at 90% RMT. Continuous TBS was administrated for 45 40 seconds in a continuous train, while iTBS was delivered for 190 seconds in 2-second trains with a 10-second inter-train interval (i.e., 2 seconds of TBS and 8 seconds of no stimulation). Finally, we administered sham stimulation using cTBS parameters but orienting the coil "upside-down" (i.e., magnetic field facing away from the head of the subject with the coil at least 7-8 cm from the skull) and lowering the stimulation intensity to 15% MSO. TBS administration was performed similarly in the anesthetized animal and the awake animal. We did not adjust the intensity over the course of TBS: while RMT may be measured daily in research studies in human subjects, it would not have been practical, safe, or accurate in awake animals only lightly restrained by the chair and collar. As a result, the %MSO was kept constant across the TBS sessions in awake animals. Figure 2.4 Representative motor-evoked potential response to TMS in a non-human primate. 2.2.4 PET data acquisition and analysis PET studies were performed on a high-resolution research tomograph (ECAT HRRT, CPS Innovations, Knoxville, TN, USA) at the University of British Columbia. The anesthetized animal was positioned prone in a PET-compatible stereotaxic head holder and advanced inside 46 the gantry. Tracer injection and scan acquisition started within 5 minutes of the end of acute stimulation. PET-raclopride assessments were carried in 8 animals that underwent cTBS, 7 that underwent iTBS, and 5 that underwent sham stimulation. The synthesis of [11C]raclopride, scanning parameters, and general procedures have been described extensively elsewhere (Doudet et al. 2000; Holden et al. 2002; Doudet and Holden 2003). Briefly, the animal was sedated with ketamine (10 mg/kg IM) to allow for quick transfer to the scanning suite and given atropine (0.05 mg/kg IM) to reduce secretions. On the scanner bed, the NHP was intubated to administer isoflurane in 100% oxygen in the lowest concentration possible to maintain immobility (1.5-2.5%). Light anesthesia was maintained for the remainder of the study (scans, RMT, and TBS or sham). An intravenous line was placed in the saphenous vein for tracer administration. Monkeys were positioned prone in an in house, custom-made PET and MR compatible head holder to prevent head movement during scan acquisition and ensure reproducible positioning between scans. The animal was situated such that the brain would be in the center of the gantry. The tracer was administrated IV, adjusted to a fixed volume of 10 mL with sterile saline and delivered over 1 minute (dose: mean= 189 MBq, SD = 28.8; specific activity: mean = 92. 389 GBq/µmol, SD= 56.758; mass: 0.75 µg, SD= 0.3). Dynamic scanning started at the beginning of tracer injection and lasted for 60 minutes. Data were reconstructed to a total of 14 frames (5 x 1 min, 2 x 2.5 min, 4 x 5 min, and 3 x 10 min). For the baseline scan, attenuation was acquired before radiotracer injection. However, the attenuation scans were acquired post-emission scans to reduce the time between TBS/sham delivery and raclopride injection. 47 Vital signs (heart rate, respiratory rate, temperature, oxygen saturation) were monitored throughout the entire study and maintained within the normal range. All animals awoke spontaneously after the scanning session, and no side effects were noted. OSEM-OP was used for reconstruction as previously described (Comtat et al. 2004), and the images were smoothed with a 2 mm Gaussian filter. PET images were registered to an in-house MRI T1 rhesus monkeys template with associated predefined hand-drawn regions of interest of the left and right caudate and putamen and of the cerebellum. The transformation parameters were used to realign the individual dynamic images to the MRI template. The predefined ROIs were used to extract time-activity curves. Non displaceable binding potential (BPND) was computed using Logan's graphical analysis for reversible tracers (Logan et al. 1996). We used the cerebellum as a reference region and a t*= 20 minutes. 2.2.5 Responder and non-responder classification Subjects that underwent active TBS were classified as responders or non-responders to stimulation based on raclopride BPND change in the striatum. BPND % change was calculated as: ((Post - Baseline)/Baseline)*100 where Post is the acute or chronic BPND and Baseline is the baseline BPND. To classify subjects, we used the average striatum (putamen and caudate) acute and chronic difference between baseline and post BPND from the sham group as a reference. Animals were classified as responders if they showed a response greater than the average change after sham in the direction expected from the literature (i.e., increase BPND after cTBS and decrease after iTBS) (Strafella et al. 2005; Ko et al. 2008). 48 2.2.6 Magnetic resonance spectroscopy MRS acquisition was performed before the first stimulation session and one day after chronic stimulation. To maintain the 24hrs delay between TBS and neuroimaging evaluation, an additional TBS or sham session was delivered to the animals after the end of the PET session and 24 hrs before the last MRI/MRS session, which was immediately followed by euthanasia. In total, MRS assessment was carried out in 9 animals stimulated with cTBS (7 with iTBS and 6 with sham. Animals were anesthetized with ketamine (10 mg/kg IM), given atropine to reduce secretions, and intubated to maintain the airways clear. They were quickly transported to the MRI suite and positioned supine in the scanner (Scanner and coil characteristics are described at the beginning of the methods). During scan acquisition, we delivered low doses of sodium pentobarbital IV (30 mg/kg/h IV) to maintain light anesthesia and immobility (Fig. 2.5) 49 Figure 2.5 Set up for magnetic resonance imaging and spectroscopy acquisition. An IV was placed to facilitate administration of light sedation using sodium pentobarbital. Animals were placed supine on the scanner bed. We placed foam sponges around the head and underneath the arms and legs to prevent movement and facilitate positioning. The animal was covered with a blanket for the entirety of the procedure (removed here for picture). A single-voxel 1H-MRS PRESS spectra were acquired (TR= 4000 ms, TE= 30 ms, sampling frequency = 2000 Hz, signal averages = 128, voxel dimensions = 15 mm × 8 mm ×10 mm). The voxel was manually placed over the left and right putamen, ensuring that they capture grey and preventing white matter inclusion as much as possible (Fig. 2.6). We used LCModel (Provencher 2001) to estimate the absolute metabolite concentration of glutamate using the reference area of the unsuppressed water signal. The quality of spectral fits was inspected visually to ensure goodness-of-fit and a narrow full width at half maximum. 50 Figure 2.6 MRS voxel placement on putamen Right (A) and left (B) putamen voxel for a subject over a T1-weighted image. (C) Visualization of 1H-MRS spectra for a representative subject: Glu + Gln: glutamate + glutamine; ml myo-inositol; NAA, N-acetylaspartate; tCr: creatine Metabolite concentrations were adjusted for the water relaxation of the different tissues within the MRS voxel. First, we used FMRIB's FAST on T1 images to segment images into three tissue classes: gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). MRS voxels were linearly registered into the T1 space and used to calculate the volume of each tissue within the voxel. Finally, tissue volume fractions were used to correct glutamate concentration estimates for water relaxation using T1 and T2 values for relaxation correction from the literature (Posse et al. 2007; Macmillan et al. 2016). 51 2.2.7 Post-mortem analysis Following completion of the MRI/MRS study, the animals were transported to the dedicated necropsy room of the main animal unit. They were deeply anesthetized with sodium pentobarbital (Euthanol; 120 mg/kg IV). After the heart stopped beating, the chest cavity was rapidly opened, the heart exposed and perfused through the ventricle with about 500 mL of cold isotonic saline followed by 3-4 L of freshly prepared 4% paraformaldehyde. The brain was dissected out and was placed whole in a jar of cold 4% paraformaldehyde for another 48-72hrs at 4°C, then switched to a solution of fresh cold PBS that was changed 3 times before shipment to the laboratory of Dr. Martin Parent at Laval University. In total, 3 animals were euthanized after sham stimulation, 4 after iTBS, and 4 after cTBS. Post-mortem processing was performed at Laval University. Brains were cut with a vibratome (VY1200 S’ Leica) into 50 µm-thick transverse sections. Four sections per monkey were selected between 7.95mm and 9.75mm from the interaural point and prepared for immunohistochemistry. Immunostainings with a polyclonal rabbit antibody directed against D2R (1:200, product no. AF960, Frontier Institute) were performed using the corresponding anti-rabbit infrared secondary antibody IR680 (1:1000, product no. 926-68070, LI-COR Biosciences). Optical density measurements were obtained from defined rectangular regions of interest located within motor cortex (over which TMS was applied), putamen, and caudate nucleus using the Odyssey LI-COR software. As an exploratory analysis to compare in vivo and post-mortem data, we computed [11C]raclopride BPND in the left and right sensorimotor cortical areas, composed of motor cortex, supplementary motor cortex, and sensory cortex (i.e. the cortical tissue located under the TMS coil) in the chronic scan condition. While raclopride is traditionally used for measuring striatal 52 D2R availability and has very low estimates in cortical regions, studies suggested that it may also provide reliable measures in non-striatal regions (Papenberg et al. 2019; Karalija et al. 2020). BPND in a stable (i.e. in the absence of an acute experimental challenge) condition is considered to represent an estimate of receptor density. We took advantage of this assumption to compare the raclopride BPND in the striatum and the sensorimotor cortex to the measures of D2R immunoreactivity obtained following post-mortem examination of the same brain regions. 2.2.8 Statistical analysis Paired t-tests were used to compare baseline and post-stimulation RMT measurements within each cohort. In total, baseline and post-stimulation RMT measurements were acquired in 8 NHP for cTBS, 7 for iTBS and 6 for sham. Repeated measurement analysis of variance (RM ANOVA) with Tukey correction for multiple comparisons was used to evaluate the effect of acute and chronic TBS delivery on BPND within each cohort. In addition, paired t-tests were used to compare glutamate concentration before and after TBS and sham. We did not carry out any statistical analysis across cohorts, given that some animals were part of more than one stimulation group. Mann-Whitney test was conducted to compare the mean optical density between sham and TBS (iTBS and cTBS) for the post-mortem analysis. All statistical analyses were performed in Prism software version 8 (GraphPad Prism, San Diego, California USA). 53 2.3 Results 2.3.1 RMT changes Paired t-test revealed a significant change in RMT measurements after chronic cTBS delivery (N =8) over the left motor cortex (p = 0.04). On average, RMT measurements were increased by 16.9 ± 16.5% the day after the end of chronic cTBS (Fig. 2.7). There was no significant difference in RMT after iTBS (N = 7) nor sham delivery (N = 6) as shown by paired t-test (p > 0.5). Although not statistically significant, RMT increased by 3.3 ± 12.7% after chronic iTBS, while post-sham assessment revealed no measurement changes (0.41 ± 3.6 %). Figure 2.7 Resting motor threshold (RMT) measurements before and after stimulation. This graph presents the percentage of the maximum stimulator output (% MSO) at baseline and after chronic delivery of sham, continuous, and intermittent theta burst stimulation (cTBS, iTBS). 2.3.2 Changes in raclopride BPND RM ANOVA showed a significant main effect of cTBS delivery on BPND in the left (p = 0.034) and right putamen (p = 0.018). While the values in the caudate nucleus varied in the same direction, they did not reach significance (left p = 0.2; right p = 0.2). Post-hoc tests using Tukey correction revealed a significant BPND increase in left and right putamen after acute (left p=0.04, right p=0.03) but not after chronic stimulation delivery (left p = 0.96, right p = 0.95). 54 In the iTBS cohort, repeated measurement (RM) ANOVA showed no significant effect on BPND in left (p = 0.78) nor right (p = 0.34) putamen. Similarly, sham stimulation showed no effect on binding in the putamen (left p = 0.54; right p = 0.18). Finally, RM ANOVA revealed no effect on caudate binding after iTBS (left p = 0.5; right p = 0.2) nor sham (left p = 0.1; right p = 0.7) delivery. Raclopride BPND at baseline, and after acute and chronic stimulation in the putamen is shown in Figure 2.8. Figure 2.8 [11C]Raclopride binding potential in putamen before and after stimulation Measurements of binding potential (BPND) acquired at baseline and after acute and chronic delivery of sham, intermittent and chronic theta burst stimulation. Variations in tracer binding were also evaluated in a control condition (sham). 2.3.3 Responder and non-responder classification Given the lack of response to chronic stimulation, classification was narrowed to effects of acute stimulation. Subjects were classified as responders if their BPND change was greater than 55 ± 5.5%, the average striatal difference after acute and chronic sham delivery, a value which is in accordance with test-retest studies (Hietala et al. 1999; Alakurtti et al. 2011, 2015). Specifically, for the cTBS cohort, NHPs with a positive BPND change greater than +5.5% were classified as responders, while iTBS-responders showed a change more negative than -5.5%. A total of 5 out of 8 subjects were classified as responders to cTBS based on the above criteria (Fig. 2.9). In addition to the putamen changes, RM ANOVA in the five responders revealed an acute effect on the right caudate (p = 0.04) as reported by a post hoc test using Tukey's correction. Tracer binding in the caudate was similar to baseline 24hrs following the last session of a course of cTBS. One out of seven subjects was classified as a responder to acute iTBS. A decrease in binding in the one responder was observed in the caudate nucleus and the putamen. Figure 2.9 [11C]Raclopride striatal binding potential (BPND) in cTBS responders. 56 2.3.4 Glutamate assessment Similar to PET assessments, we did not find changes in glutamate concentrations after chronic stimulation in the left or right putamen. Glutamate concentration after sham stimulation was 6.8% (p = 0.1) greater than baseline measurements in the left putamen and 5.6% (p = 0.6) smaller in the right putamen. Similarly, concentration after cTBS was 4.7% (p = 0.3) greater than at baseline in the left putamen and 4.7% (p = 0.2) smaller in the right putamen. Concentration after iTBS was 3.7% (p = 0.6) smaller than at baseline in the left putamen and 2.4% (p = 0.6) greater in the right putamen (Fig. 2.10). Figure 2.10 Glutamate concentration in putamen before and after stimulation. Based on the responder and non-responder classification from PET-raclopride assessment, glutamate concentrations in the animals in the responder group (n = 5) were evaluated separately using a t-test. No significant differences were found between baseline and post-cTBS glutamate concentration in the left (p = 0.7) nor the right putamen (p = 0.3). 57 2.3.5 Post-mortem analysis There was no significant difference between the left and right hemispheres in the mean optical density in any of the cohorts. As such, we are presenting the averaged values for the motor cortex, caudate nucleus, and putamen (Fig. 2.11). Mann-Whitney test showed no significant difference between sham and iTBS nor cTBS in the motor cortex (iTBS p = 0.06; cTBS p = 0.62), putamen (iTBS p = 0.4; cTBS p = 0.62), and caudate nucleus (iTBS p = 0.06; cTBS p = 0.85). Since there were no significant differences in the raclopride BPND between the left and right cortices and striatum after chronic stimulation, the left and right were averaged. Cortical post-mortem D2R measurements and cortical BPND are shown in Figure 2.11. 58 Figure 2.11 In vivo and post-mortem markers for dopamine neurotransmission. D2R mean optical density (left column) and [C11]raclopride binding (BPND) in the sensorimotor cortex, putamen, and caudate nucleus after chronic sham, iTBS, and cTBS. 2.4 Discussion 2.4.1 TBS modulation of cortical excitability We evaluated changes in RMT, a measurement that has been shown to correlate with other excitability measurements and evaluations of behaviour and function, such as motor performance (Pascual-Leone et al. 2002; Kühn et al. 2004; Chen et al. 2008; Silbert et al. 2013; Fisicaro et al. 2020). We found good replicability between baseline and chronic RMT measurements in the sham group (range of -4% to 6.3% MSO), even when these measurements were taken in monkeys under anesthesia, a condition expected to introduce variability. 59 Chronic cTBS delivery induced a significant increase in RMT compared to baseline, suggesting a reduction in cortical excitability, in line with reported cTBS inhibitory effects following a single session (Huang et al. 2005). These changes in RMT after cTBS were still present a day after the last stimulation session, different from previous human studies where cortical excitability change was observed only up to 1-hour post-acute stimulation (Huang et al. 2005; Chung et al. 2016; Jannati et al. 2019). This longer-lasting decrease in cortical excitability presumably resulted from cumulative cortical modulation that potentiated the effect of a single stimulation session (Bäumer et al. 2003). The recorded cortical excitability change suggests that chronic cTBS delivery might be an adequate therapeutic tool to target abnormal cortical hyperexcitability observed in disorders like migraine (Brighina et al. 2002), tinnitus (Langguth et al. 2007), amyotrophic lateral sclerosis (Di Lazzaro et al. 2006), stroke (Blesneag et al. 2015) and mixed and vascular forms of dementia (Alagona et al. 2004; Vinciguerra et al. 2020; Di Lazzaro et al. 2021). We, like others (Perellón-Alfonso et al. 2018; Bouaziz et al. 2021), did not find significant effects after chronic iTBS delivery, even though studies have shown an increase in cortical excitability following a single session of iTBS (Huang et al. 2005; Chung et al. 2016). Given that we measured RMT 24 hours following the last iTBS session, it is possible that we missed the window in which changes would have been noted. The lack of significant cortical excitability changes after iTBS could also be attributed to the variability of RMT estimates across subjects in the iTBS cohort. While RMT increased in seven out of eight subjects after cTBS, iTBS did not induce consistent changes, with three animals showing an increase, three showing a decrease and 1 showing no clear change (Fig. 2.7). Similar variability was reported in human participants after acute iTBS and cTBS delivery 60 (Hamada et al. 2013). However, it is unclear why, in our sample, considerable variability was primarily observed after chronic iTBS and was much less after cTBS. Alternatively, in healthy subjects, homeostatic plasticity processes might prevent a further increase of cortical excitability in the already intrinsically excited motor cortex (Turrigiano 1999; Bear 2003; Turrigiano and Nelson 2004a, 2004b). Homeostatic plasticity could have modulated intrinsic or synaptic plasticity to maintain neural activity in the cortex to a set physiological point. A recent acute iTBS study in humans suggested something similar. After reporting no significant change in cortical excitability, Volz and colleague suggested that the lack of iTBS effect might be explained by the presence of a pre-activation state of the cortical circuits that modulate iTBS corticospinal effects (Volz et al. 2019). Similarly, Nettekoven and colleagues failed to induce increased functional connectivity after acute iTBS over the motor cortex in subjects with higher baseline motor network connectivity (Nettekoven et al. 2015). Thus, in the current work, an excited baseline state might have contributed to creating a ceiling effect, making it harder to increase cortical excitability further. 2.4.2 Acute TBS modulation of dopamine release In the iTBS cohort, there were no changes in acute or chronic striatal dopamine release. Along with the lack of RMT changes after chronic iTBS, the absence of dopamine modulation might directly result from iTBS ineffectiveness in altering cortical excitability or the variability of its effects. While most subjects showed an increase in tracer binding and RMT after cTBS delivery, iTBS response was highly variable as we observed increase, decrease, or no change in dopamine release and RMT was observed following iTBS. Variable local activity modulation in the motor cortex after iTBS may have led to the variable distal effects in striatal dopamine 61 release. High iTBS variability combined with the low number of subjects (N = 7) ultimately limited the sensitivity of our study. A significant effect of iTBS delivery might be detectable in a larger cohort. Dopamine modulation in an unimpaired brain often has limited results, even when using pharmacological interventions (Antonini et al. 1994; Tedroff et al. 1996). These authors recorded no change in [C11]raclopride binding after L-dopa administration in healthy subjects, while the same intervention in Parkinson's patients resulted in significant raclopride binding changes consistent with increased dopamine release. Thus, the difficulty in perturbing an intact system should be considered when translating and interpreting current results, as iTBS might not be able to consistently modulate dopamine release in a healthy brain but might induce changes in an impaired one. Unlike iTBS delivery, we found a significant increase in BPND in both the left and the right putamen following acute cTBS, suggesting a bilateral decrease in dopamine release. These changes were likely mediated by modulation of cortico-striatal projections from the motor cortex to the bilateral striatum (Kunzle 1975; Parent and Parent 2006). Cortical glutamatergic inputs to the striatum modulate dopamine release through activation of cholinergic striatal interneurons, which in turn activates terminals of dopaminergic neurons, inducing dopamine release (Cachope et al. 2012; Kosillo et al. 2016). Thus, inhibition of cortical activity through cTBS delivery over the motor cortex might have inhibited the input of cortical projections to the striatum, ultimately decreasing dopamine release. The discrepancy between the effects of conventionally facilitatory and inhibitory forms of rTMS on dopamine release has been previously reported. Malik and colleagues found that deep 1 Hz rTMS decreased dopamine release in the striatum and substantia nigra, but reported no 62 changes after 10 Hz rTMS (Malik et al. 2018), contrary to previous findings (Strafella et al. 2001, 2003). Thus, the current study, along with Malik’s work, illustrates how different rTMS protocols might have very variable effects on dopamine modulation even when stimulating cortical regions known to mediate it. Classification of subjects into responders and non-responders further highlighted the different effects of the two TBS protocols. Intermittent TBS reduced tracer modulation past the threshold in a single subject, while cTBS increased tracer binding past the threshold in five subjects. Notably, binding was increased in three subjects from the iTBS cohort, indicating a decrease in dopamine release, opposite to what expected given its excitatory effects. We cannot exclude the possibility that isoflurane anesthesia may have lowered or interfered with normal excitatory response in this cohort of healthy animals. 2.4.3 Chronic TBS modulation of dopamine release We did not observe a significant effect of long-term cTBS or iTBS delivery on [C11]raclopride BPND. Our findings are in line with results from rTMS evaluation in human clinical populations, where dopamine change after 10 Hz rTMS delivery was not observed 24 hrs following chronic delivery (Kuroda et al. 2006, 2010). Similarly, Pogarell and colleagues compared the effects of 10 Hz rTMS immediately after acute stimulation and at three time points after chronic stimulation: within minutes, after 24hrs and after 2 weeks (Pogarell et al. 2006). They found no change in dopamine release 24 hrs or 2 weeks after chronic stimulation. In contrast, dopamine release increased immediately after the first and the 15th rTMS sessions. This suggests that dopamine modulation might only be transient, lasting less than a few hours after rTMS delivery (Lamusuo et al. 2017) and that the acute effect remains even after multiple daily 63 stimulations. Unfortunately, we did not evaluate release immediately after the last session of our TBS course (to mitigate the burden on the animals) and elected to only look at the long-term effects of a clinically relevant course. In the cTBS cohort, the lack of measurable dopamine receptors changes in the presence of long-term cortical excitability modulation might be the result of an adaptive response to chronic stimulation. As mentioned previously, neurons tend to engage in homeostatic mechanisms after sustained perturbation to attempt to bring activity back to an optimal responsiveness level (Turrigiano 1999; Bear 2003; Turrigiano and Nelson 2004a, 2004b). Sustained change in cortical excitability, and ultimately in the modulation of cortical inputs to the striatum, might have induced alterations in the striatum, such as synaptic strength or synaptic scaling, and decreased the responsiveness to cortical excitability modulation. In-vivo findings were confirmed by the post-mortem analysis of D2R density, as we did not find any significant effects in optical density measurements of the putamen, caudate nucleus, and motor cortex following chronic stimulation. The binding potential of [C11]raclopride in the absence of an acute intervention is considered to reflect receptor density and should thus be aligned with post-mortem findings. Both measurements agreed despite the different number of observations and methods, suggesting no prolonged effects of a clinically relevant course of TBS on the dopamine system in healthy control subjects. We had hypothesized that prolonged exposure to increased or decreased DA transmission might lead to decreased or increased receptor density. However, as discussed above, the ability of a healthy system to regulate itself may make it difficult to induce sustained changes in receptors density with only an intermittent (once a day) and transient alteration in synaptic concentrations. 64 2.4.4 Chronic TBS modulation of glutamatergic activity In line with PET-raclopride findings, we found no significant difference in glutamatergic markers between baseline and post-stimulation. These results are in line with studies in healthy humans participants, where no changes in Glx nor glutamate were observed at the stimulated and connected regions (Michael et al. 2003; Stagg et al. 2009; Bridges et al. 2018; Rafique and Steeves 2020; Stoby et al. 2022). These results, however, do not mean TBS has no effect on glutamatergic activity in the studied regions. It is possible that TBS-induced modulation of glutamatergic activity is only observed acutely and, given that our assessment was carried one day after stimulation, these changes had faded. Michael and colleagues reported such behaviour after HF-rTMS over the left DLPFC (Michael et al. 2003). Authors reported that changes in Glx were observed immediately after a single stimulation session; however, MRS evaluation 24 hours after five stimulation sessions showed Glx values were no different from those recorded at baseline. These results suggest that rTMS modulation of glutamatergic activity might behave similarly to dopaminergic modulation displaying only acute changes that dissipate within 24 hours of stimulation. 2.4.5 NHP in the study of rTMS and the effects of anesthesia Even though humans and non-human primates have comparable neuroanatomy and many common physiological responses, caution should be taken when extrapolating the current results. Differences between humans and non-human primates might influence rTMS effects, including skull shape and tissue thickness, the adult monkey's having a thick skull and muscle insertions on the top of the head, which increases the distance between coil and brain tissue, and smaller brain volume. 65 The use of anesthesia during PET and MRS acquisition might also impact measurements and thus, mask or exacerbate any TBS effects. However, previous monkey studies showed that low doses of anesthesia with ketamine or propofol had no significant impact on the evaluation of neural activity (Salinas et al. 2011, 2013) or dopamine modulation (Ohnishi et al. 2004) by PET after rTMS. We are unaware of studies specifically looking at the effect of isoflurane nor pentobarbital anesthesia on differential responses to rTMS or TBS stimulations and thus cannot exclude a modulatory effect. Notably, a [11C]raclopride study evaluating the effects of isoflurane in non-human primates showed that it induced negligible modulation of tracer uptake by itself but that it can modify the effect of interventions that induce dopamine release (Tsukada et al. 2002). The lack of significant effect by iTBS appears more due to the response variability compared to sham overall unchanged responses. Thus, we cannot exclude the possibility that isoflurane might have mitigated iTBS effects or introduced variability to the reported [11C]raclopride measurements. Regarding ketamine administration prior to MRS and PET acquisition, while the sustained infusion of ketamine was shown to increase dopamine release in the striatum (Tsukada et al. 2000), studies where a single dose of ketamine was administered (as done in the current work, at least 1-2 hour prior to PET or MR assessment), showed no significant changes in striatal dopamine release in non-human primates (Adams et al. 2002). Adams et al. delivered a subanesthetic dose (5 mg/kg) and, using microdialysis, observed a mild and transient increase in striatal dopamine release that dissipated 45-60 minutes after administration. In the current work, we delivered a higher ketamine dose (up to 10mg/kg) which could have increased dopamine release. However, it is unlikely that a significant effect would have persisted by the start of the PET evaluation given that there was a significant delay between ketamine administration and 66 raclopride injection. The lack of ketamine effects in PET measurements was confirmed by the reproducibility of binding potential between baseline and acute measurements in the sham cohort. In the case of MRS evaluation of glutamate, while ketamine has been shown to increase glutamate concentrations measured with MRS (Rowland et al. 2005), these measurements were carried during ketamine administration. Further studies in healthy human participants and patients with major depressive disorder reported no significant changes in glutamate after 3 hrs, 24 hrs and 48 post ketamine administration (Evans et al. 2018). Given that MRS assessments happened more than 2 hours post ketamine administration, it is unlikely any effects were still present. In the case of cortical excitability and anesthesia, administration of isoflurane has been shown to affect motor threshold as measured with transcranial electrical and magnetic stimulation (Schmid et al. 1992; Ubags et al. 1998; Dockx et al. 2019). Specifically, isoflurane has been reported to decrease MEP amplitudes or completely suppress MEPs in human participants (Schmid et al. 1992; Ubags et al. 1998). This suggests that, in subjects under isoflurane anesthesia, a higher TMS intensity might be necessary to induce a consistent motor response, ultimately increasing RMT measurements. This could indicate that the stimulation delivered in the current study might have been higher than 90% of RMT. However, the animals were kept under very light anesthesia, not surgical-level anesthesia, which should have only minor effects (Ubags et al. 1998). Finally, the reproducibility of RMT measurements in the sham evaluation confirms that anesthesia did not induce significant changes in RMT measurements between the two-time points. Thus, any changes in RMT are likely a result of the stimulation procedure. 67 Unfortunately, given the nature of animal studies, daily RMT measurement in the awake animal would not only have been extremely technically challenging but also unreliable. RMT measurement would require the animal to stay still for longer requiring additional animal restraining. This would induce considerable stress in the subject and would not completely prevent muscle contraction, two phenomena that have been reported to impact cortical excitably (Darling et al. 2006; Milani et al. 2010). As a result, RMT measurements were only carried out before acute sham or TBS in the anesthetized animal. TBS in the awake NHP was delivered at the same percentage of MSO daily and in the approximate location of motor cortex based on the location marked on the day of acute delivery. Finally, another relevant caveat is the (smaller) size of the NHP head and brain compared to the (large) TMS coil size. This likely reduced the focality of the stimulation. Although smaller coils exist, when the protocol was tested using a 50 mm coil the TBS parameters used would quickly overheat the coil. Furthermore, a larger coil allowed for greater stimulation depth, required due to the thick NHP muscle (2-4 cm thick depending on age) insertions in the top of the head making the space between the coil and the cortex larger. While our subject sample is larger compared to other rTMS studies in awake non-human primates (Gerits et al. 2011; Salinas et al. 2011; Papazachariadis et al. 2014; Balan et al. 2017), it is still relatively small compared to human cohorts and this is a limitation to the current study. In rTMS and TBS studies, larger samples are especially important given the high variability of their effects (Suppa et al. 2016; Goldsworthy et al. 2021). Thus, the results presented in this work should be interpreted with caution and replicated in a larger cohort of healthy subjects, especially in the post-mortem evaluation. However, they provide some needed information as to the effects of clinically relevant courses of TBS (same parameters, same coil and equipment, same duration) 68 in an intact primate brain and permit a tentative comparison to results obtained in clinical populations. Despite these limitations, the non-human primate model has proven useful in studying and developing brain stimulation techniques (Lisanby and Belmaker 2000; Perera et al. 2007; Peterchev et al. 2008). Further, the data presented in this work are supported by results from human studies. 2.5 Conclusion In conclusion, in healthy brains, acute cTBS applied over the motor cortex induces a decrease in dopamine release in the bilateral striatum, which appears to be transient as changes were not evident the day after chronic cTBS delivery. Yet changes in cortical excitability persisted even 24 hrs after the end of chronic cTBS, suggesting a cumulative neuroplastic effect. In contrast, iTBS did not significantly modulate dopamine release either acutely or chronically nor affect cortical excitability. Importantly, our study showed that cTBS leads to a decrease in dopamine release in vivo, which may have implications for the choice of and delivery of repetitive non-invasive brain stimulation in clinical populations. 69 Chapter 3: Evaluation of functional connectivity In this chapter, we report changes in functional connectivity following a clinical course of TBS. This study assesses the interaction of regions within the motor loop, including the motor cortex, putamen, and the motor thalamus. Connectivity evaluations were carried out using rsfMRI and a seed-based analysis approach. 3.1 Introduction Repetitive TMS and TBS can alter the activity of brain regions that are functionally and anatomically connected to the stimulated area. Early PET studies allowed visualization of these remote modulatory effects after stimulation over the motor cortex (Paus et al. 1998; Siebner, Rossmeier, et al. 2000), the frontal eye field (Paus et al. 1997), the mid-dorsolateral prefrontal cortex (Strafella et al. 2001), and the lateral premotor–prefrontal cortex (Strafella et al. 2001). Similarly, fMRI studies have recorded local and distal activity modulation following rTMS over the motor cortex (Bestmann et al. 2005; Cardoso et al. 2008), the somatosensory cortex (Schneider et al. 2010), the parietal cortex (Sack et al. 2002) and the prefrontal cortex (Cardoso et al. 2008). By altering the activity of stimulated and related areas, rTMS can modify how these brain regions interact with each other by modulating their connectivity. Functional MRI studies enable the assessment of functional connectivity by examining the temporal correlation of BOLD signals (Lowe et al. 2000). This technique allows researchers to understand how different brain areas work together during various cognitive and motor tasks (Rissman et al. 2004; Tung et al. 2013), thereby revealing the strength of inter-regional cooperation. 70 Functional connectivity can also be evaluated at rest (i.e., in the absence of stimuli or tasks) to assess the inherent organization and function of the brain, providing insights into the brain's intrinsic architecture and the level of communication between different regions (Biswal et al. 1995; Salvador et al. 2005). Clinically, the study of resting state connectivity can help to understand the functional neuroanatomy of a healthy brain and how and when these brain connections are affected by disease or injury. It can also serve as a biomarker to identify abnormal biological processes, brain disorders, and disease progression (Greicius 2008; Hohenfeld et al. 2018) and to assess treatment responsiveness (Sarpal et al. 2016; Moreno-Ortega et al. 2019; Mehta et al. 2021; Taylor et al. 2021). Repetitive TMS can target distal interconnected networks by stimulating proximal accessible areas that are part of a given connectivity network, inducing neuronal plasticity and restructuration of neuronal networks (Kozyrev et al. 2018). Clinically, this attribute is relevant as it has been suggested that rTMS is capable of modulating dysfunctional networks in psychiatric (Kozel et al. 2011; Eshel et al. 2020; Zheng et al. 2020) and motor disorders (Chou, You, et al. 2015; Wadden et al. 2019; Mi et al. 2020). While there are multiple connectivity-based rTMS studies, the effects of rTMS on brain connectivity are still not fully understood. The currently available literature is affected by the heterogeneity of study designs, participant populations, and data acquisition and analysis methods, adding another layer of complexity to the characterization of rTMS effects in connectivity. Thus, further studies of rTMS are still necessary to unveil the impact of different rTMS protocols. In this study, we aimed to investigate the effects of continuous and intermittent TBS on brain connectivity when applied over the left motor cortex region. Based on results from Chapter 71 2, we hypothesized changes in connectivity would be observed between the motor cortex and the striatum. Also, based on known structural and functional connections, we expected changes in regions within the cortico-striatal-thalamic-cortical (CSTC) loop. Thus, we evaluated connectivity before and after stimulation and sha delivery between regions of the CSTC motor loop: the motor cortex, putamen, and thalamus. 3.2 Methods The section below describes the methods for resting state functional MRI (rsfMRI) acquisition and analysis. Details regarding the animal subjects, characteristics, training, and stimulation protocol have been previously described in Chapter 2. 3.2.1 Functional MRI acquisition Acquisition of rsfMRI was carried on the same session as T1-weighted image and MRS at the University of British Columbia Research Facility on a Philips Achieva 3.0T MRI scanner (Phillips Healthcare, Andover, MD). Animals were prepared for scan acquisition as described in Chapter 2. Briefly, animals were given ketamine (10 mg/kg IM) and atropine to allow IV placement, intubation, and transportation to the scanning suite. Animals were positioned supine on the MRI table (see Fig. 2.5) and were kept under light anesthesia during scan acquisition with low doses of sodium pentobarbital IV (30 mg/kg/h IV). Vital signs were monitored throughout the scanning session. Eleven healthy NHPs underwent cTBS, iTBS, or sham stimulation and rsfMRI assessment. NHP underwent one or up to three clinical simulation courses, each separated by 4.5 to 9 months. MR sessions were carried out before the first stimulation session and one day after a 72 clinical course of TBS or sham delivery (Figure 1.1). A single baseline MR session was acquired for each animal during the first course of clinical stimulation to decrease the burden on the animals and facilitate scheduling. Thus, if an animal had already undergone a trial of chronic stimulation, no pre-stimulation scan was acquired for the second trial. BOLD scans were acquired with a single shot echo-planar imaging (EPI) sequence with T2 = 2000 ms; TE =30 ms, flip angle h = 90, voxel dimension = 3 mm3, 20 slices, FOV = 2180 x 79 x 180 mm, scan time = 8 min. In total, nine fMRI assessments were carried out post-cTBS, seven post-iTBS, and six post-sham. 3.2.2 Image preprocessing All preprocessing procedures were carried using the FMRIB Software Library toolbox (FSL; http://www.fmrib.ox.ac.uk.). Preprocessing included brain extraction, motion correction, spatial smoothing (Gaussian kernel of full-width at half-maximum [FWHM] 3 mm), high-pass temporal filtering (Gaussian-weighted least-squares straight line fitting with sigma = 100 s), low-pass temporal filtering, slice timing correction, and intensity normalization. Signals derived from WM and CSF were removed from the preprocessed functional images. Briefly, we created a subjects-specific WM and CSF mask by segmenting the animal's anatomical T1-weighted image into three tissues: grey matter (GM), WM, and CSF. WM and CSF masks were then eroded twice to ensure that only voxels from the CSF and WM were included in their respective masks, which were then normalized into the functional space. Next, the normalized eroded masks were used to extract WM and CSF mean time series from the preprocessed data by averaging the time courses from all the voxels within the masks. These GM 73 and CSF time series were then removed from the preprocessed functional data using linear regression. 3.2.3 Seed-based analysis We carried out a seed-based analysis using regions of interest (ROIs) associated with the 112RM-SL atlas template (Moirano et al. 2018). The associated regions of interest were normalized to the NHP anatomical T1-weighted image and then transformed into the functional image space. Seed-region masks were created using the predefined atlas area for left and right motor cortex, putamen, and the thalamus's ventral lateral and ventral anterior nucleus. A new mask was created by adding the ventral and lateral thalamus nuclei mask and was called the motor-thalamus. These masks were eroded and manually modified to ensure that only voxels from the ROIs were included (Figure 3.1). Masks were overlaid on the subject's functional image by normalizing the 112RM-SL atlas (12 degrees-of-freedom [DOF] linear affine transformation) to the subject T1-weighted image, followed by a second normalization to the functional space (6 DOF linear affine transformation). The placement of the seed masks was visually inspected and modified if necessary. Figure 3.1 Coronal view of 112RM-SL atlas with the seed's mask. 74 Mean time series from the seed masks were extracted to carry pair-wise correlation between all regions using Pearson's correlation. Fisher's transformation converted correlation coefficients (Person's r) into normally distributed scores (z-scores). Paired t-test was then used to compare the correlation z-scores for baseline and post-stimulation scans. Holm-Sidak was used to correct for multiple comparisons. Furthermore, given that 6 animals underwent both cTBS and iTBS evaluation, RM ANOVA was carried out to evaluate baseline, cTBS, and iTBS Z-scores along Tukey correction for multiple comparisons. Furthermore, as an exploratory analysis, we used results from Chapter 2 to investigate the relationship between connectivity, dopamine modulation, and cortical excitability. Pearson's correlation was used to compare [11C]raclopride binding and RMT to functional connectivity measurements. Specifically, we compared the baseline connectivity between the motor cortex and ipsilateral putamen to the percentage [11C]raclopride BPND changes (((Acute-Baseline)/Baseline)*100). We also investigated the correlation of RMT measurements (%MSO) to connectivity (z-scores) between the stimulated motor cortex and contralateral motor cortex at baseline and post-stimulation. 3.3 Results Paired t-test of z-scores from sham connectivity assessment showed no significant difference between baseline and post-sham scores derived from any of the paired-wise correlations (p > 0.9). Paired t-test of baseline and post-cTBS z-cores indicated an increase in connectivity between the left motor cortex and the left putamen (p = 0.022, Fig. 3.2). Additionally, we found a decrease in connectivity between the left putamen and the left motor thalamus (p = 0.041), as 75 well as a decrease in connectivity between the right putamen and the right motor thalamus (p = 0.018). However, none of these comparisons were significant after correction for multiple comparisons. Comparison of baseline and post-iTBS z-scores indicated a decrease in connectivity between the right motor cortex and the right putamen (p = 0.009) after iTBS delivery, but similar to the cTBS assessment, changes in the z-score were not significant after correction for multiple comparisons (Fig. 3.2). Figure 3.2 Functional connectivity modulation. Modulation of connectivity following continuous and intermittent theta burst stimulation (cTBS, iTBS). P values derived from paired t-test of baseline and post-stimulation z-scores before correction for multiple comparisons. Green arrows indicated an increase in connectivity, and red arrows indicated a decrease in connectivity compared to baseline. Additionally, RM ANOVA carried out in the 6 animals with both iTBS and cTBS assessments revealed a significant stimulation effect (Fig. 3.3). Comparison to baseline assessment revealed an increase in connectivity between the left and right motor cortex following cTBS (p < 0.001) and iTBS (p = 0.011). Comparison between baseline and iTBS assessment also confirmed the decrease in connectivity between the right putamen and the right motor thalamus (p = 0.04). After correction for multiple comparisons, only the connectivity increase between the left and right motor cortex post-cTBS was significant (p < 0.001). 76 Comparison of iTBS and cTBS z-scores showed connectivity between the right motor cortex and the right putamen to be lower after iTBS than cTBS (p = 0.01), and this difference remains significant after correction for multiple comparisons (p = 0.03). Figure 3.3 RM ANOVA assessment of functional connectivity. Assessment of connectivity scores at baseline, post-cTBS, and post-iTBS from a subset of animals (n=6). P values derived from RM ANOVA of z-scores before correction for multiple comparisons. Green arrows indicated an increase in connectivity, and red arrows indicated a decrease in connectivity compared to baseline. Assessment of the relation between connectivity and [11C]raclopride BPND change in the cTBS cohort revealed a significant positive correlation between tracer binding in the left putamen following acute stimulation and connectivity between left motor cortex to left putamen (r = 0.8, p = 0.01, Fig. 3.4) . We found no significant correlation between connectivity and BPND change for the iTBS and the sham cohort (p > 0.1). Connectivity and cortical excitability comparison also revealed no correlation between RMT measurements and connectivity assessments for any cohort (p > 0.1). 77 Figure 3.4 Relation of acute dopamine modulation and baseline connectivity. Correlation of acute [11C]raclopride BPND change (%) from the left putamen to connectivity (z-scores) between left motor cortex to ipsilateral putamen. BPND % change was computed as ((acute-baseline)/baseline)*100. 3.4 Discussion Functional MRI is a prominent tool that has helped to examine brain activity non-invasively. The study of resting state information enables the assessment of intrinsic brain activity and functional organization without cognitive and sensory inputs. In the study of rTMS, the evaluation of functional connectivity at rest is used to illustrate the effects of stimulation on those intrinsic processes. We took advantage of this technique in the current study and evaluated resting state connectivity changes after a clinical course of TBS over motor cortex. We assessed connectivity between regions of the CSTC motor loop and performed a pair-wise seed-based analysis. We evaluated the connectivity between these regions as it might facilitate the translation of current results to parallel CSTC loops (Alexander et al. 1986; Haber 2003, 2016; Metzger et al. 2013). CSTC circuits play an important role in cortical-subcortical integration, connecting functionally-segregated higher-order cortical regions (e.g., DLPFC, motor cortex, anterior cingulate cortex) to basal ganglia (i.e., striatum, thalamus, and subthalamic nucleus) 78 enabling the integration of motor, sensory and cognitive processes (Alexander et al. 1986; Haber 2003; Romanelli et al. 2005). Clinically, the functional connectivity of CSTC loops is relevant as aberrant communication of regions within these networks is thought to contribute to the pathophysiology of several psychiatric (Bora et al. 2012; Kerestes et al. 2015; Han et al. 2017; Ramkiran et al. 2019) and motor disorders (Loonen and Ivanova 2013; Hengenius et al. 2022). These characteristics make CSTC loops a potential therapeutic target (Dunlop et al. 2016; Peters et al. 2016; Rǎdulescu et al. 2017; Mi et al. 2020). 3.4.1 CSTC connectivity modulation In the current work, our trend-level findings showed a distinctive topological effect of cTBS and iTBS in functional connectivity that goes beyond the inhibitory and excitatory paradigm. Continuous TBS seemed to elicit a more widespread effect compared to iTBS. Delivery of iTBS showed modulatory effects only in the right hemisphere, and specifically, it decreased the connectivity between the putamen and the motor-thalamus. The evaluation of cTBS effects showed increased connectivity between the stimulated left motor cortex and the ipsilateral putamen and a decreased connectivity between the putamen and the ipsilateral motor-thalamus in both hemispheres. However, these changes were ultimately non-significant after correction for multiple comparisons, which might result from our small sample size. For reference, in the current work, the sample size was between 6 and 9 subjects per stimulation cohort, while some human studies have been carried out with at least double the number of participants (see (Beynel et al. 2020)). Thus, these results should be considered preliminary and in need of replication in a larger sample. 79 The observed trend-like modulation of corticostriatal connectivity might have been derived from compensatory processes originating from chronic motor cortex inhibition and, as a result, chronic inhibition of corticostriatal inputs. Based on the results presented in Chapter 2, we can assume cTBS effectively reduced motor cortex inputs over the putamen, as illustrated by the reduction of dopamine release. Thus, it might be possible that the chronic inhibition of corticostriatal projections, through daily cTBS sessions, induced a compensatory increase in connectivity to counterbalance the cTBS-induced reduction of cortical input to the putamen. This hypothesis is further supported by the lack of chronic changes in dopaminergic activity in the presence of decreased cortical excitability, indicating that, even when activity in the motor cortex is lowered, the input to putamen remains similar to pre-stimulation levels. As previously mentioned, corticostriatal changes in connectivity following cTBS were only trend-like. Further studies should replicate these results, especially since current literature has presented conflicting results, reporting both increases (Cocchi et al. 2015) and decreases (Heinen et al. 2017) in corticostriatal connectivity following cTBS. Finally, we did not observe changes in corticostriatal connectivity following a clinical course of iTBS. These results align with Chapter 2 findings, where we reported no modulation of cortical excitability or dopamine post-iTBS. We found cTBS-induced decrease in dopamine correlated to baseline connectivity. This might suggest that baseline assessments of functional connectivity could predict the dopaminergic response in the striatum to acute cTBS delivery. Furthermore, this might also indicate that, in patient populations where these connections are affected, cTBS effects on dopamine release might be limited. 80 The presented results also suggest a possible modulatory effect of iTBS and cTBS on connectivity between the putamen and the motor-thalamus. These changes in connectivity could have been facilitated through direct anatomical connections originating from the thalamus to the putamen or indirect connections from the putamen to the thalamus via the pallidum. If further studies confirm these effects, stimulation could be used to target these connections in a patient population with abnormal striatal-thalamic connections such as Tourette's syndrome (Ramkiran et al. 2019), Parkinson's (Martel and Galvan 2022) and depressive disorders (Lu et al. 2016; Zhang et al. 2018). 3.4.2 Interhemispheric connectivity Evaluation using RM ANOVA revealed a significant increase in connectivity between the stimulated motor cortex and the contralateral motor cortex after iTBS and cTBS. This increase in connectivity is not surprising as the modulatory effects of rTMS and TBS over the homologous target have been extensively reported in human and animal studies (Ishikawa et al. 2007; Di Lazzaro et al. 2008; Suppa et al. 2008; Salinas et al. 2011) and are in line with known structural trans-callosal connections (Rouiller et al. 1994). These results add to the conflicting observations of connectivity assessments of TBS and other rTMS protocols, with some authors reporting no change (Agnew et al. 2018), increase (Allendorfer et al. 2012; Nettekoven et al. 2015; Alkhasli et al. 2019) or decrease (Andoh et al. 2015; Griffis et al. 2016; Tang et al. 2019) in interhemispheric connectivity following stimulation. Furthermore, the similarity between iTBS and cTBS is in conflict with a previous study (Watanabe et al. 2014), where the comparison of inhibitory and excitatory forms of rTMS revealed a bidirectional effect on connectivity modulation between the left and right motor cortex. In their work, Watanabe et al. 81 found that inhibitory QSP increased interhemispheric motor cortex connectivity while excitatory QPS reduced it immediately after stimulation (Watanabe et al. 2014). This difference might have resulted from the discrepancy in stimulation protocols (i.e., QPS and TBS) or be the result of the difference in the time of the assessment (Battelli et al. 2017), which could suggest a delayed compensatory increase in connectivity as an attempt to maintain global homeostasis. Given that the interaction between the left and right motor cortex is thought to be inhibitory (Ishikawa et al. 2007; Mochizuki et al. 2007; Suppa et al. 2008), the observed increase in connectivity between the two motor cortices would mean the inhibitory and modulatory effects of these regions over each other might be stronger. Thus, patients population with disrupted interhemispheric connections, such as those recovering from a stroke, could benefit from the chronic delivery of TBS (Nyffeler et al. 2019). 3.4.3 Study limitations NHPs are a relevant subject in the study of rTMS effects, especially those concerned with functional connectivity since macaque and human brains share anatomical and functional similarities, including resting state functional connectivity topology (Hutchison and Everling 2012). However, NHP studies come with limitations: as mentioned in Chapter 2, the current work is limited by the intrinsic characteristics of the animal subjects. Differences to human subjects, such as the smaller size of the head and brain, the insertion of facial muscles, and thicker skulls that ultimately increase the space between the coil and the brain cortex, might alter the effects of TBS. Another relevant limitation that might affect the translation of current results is the acquisition of rsfMRI under general anesthesia. The delivery of ketamine was used to allow for 82 animal preparation. Ketamine has been reported to have a concentration-dependent effect on cerebral blood flow that could ultimately modify BOLD signal acquisition (Långsjö et al. 2004). However, given that ketamine was delivered at least 2 hrs from image acquisition the effects of the sedative should have been minimal, as previously reported in baboon studies (Salinas et al. 2011, 2013, 2016). We also administrated sodium pentobarbital to maintain light anesthesia during image acquisition. Barbiturates have been reported to decrease global oxidative metabolism and cerebral blood flow (Wechsler et al. 1951; Slupe and Kirsch 2018), which might ultimately affect the recorded BOLD signal. Furthermore, the dampening effects of pentobarbital are variable among brain regions (cortex vs. subcortical regions) and may have contributed to a loss of strength in the cortico-striatal connections during scan acquisition. However, the doses administrated in the current study were minimal (below the recommended anesthetic level), just enough to maintain the animal immobile, and thus should have minimal effect on our measurements. Nevertheless, it cannot be excluded that the brain activity and connectivity between regions were dulled, which could have led to the non-significance in our results. While the effects of the utilized anesthetics on rsfMRI are not apparent, it is certain it modulates brain activity and could ultimately alter resting state recordings. However, many other animal studies have acquired resting state measurements under different anesthetics (Vincent et al. 2010; Hutchison et al. 2011, 2013; Mars et al. 2011; Matsui et al. 2011; Salinas et al. 2011, 2013; Hutchison and Everling 2012). The advantages of anesthesia in animal studies outweigh its limitations, as it allows the acquisition of images without motion, reduces stress in the animal, and can eliminate the recording of conscious processes such as passive mind wandering, changes in attention, and active monitory and arousal (Hutchison et al. 2012). 83 3.5 Conclusion We found that while iTBS and cTBS delivery typically produce diametrical effects on cortical excitability (Huang et al. 2005), our study revealed that effects in functional connectivity do not follow this opposing convention. In this work, we found a significant increase in rsFC between left and right motor cortex, both after iTBS and cTBS. These results are supported by a recent meta-analysis that reported that studies of rTMS on rsFC more consistently observed an increase in connectivity regardless of the protocol used (Beynel et al. 2020). While the mechanisms underlying TBS-induced modulation of rsFC are unclear, studies have suggested that these effects are the result of the propagation of the stimulation effects through anatomical connections (Vink et al. 2018). Thus, the modulatory effects observed in the current study might have been facilitated through 1) transcallosal white matter connecting left and right motor cortex, 2) cortico-striatal projections (Yamawaki and Shepherd 2015; Charpier et al. 2020), 3) cortico-thalamic projections (Molinari et al. 1985), and 4) thalamo-striatal connections or striatal-pallidal-thalamic connections (Parent and Parent 2006). Another possible mechanism for TBS-induced connectivity changes is the entrainment of endogenous brain oscillation (Thut and Miniussi 2009). The stimulation of the targeted area allows neural synchrony between functionally connected areas to be modulated, altering their connectivity. Alternatively, as previously mentioned in this chapter, rsFC changes could derive from homeostatic processes that, with the objective of maintaining global brain homeostasis, induce the reorganization of highly connected regions to compensate for rTMS-induced changes in activity (Watanabe et al. 2014). Ultimately, some of the results presented in this work lead to more questions and should be further studied in a larger sample. However, the current work 84 illustrates the relevance of resting state functional connectivity evaluation following rTMS stimulation. 85 Chapter 4: TBS-specific metabolic patterns, a pilot study In this chapter, we present a pilot study that evaluated changes in metabolic connectivity following TBS delivery. In this proof-of-concept study, we employed PET-FDG and a method previously validated for NHP to obtain stimulation-specific metabolic patterns (Ma et al. 2012). While our results need further validation, they provide information that may be used to generate hypotheses for future studies and illustrate the utility of PET-FDG and metabolic connectivity assessments in the characterization of rTMS effects. 4.1 Introduction PET-FDG ([18F]-2-deoxy-2-fluoro-D-glucose) imaging is a valuable tool in the study of brain function. As a glucose analog, [18F]FDG enters the brain via a glucose transporter and is taken up by the cells, where it is metabolized by cerebral hexokinase resulting in the production of the radiometabolite FDG-6-phosphate (FDG-6-P). The radiometabolite FDG-6-P is only very slowly degraded, thus essentially trapped inside the cell during the PET assessment time frame (60-120 min PET scan). As a result, tracer uptake can be used as a surrogate marker for glucose metabolism, and given that glucose utilization increases along with neural activity, PET-FDG can be used to indirectly measure brain activity (Sokoloff et al. 1977). Like fMRI, PET-FDG can assess functional interactions between regions by modelling the variability of images as spatially distributed networks (Moeller and Strother 1991; Alexander and Moeller 1994). The scaled sub-profile model (SSM) method can be used to explore these networks. SSM is a spatial covariance method based on principal component analysis (PCA) that investigates the subject-by-region effects from functional brain images. 86 SSM-PCA decomposes sources of variation in the data into a set of linearly uncorrelated vectors called Principal Components (PCs) (Ma et al. 2007; Habeck et al. 2008). For each PC, two outputs of interest are computed: 1) a set of subject scores per each subject, which indicate how much a subject "expresses" a given PC, and 2) voxel loadings, which indicate the contribution of each voxel to the spatial covariance pattern along each PC. To identify significant topographic covariance profiles that best distinguish between two populations, PCs are judged by their discriminative accuracy. When applied to PET-FDG images, SSM-PCA can obtain metabolic patterns specific to a given condition, such as a disease or an intervention. For example, SSM-PCA has been used to identify metabolic patterns specific to patients with Parkinson's (Eidelberg et al., 1994; Mudali et al., 2015; Spetsieris et al., 2013) and Alzheimer's (Peretti et al. 2022) diseases. Metabolic patterns have also been used to describe changes in metabolic connectivity following a therapeutic intervention (Fukuda et al. 2001; Ma et al. 2012). Thus, PET-FDG provides an alternative to rsfMRI in the assessment of connectivity. Although fMRI has proven to be a valuable and versatile technique, it presents several limitations. One of the most relevant shortcomings of fMRI is the limited reproducibility caused due to the low signal-to-noise ratio of the BOLD signal. In this regard, PET-FDG evaluations are an alternative to fMRI, showing a better signal-to-noise ratio, which results in robust and reproducible measurements (Ma et al. 2007; Spetsieris et al. 2013; Veronese et al. 2019) even in small patient samples (Schindlbeck and Eidelberg 2018; Ripp et al. 2020). In the study of rTMS effects, PET-FDG has been used to evaluate activity modulation in specific brain regions. These studies have shown that rTMS can modulate metabolic activity in the targeted area and regions distal to the stimulated site (Kan et al. 2019; Park et al. 2019; Xu et 87 al. 2022). However, to our knowledge, no studies have evaluated the effects of rTMS on glucose metabolism at a brain-wide level. We carried out a pilot study to assess the viability of using PET-FDG to investigate the effects of rTMS on metabolic connectivity. In this proof-of-concept study, we used SSM-PCA to compare baseline to post-iTBS, post-cTBS, and post-sham metabolic images to explore stimulation derived metabolic networks. 4.2 Methods Animal training and stimulation delivery have been explained in detail in previous chapters. Briefly, 11 animals (4 females) were randomly assigned to receive sham, cTBS, or iTBS. Some underwent more than one trial of clinical stimulation and neuroimaging sessions. One PET-FDG scan was acquired before the first stimulation session (baseline scan) and one 24 hrs after a series of awake stimulation sessions. A single baseline PET-FDG session was acquired for each animal before the first stimulation trial (before any intervention) and was used as the baseline for all the stimulation experiments. Thus, if a subject participated in three stimulation trials, the same baseline was used to compare to the three post-intervention images. In total, 4 sham, 7 iTBS, and 6 cTBS PET-FDG evaluations were carried out. 4.2.1 FDG acquisition PET-FDG images were acquired on a high-resolution research tomograph (ECAT HRRT, CPS Innovations, Knoxville, TN, USA) at the University of British Columbia. Animal preparation started the day before scan acquisition. The animal was transferred from its large housing pen to a smaller squeeze cage the night before and left overnight in the housing room 88 without access to food to obtain fasting glucose plasma levels for the scan the next day; water was available ad libitum. On the morning of the scan, the cage was transferred to a procedure room to enable easy access for radiotracer administration. The animal's housing partner was also moved to a squeeze cage and placed next to each other to reduce separation anxiety and stress. Injection of [18F]FDG tracer was carried out in the awake animal to minimize the potential effects of anesthesia on cerebral metabolism (Brownell et al. 2003; Ma et al. 2012). On the day of scan acquisition, the [18F]FDG dose was prepared in the PET suite (average 196.1 MBq ± 22.2, adjusted to a fixed volume of 1.5 mL in sterile saline) and transported to the animal unit in a lead-shielded syringe. It was immediately injected intramuscularly (tight muscle) instead of intravenously to reduce the risks and stress of IV injection while awake. The investigator left the room, leaving the animal and its partner alone, and tracer uptake was allowed for 40 minutes. During this time, the animal remained awake in the dimly lit procedure room. Once the 40 minutes had passed, the animal was sedated with ketamine (10mg/kg IM) and given atropine (0.05 mg/kg IM) to reduce secretions and to facilitate transport to the PET suite, where the animal was intubated and placed under light anesthesia (isoflurane 1– 1.5% in 100% oxygen). A blood sample was drawn immediately upon arrival to the PET suite (i.e., about 60 minutes post tracer injection) to assess plasma glucose concentration (average 3.3mmol/L). Starting at 80 minutes post tracer injection, a 30-minute scan was acquired. A second blood sample was obtained at the end of the scan to verify the stability of plasma glucose over time. 89 4.2.2 Image processing The acquired data were reconstructed using OSEM-OP algorithm (Comtat et al. 2004). Image preprocessing was done using the FMRIB Software Library toolbox (FSL; http://www.fmrib.ox.ac.uk.), and MRIcroGL (https://www.mccauslandcenter.sc.edu/mricrogl/). Images were reoriented into Neurological Convection and cropped onto a small matrix. Voxels outside the brain were eliminated manually and with the help of a binary brain mask derived from the subject's T1-weighted image. To create the mask, we used the BET tool from FSL to extract the brain from the T1-weighed image. The extracted brain was normalized to the FDG image (6 DOF linear affine transformation). Once in the FDG space, the extracted brain was converted into a binary mask. We used this binary normalized mask on the [18F]FDG image to eliminate voxels not within the mask. Any remaining non-brain voxel was deleted manually using MRIcroGL. Finally, to facilitate the voxel-based analysis, the brain-only FDG images were normalized into a macaque brain template (Black et al. 2001). 4.2.3 Pattern Identification To identify stimulation-derived metabolic patterns, we performed a PCA analysis on the preprocessed data using an automated software package (SSMPCA Toolbox) available online (http://www.fil.ion.ucl.ac.uk/spm/ext) and customized software from the Feinstein Institute (ScanVP: freely available at http://www. feinsteinneuroscience.org/software). We performed a voxel-level PCA analysis for each stimulation cohort, using baseline and post-stimulation FDG images. We then selected the relevant stimulation-related PCs. To do so, we identified the PCs that accounted for at least 5% of the total subject-by-region variability. We then carried paired t-test to evaluate if the subjects' scores of those PCs were significantly 90 different between baseline and post-intervention assessment. PCs that resulted in a p < 0.05 were considered stimulation-specific. If more than one PC fitted these characteristics, PCs were entered into a logic regression model to create a stimulation pattern. For anatomical visualization and localization, the stimulation patterns were superimposed on a macaque MRI brain template (112RM-SL (Moirano et al. 2018)). 4.2.4 Pattern expression assessment We compared the expression of stimulation patterns between the scans from the stimulation cohort and the remaining baseline scans not used for pattern identification. Stimulation pattern expression was quantified for each scan using an automated single-scan routine (Ma et al. 2007; Tang et al. 2010). The network values were z-transformed for the relevant derivation sample and adjusted so that the mean for the control scans was zero. 4.3 Results SSM-PCA analysis of the sham cohort yielded 4 PC with an accounted variance greater than 5%. Paired t-test showed subjects scores were no significantly different for any PC before and after sham delivery (p > 0.2). Similarly, the cTBS assessment resulted in 6 out of 12 PCs that accounted for more than 5% of variance but paired t-test showed no significant differences in PC expression between baseline and post-cTBS (p > 0.1). Evaluation of baseline and post-iTBS scans resulted in 7 out of 14 PCs that made the 5% variance cut off; out of those PCs, paired t-test revealed two PCs whose expression (subject scores) were significantly different between baseline and post-stimulation assessments (PC1 p = 0.02, PC2 p = 0.04). The linear combination of these PC, called iTBS-pattern, accounted for 27 91 % of the total subject-by-region variability (Figure 4.1). This iTBS-pattern was characterized by a relative increase of metabolic activity in the occipital cortex, cerebellum, motor thalamus, and in a small part of the somatosensory cortex with a relative decrease of metabolism in the bilateral somatosensory area, the premotor cortex, the anterior cingulate cortex, temporal cortex, the insula, the caudate and the putamen. Figure 4.1 Intermittent TBS-specific metabolic pattern Metabolic pattern displayed as z-scores. Coronal (A, B), axial (C), and sagittal (D) view of the iTBS-specific metabolic pattern. E) shows the comparison of the expression (i.e., subject scores) of the pattern in pre-and post-iTBS delivery (Identification group), as well as the expression on scans acquired at baseline from the four subjects that were not part of the iTBS cohort. We compared the expression of the iTBS-pattern on the four baselines PET-FDG images from the subjects that did not undergo iTBS stimulation, as shown in Figure 4.1E. An unpaired t-test revealed a trend to a significant difference between these scan scores and the post-iTBS scans (p = 0.056). 92 4.4 Discussion PET can evaluate the glucose utilization of living cells in a given brain region using [18F]FDG. In the study of brain metabolism, PET-FDG signal measures neuronal oxidative metabolism and astrocytes glycolysis, mainly reflecting synaptic processes (Stoessl 2017). This tool has proven helpful in the evaluation of dysfunctional brain activity in different brain disorders (Poston and Eidelberg 2012; Boccalini et al. 2022) and aided in the understanding of the effects of brain stimulation methods, including rTMS (Kan et al. 2019; Park et al. 2019; Xu et al. 2022). PET-FDG assessment of brain activity is based on the coupling between synaptic transmission and local glucose consumption. In the era of brain connectivity, [18F]FDG-PET evaluations have been used to evaluate metabolic connectivity by assessing the relationships between tracer uptake in different brain regions across a homogeneous group of subjects. Metabolic connectivity is based on the premise that brain regions whose metabolism is related are functionally interconnected. Although studies have evaluated changes in brain metabolism following rTMS, these studies have only evaluated regional metabolism (Kan et al. 2019; Park et al. 2019; Xu et al. 2022). As discussed in Chapter 3, the effects of rTMS are brain-wide, not only modulating local brain activity but also the activity and connectivity of brain regions associated with the stimulated site and other functional and anatomical related areas. Thus, we tested the feasibility of using PET-FDG to evaluate the effects of TBS on metabolic connectivity for the first time. The current study design allowed for the acquisition of metabolic images that provided information on the resting state activity of the awake animal. Furthermore, tracer uptake was allowed in the awake subjects in a quiet room under a setting designed to reduce stress and 93 anxiety during the procedure. This setup ensured that the effect of anesthesia on metabolic activity was minimal, illustrating how PET-FDG, combined with network analysis, is a relevant tool in assessing resting state activity in animals, not only for the assessment of effects of external interventions but also in the characterization of the inherent metabolic interactions between brain regions. 4.4.1 Post iTBS metabolic pattern Comparison of metabolic connectivity between baseline and post-iTBS evaluations suggested that stimulation modulates connectivity in a brain-wide network. The prospective iTBS-pattern included regions functionally related to motor cortex and motor processes, such as the somatosensory and premotor cortex, the cerebellum (Hanakawa et al. 2003; Otten et al. 2012; McGregor and Gribble 2017), and regions from the CSTC loop (caudate, posterior putamen and motor thalamus) (Haber 2003; Greene et al. 2020), similar to rsfMRI findings from Chapter 3. This iTBS-pattern did not include the motor cortex, which might indicate that most synaptic activity changes are mainly located in regions anatomically and functionally related to the stimulated area. These results align with the lack of cortical excitability changes post-iTBS reported in Chapter 2 since studies have indicated that TBS modulates cortical excitability changes through local interneural circuits (Hamada et al. 2013). Thus, the difference between baseline and post-iTBS metabolism might reflect the absence of synaptic changes in the local circuitry. Modulation of activity in the other regions, such as the insula, has been observed after motor cortex stimulation in a task-based fMRI. The authors found a decrease in insular activity immediately after stimulation (Yoo et al. 2008). Similarly, a CBF PET study recorded blood 94 flow modulation in the insular cortex following motor cortex stimulation with epidural electric stimulation (García-Larrea et al. 1999) and subthreshold LF-rTMS (Speer et al. 2003a). These modulatory effects align with reports from monkey and human studies of anatomical (Jane et al. 1961) and functional (Nomi et al. 2016) connectivity between the motor cortex and the insular cortex. The occipital cortex has also been reported to be functionally modulated following rTMS over the motor cortex (Speer et al. 2003a). As a tractography study showed, white matter connections might have facilitated these effects (Guye et al. 2003). Many regions identified in our iTBS-pattern are part of functional resting state networks in monkeys and humans, specifically the default mode network (anterior cingulate cortex), the somatomotor network (motor, premotor, and somatosensory cortex), and the salience network (SN; temporal cortex, anterior cingulate, insula and caudate) (Seeley et al. 2007; Hutchison et al. 2011; Hutchison and Everling 2012; Seitzman et al. 2019). Functional MRI studies have reported modulation of connectivity of these networks by rTMS when applied over the motor cortices (Watanabe et al. 2014; Bharath et al. 2017; Ji et al. 2017; Beynel et al. 2020). These results also suggest iTBS modulate metabolic activity in regions that are part of resting state networks measured with rsfMRI. Even though functional and metabolic connectivity measurements reflect different processes (see below), studies have reported the spatial overlap of metabolic and functional networks (Di and Biswal, and Alzheimer’s Disease Neu 2012; Savio et al. 2017). Thus, these studies suggest that current findings reflect connectivity modulation induced by iTBS stimulation in resting state networks. Ultimately, these results need replication given that the assessment of iTBS-pattern expression in the baseline scans (acquired from subjects not 95 part of the pattern identification group) was inconclusive, likely due to the small subject sample. Thus, further studies should implement robust validation methods such as cross-validation. 4.4.2 Sham and cTBS results Assessment of post-cTBS and post-sham evaluations suggested no significant changes in metabolism after delivery, as shown by the lack of PC expression differences before and after stimulation. Interestingly PC1 derived from cTBS showed a similar spatial pattern to the first PC from the iTBS evaluation (Figure 4.2). This similarity might indicate the overlapping effects of both stimulation paradigms. However, given that no cTBS-pattern was observed, no conclusions can be made regarding the origin of this cTBS PC. Figure 4.2 First principal component from cTBS and iTBS evaluation Principal component 1 (PC1) from the voxel-based covariance pattern analysis of metabolic images from the two different stimulation cohorts (cTBS and iTBS) with their associated percentage of accounted variance (VAR). 96 4.4.3 Methods for metabolic connectivity assessments The word “connectivity” in the neuroimaging field is usually understood in terms of fMRI measurements, even though other imaging techniques have coined the same term through the analysis of measurements such as EEG, MEG, and, as shown here, PET-FDG. Thus, a comment should be made regarding the distinction between fMRI and PET-FDG-derived connectivity. Although analysis techniques derived from fMRI have been applied to FDG (see below), they measure and evaluate distinct processes. The distinction between functional and metabolic connectivity is derived from 1) the origin of the signal measured and 2) the different way analyses are carried out due to the lack of temporal resolution in FDG images. Both fMRI and FDG are indirect activity measurements, but they measure distinct processes based on different coupling mechanisms. FDG evaluates glucose consumption which reflects activity at the synapse level. While some studies have suggested the FDG also reflects glucose utilization in astrocytes (Zimmer et al. 2017), FDG uptake in the healthy brain still reflects synaptic activity as neuronal activity results in glucose uptake in astrocytes to meet the energy requirements of neurons (Stoessl 2017). Unlike FDG, functional MRI detects indirect neural activity by measuring the amount of oxygen in blood supplying a given brain region. Analysis of PET-FDG is carried out differently from fMRI, given the absence of temporal information. In contrast, fMRI studies evaluate temporal covariances, FDG studies compare the relationship of metabolic activity across a homogeneous subject population. However, there is a close relationship between metabolic and functional information, as studies have found an overlap in functional and metabolic networks (Passow et al. 2015; Riedl et al. 2016; Savio et al. 2017). 97 We used SSM-PCA to find patterns of metabolic connectivity; however other methods exist and could also provide valuable information regarding the effects of rTMS. Some of these methods are seed correlation and interregional correlation analysis (IRCA)(Lee et al. 2008), independent component analysis (ICA) (Di and Biswal, and Alzheimer’s Disease Neu 2012), and regions of interest (ROI)-based approaches (Sala and Perani 2019). ICA is a voxel-wise method commonly used to analyze rsfMRI data that uses a multivariate approach to discern statistically independent components from a group of PET-FDG images. Like PCA, this approach enables the assessment of resting state networks without an a priori definition of ROIs. IRCA is based on the voxel-wise correlation of the average uptake in a given ROI to the tracer uptake across voxels, enabling the evaluation of networks associated with a specific brain region. Finally, ROI-based approaches are based on pair-wise correlation of the average uptake between different brain regions across subjects, generating a single connectivity matrix per group of participants. This last approach was also used in the current data set but yielded no significant pair-wise correlations, possibly due to the small number of subjects, exemplifying how some connectivity analysis methods might be more adequate than others depending on the characteristics of the data set. 4.5 Conclusion We showed the feasibility of metabolic connectivity analysis using SSM-PCA in a cohort of subjects after a clinical course of TBS delivery. We illustrated and discussed the relevance of metabolic connectivity studies in assessing rTMS effects. Furthermore, in this pilot study, we could identify a metabolic network that seemed to be modulated by iTBS delivery over the motor cortex. This iTBS-derived metabolic pattern included regions known to be part of resting state 98 networks from fMRI studies, such as the default mode network, the salience network, and the sensorimotor network. While validation of this pattern is still necessary, we found the derived metabolic network in agreement with previous reports of activity modulation after rTMS delivery. However, the current findings should be interpreted carefully and taken as a proof-of-concept study. 99 Chapter 5: Evaluation of markers for glial activation and cellular damage In this chapter, we assessed the effects of a clinical course of TBS on neuroinflammatory processes by evaluating markers for microglia activation and tissue injury. We used PET-TSPO, MRS, and immunostaining to investigate changes in markers for neuroinflammation and cellular damage. Additionally, in preparation for the analysis of PET-TSPO images, we also carried out a thorough study to determine the best method of image analysis; this initial validation study has been published: Aceves-Serrano L, Sossi V, Doudet DJ. Comparison of Invasive and Non-invasive Estimation of [11C]PBR28 Binding in Non-human Primates. Mol Imaging Biol. 2021;(0123456789). doi:10.1007/s11307-021-01661-6 (Aceves-Serrano et al. 2021). The majority of the data in this chapter have been submitted for publication: Aceves-Serrano L, Neva JL, Munro J, Vavasour I, Parent M, Boyd LA, Doudet DJ. Evaluation of neuroinflammation following a clinical course of TBS: a non-human primate study. Brain stimulation (under review). 5.1 Introduction Repetitive TMS has the potential to modulate activity in a diverse number of cells, yet there are limited studies evaluating its effects on glial cells, such as microglia, which are prominent in the brain as the primary resident immune cells of the central nervous system. Microglia are one of the key cellular mediators of the neuroinflammatory process (Graeber et al. 2011; Taylor and Sansing 2013), taking part in the immune response of the brain, tissue repair, and plasticity (Delpech et al. 2015; Shemer et al. 2015). Microglia can also respond to electrical activity involved in neuronal signaling (Lenz and Nelson 2018), making it a potential mediator of rTMS effects. Thus, the evaluation of microglia activity following rTMS is relevant in 100 studying the neurobiological effects of rTMS. Furthermore, since microglia play an essential role in immune activation in response to injury (Lenz and Nelson 2018), evaluating their reactivity could help assess the possible induction of neuroinflammation and injurious tissue effects after prolonged rTMS exposure. Reports on rTMS safety have mainly assessed patient comfort (i.e., headache, neck pain, hearing, and others) and seizure risk. Limited studies have explored the safety of rTMS by examining molecular and cellular markers (Liebetanz et al. 2003; Zorzo et al. 2019). As new rTMS paradigms with a higher number of pulses, frequency, and intensity are developed, safety evaluations are imperative, especially in interventions of prolonged exposure (e.g., during clinical delivery). The assessment of neuroinflammatory markers following rTMS may thus be used as a surrogate marker for long-term safety of chronic stimulation, as studies have shown the long-term injurious effect of low-grade inflammation (Qin et al. 2007; Belarbi et al. 2012; Li et al. 2016; Bajwa et al. 2019; Rajesh and Kanneganti 2022). Thus, if such neuroinflammatory processes are presented as a result of stimulation, they could be detrimental. Very few studies have investigated glia response to rTMS (Liebetanz et al. 2003; Zorzo et al. 2019). An early evaluation by Liebetanz et al. assessed glial activity after five days of 1Hz rTMS delivery in rats (Liebetanz et al. 2003). They reported no changes in astrocyte or microglia activation and proliferation. Similarly, a study of very high frequency (100 Hz) rTMS found no microglia nor astrocyte reactivity at the stimulated site after three stimulation sessions (Zorzo et al. 2019). While these studies are relevant, their comparability to human clinical studies is limited due to the nature of the animal model (e.g., small head and brain), the delivery of very high-frequency rTMS, and the number of experimental sessions which differed from clinical stimulation protocols. 101 In the study of neuroinflammation, PET has proven to be a valuable tool to assess neuroinflammatory processes in vivo (Albrecht et al. 2016; Dupont et al. 2017) by targeting the translocator protein (TSPO), a molecule that is over-expressed in activated microglia (Werry et al. 2022). PET-TSPO studies in animals have shown an increase in TSPO expression with neuroinflammation induction (Hannestad et al. 2012; Hillmer et al. 2017), while studies in humans have reported upregulation of TSPO after stroke and traumatic brain injury near the lesion site (Chen and Guilarte 2008; Schroeter et al. 2009; Thiel et al. 2010; Coughlin et al. 2017). Similarly, MRS allows in vivo evaluation of metabolites associated with neuroinflammatory processes and neural integrity (Chang et al. 2013). Elevated MRS measurements of myo-inositol (mI), an osmolyte that is particularly prominent in astrocytes (Brand et al. 1993; Filibian et al. 2012), are associated with neuroinflammation, and activated astrocytes and microglia. Specifically, elevated mI has been reported in neuroinflammatory diseases such as multiple sclerosis (Jung et al. 2020) traumatic brain injury (Yasmin et al. 2019) and neurodegenerative disorders (Huang et al. 1999). MRS can also be used to evaluate N-acetyl-aspartate (NAA) concentration which is often used as a neuronal maker (Nordengen et al. 2015). A decrease in NAA is thought to indicate cellular dysfunction and damage, as well as an underlying dysfunction in myelin maintenance (Demougeot et al. 2001, 2004; Nordengen et al. 2015). In studies of traumatic brain injury and stroke, NAA levels are reduced proportionately to the degree of tissue damage (Wardlaw et al. 1998; Marklund et al. 2006; Moffett et al. 2013) and remain depressed for hours to weeks, depending on injury severity (Wardlaw et al. 1998; Arun et al. 2010; Signoretti et al. 2011). Thus, MRS evaluation of both mI and NAA are useful in the 102 investigation of injury as they permit the indirect assessment of neuroinflammation cellular damage. In this study, we utilized PET and MRS imaging to evaluate the effects of a clinical course of rTMS on inflammatory markers in a healthy subject population. Additionally, post-mortem immunofluorescence imaging was carried in the laboratory of Dr. Martin Parent to assess changes in TSPO expression and will be reported in this chapter. By utilizing these imaging techniques, we aimed to gain a deeper understanding of the effects of rTMS on inflammatory markers. 5.2 Methods Animal preparation, motor cortex location, RMT measurement and stimulation delivery were carried as reported in Chapter 2. 5.2.1 Positron emission tomography PET-TSPO studies were performed on a high-resolution research tomograph (ECAT HRRT, CPS Innovations, Knoxville, TN, USA) at the University of British Columbia. Synthesis of [11C]PBR28 tracer was carried as previously described (Walker et al. 2015). Two [11C]PBR28 scans were acquired: one before (baseline) and one 24 h after the last chronic stimulation delivery. In total, evaluations were carried out in 7 animals that received cTBS, 8 animals that received iTBS, and 7 animals that received sham stimulation. The PET procedures are the same as described in Chapter 2. Briefly, monkeys were positioned in a custom-made PET-compatible head holder and light anesthesia with isoflurane (1-1.5% in 100% oxygen) was maintained for the duration of the scan. The tracer was delivered 103 in 10 mL saline through IV administration over 1 minute (Dose: 179.9 ± 12 MBq, Specific activity: 119.4 ± 78 GBq µmol-1). Dynamic image acquisition started at tracer injection and ended 90 minutes later. Images were reconstructed (OSEM-OP (Comtat et al. 2004)) and smoothed with a 2 mm Gaussian filter. Upon completion, anesthesia delivery was terminated. Animals awoke spontaneously, and no side effects were noted. PET images were registered to an in-house MRI T1 rhesus monkey template with associated predefined hand-drawn regions of interest on the bilateral motor cortex, putamen (a region densely connected to motor cortex), cerebellum, and white matter of the centrum semiovale. We calculated the total volume of distribution (VT) and the distribution volume ratio (DVR) to quantify [11C]PBR28 in each region of interest. Two DVR estimates were computed, one using the cerebellum and the other using the centrum semiovale (DVRcereb, DVRWM ) as pseudo-reference regions (Logan et al. 1996); DVR was calculated with the centrum semiovale as reference region to provide better comparison with the postmortem data (see below). Data between 20 to 70 minutes post-injection were fitted. VT was estimated using an in-house population-based input function as previously described and validated in another group of monkeys (Logan et al. 1990; Aceves-Serrano et al. 2021); data between 20 to 70 minutes post-injection were fitted without blood volume correction and no time shift for the input function. 5.2.2 Magnetic resonance spectroscopy The concentrations of NAA and mI were assessed (please see Figure 2.6 for representative spectra). Spectra were acquired using MRS as described in Chapter 2. MRS acquisition was performed 24 to 48 hours before the first stimulation session and 24 hours after the last session. Single-voxel 1H-MRS PRESS spectra were acquired from the left and right 104 putamen. Voxels were placed manually, avoiding white matter inclusion as much as possible. Metabolite concentrations were adjusted for the water relaxation of the different tissues within the MRS voxel, as described in Chapter 2. Briefly, metabolite concentrations were calculated with LCmodel and corrected for the water relaxation of different tissues within the MRS voxel using the different tissue volume fractions calculated from the T1 image. Metabolite concentrations were adjusted for the water relaxation of the different tissues within the MRS voxel. The tissue volume fractions were determined using FMRIB's FAST to segment the images into gray matter, white matter, and CSF. The MRS voxels were registered in the T1 space to calculate the volume of each tissue within the voxel. NAA and mI concentrations were then corrected using tissue volume fractions for water relaxation using T1 and T2 values for relaxation correction from the literature (Posse et al. 2007; Macmillan et al. 2016). 5.2.3 Post-mortem evaluation The animals received one more session of TBS after completing the PET studies and were euthanized 24 h later using a previously described method (Aceves-Serrano et al. 2022). Euthanasia procedures, and brain extraction and processing were described in Chapter 2. Immunostaining procedures were carried out at the laboratory of Dr. Martin Parent at Laval University. In total, 3 animals were euthanized after sham stimulation, 3 after iTBS, and 4 after cTBS. Brains were cut with a vibratome (VY1200 S’ Leica) into 50 µm-thick transverse sections. Sections were selected from each NHP brain at the anteroposterior coordinate of -7 mm relative to the anterior commissure. These were incubated in a blocking solution made of 0.1% Triton X-100, and 2% normal donkey serum (NDS) diluted in phosphate buffer saline (PBS) 105 (0.1M, pH 7.4). Primary antibody incubation was made overnight at 4°C using anti-TSPO made in goats (1:200, product no. AP31284PU-N, Origene). Secondary antibody incubation lasted 2 h at room temperature using FITC anti-goat made in donkey (1:400, product no. 705-095-147, Jackson). All antibodies were diluted in the blocking solution. Sections were then mounted on gelatin-coated slides and cover slipped using Dako. Stained sections were visualized with a confocal microscope (LSM700, Zeiss). Using the Zen software, z-stacks of 35 µm were acquired with a 10x objective from the regions of the motor cortex, putamen, and centrum semiovale. These image stacks were then processed using maximum intensity projection, and the mean fluorescence intensity was recorded from the software. Mean fluorescence intensity from the motor cortex and putamen was reported as a ratio to the mean fluorescence intensity obtained in the centrum semiovale (%WM). 5.2.4 Statistical analysis Paired t-tests were used to evaluate differences between baseline and post-stimulation estimation of PET and MRS measurements. Correction for multiple comparisons used the Holm-Sidak method. Unpaired t-tests were used to evaluate the difference between the sham and TBS cohorts from the post-mortem data. All statistical analyses were conducted using GraphPad Prism version 9.0.0 for Windows, GraphPad Software, San Diego, California USA, www.graphpad.com. 5.3 Results 5.3.1 [11C]PBR28 quantification 106 In vivo assessment revealed no significant difference between baseline and post-stimulation nor sham assessment in the left and right hemisphere (Fig. 5.1). Specifically, there were no significant differences between baseline and post-stimulation VT after sham (p > 0.6), iTBS (p > 0.9), or cTBS (p > 0.7) in the motor cortex. Similarly, there was no significant difference in measurements in the putamen (p > 0.6, see Table 5.1 and Fig 5.1). Table 5.1 Summary of Total Volume of Distribution Volume of Distribution (VT) before (Baseline) and after (Post) theta burst stimulation (TBS). Values are presented as the average across subjects ± SD and the average percentage difference (Diff) between the two time points. Corrected p values from paired t-test are also shown. Sham iTBS cTBS Avg Baseline Avg Post % Diff (p val) Avg Baseline Avg Post % Diff (p val) Avg Baseline Avg Post % Diff (p val) M1 L 43.8 33.4 -23 (0.7) 39.3 32.5 -17 (0.7) 38.4 45.1 17 (0.6) ± 20 ±10 ± 15 ±9 ± 19 ±12 R 41.7 31.4 -24 (0.6) 39.2 36.4 -7 (0.8) 38.4 43.3 13 (0.6) ± 18 ±9 ± 15 ±16 ± 20 ±11 Putamen L 52.2 42.7 -18 (0.7) 50.9 44.2 -13 (0.8) 47.1 51.8 10 (0.6) ± 25 ±13 ± 22 ±18 ± 23 ±13 R 54.7 41.3 -24 (0.7) 51.3 41.5 -19 (0.7) 47.2 54 14 (0.6) ± 28 ±12 ± 22 ±15 ± 24 ±12 DVRcereb estimates did not significantly change in motor cortex (Figure 5.2) nor in any other region of interest following chronic sham (p > 0.2), iTBS (p > 0.9), or cTBS (p > 0.9) after multiple comparison correction (p > 0.1, see Table 2). DVRWM estimates also did not significantly change in motor cortex nor in any other region of interest after chronic sham (p > 0.9), iTBS (p > 0.9), or cTBS (p > 0.08) after multiple comparison correction (see Table 5.2). 107 Table 5.2 Summary of [11C]PBR28 distribution volume ratios. Distribution volume rations were calculated using cerebellum (DVRcereb) and white matter (DVRWM) as reference regions. Baseline and post-theta burst stimulation (TBS) values are presented as the average across subjects ± SD, and the average percentage difference (Diff) between the two time points. Corrected p values from paired t-test are also shown. Sham iTBS cTBS Avg Baseline Avg Post % Diff (p val) Avg Baseline Avg Post % Diff (p val) Avg Baseline Avg Post % Diff (p val) DVRcereb Motor Cortex L 1.01 0.97 -4 (0.9) 1.0 3 1.05 2 (0.9) 0.96 0.97 1 (0.9) ±0.2 ±0.07 ±0.1 ±0.2 ±0.1 ±0.09 R 0.98 0.94 -4 (0.9) 1.02 1.05 3 (0.9) 0.95 0.95 0 (0.9) ±0.2 ±0.08 ±0.1 ±0.2 ±0.1 ±0.08 Putamen L 1.21 1.27 5 (0.8) 1.35 1.34 -1 (0.9) 1.19 1.22 3 (0.9) ±0.2 ±0.06 ±0.2 ±0.2 ±0.1 ±0.08 R 1.18 1.26 6 (0.2) 1.35 1.32 -2 (0.9) 1.2 1.23 3 (0.9) ±0.1 ±0.1 ±0.2 ±0.2 ±0.09 ±0.08 DVRWM Motor Cortex L 1.47 1.46 -1 (0.9) 1.5 1.49 -1 (0.9) 1.43 1.62 14 (0.1) ±0.1 ±0.2 ±0.1 ±0.2 ±0.1 ±0.1 R 1.44 1.43 -1 (0.9) 1.48 1.5 1 (0.9) 1.41 1.57 12 (0.2) ±0.2 ±0.2 ±0.1 ±0.2 ±0.1 ±0.2 Putamen L 1.89 1.9 0.5 (0.9) 1.97 1.91 -3 (0.9) 1.83 2 9 (0.2) ±0.2 ±0.3 ±0.2 ±0.3 ±0.3 ±0.2 R 1.79 1.9 6 (0.9) 1.98 1.92 -3 (0.9) 1.82 2.04 12 (0.2) ±0.3 ±0.2 ±0.2 ±0.4 ±0.3 ±0.1 108 Figure 5.1 PET and post-mortem measurements of TSPO TSPO evaluation in the motor cortex and the putamen after stimulation. [11C] PBR28 was measured using total volume of distribution (VT) and distribution volume ratio computed using the cerebellum (DVRcereb) and centrum semiovale white matter (DVRWM) as reference regions. Mean fluorescence intensity is reported as a ratio to the mean fluorescence intensity in the centrum semiovale (%WM). 5.3.2 NAA and mI concentrations Paired t-test demonstrated there were no significant changes in NAA and mI in the left putamen after sham (NAA: p = 0.7, mI: p = 0.8), iTBS (NAA: p = 0.6, mI: p = 0.7), and cTBS (NAA: p = 0.7, mI: p = 0.9). Similarly, no significant changes in the right putamen were found after sham (NAA: p = 0.6, mI: p = 0.4), iTBS (NAA: p = 0.8, mI: p = 0.3) and cTBS (NAA: p = 0.5, mI: p = 0.6) (see Figure 5.2). 109 Figure 5.2 Metabolite concentration in Putamen Graphs of myo-inositol (mI) and N-acetylaspartate (NAA) concentrations in the left and right putamen before (baseline) and after (post) theta burst stimulation (TBS) of the left motor cortex (M1). 5.3.3 Post-mortem evaluation Unpaired t-test showed no significant difference in %WM (mean fluorescence intensity ratio to WM) between sham and stimulated animals in the motor cortex (p > 0.5). Evaluation of %WM in the putamen yielded similar results as there were no significant differences between the sham and cTBS cohort nor between the sham and iTBS cohort in any of the regions, as shown by a p > 0.2 across all regions (Fig. 5.1). 5.4 Discussion The current chapter assessed markers for injury and glial activity following chronic TBS in healthy non-human primates. NAA and mI concentrations and TSPO expression were evaluated as markers for neuroinflammatory and injurious processes using PET, MRS, and immunofluorescence imaging. 110 In vivo studies of neuroinflammation, PET-TSPO is a widely used technique. Since its first appearance, multiple TSPO tracers have been developed, increasing its popularity and applicability. TSPO is thought to be involved in multiple cellular functions, such as mitochondrial respiration (Herrera-Rivero et al. 2015). While its specific physiological functions are still unclear, TSPO is the molecule of choice for PET studies of neuroinflammation as it is over-expressed in activated microglia (Chen and Guilarte 2008; Cosenza-Nashat et al. 2009; Hillmer et al. 2017). Evaluations of neuroinflammation have assessed the concentration of mI, an organic osmolyte present in glial cells proposed as a marker for activated astrocytes. MI is elevated in an array of pathologies thought to involve neuroinflammation (Bitsch et al. 1999; Castillo et al. 2000; Rothermundt et al. 2007; Chang et al. 2013) and has been shown to be a selective glial marker in rat brain tissue (Brand et al. 1993). Studies of viral infections and multiple sclerosis have reported a relationship between an increase in mI and PET-TSPO uptake (Grover et al. 2012; Datta et al. 2017). Furthermore, MRS evaluation of NAA, a selective marker for mature neurons, allows for the simultaneous assessment of cellular damage that might be concurrent with neuroinflammation. By combining both techniques, PET-TSPO and MRS, we aimed to evaluate different components of the neuroinflammatory process. Three [11C]PBR28 measurements were calculated, VT, DVRcereb, and DVRWM. The latter was computed to improve comparability to immunofluorescence imaging measurements normalized using centrum semiovale estimates. [11C]PBR28 measurements showed no significant difference between tracer binding before and after cTBS, iTBS, and sham stimulation. This was consistent across the different measurements and different motor brain regions. MRS 111 evaluation of mI concentration showed similar results, and no significant changes were found after stimulation, or sham delivery, in the bilateral putamen. Correspondingly, immunofluorescence analysis showed that TSPO expression in motor cortex and putamen was comparable between the sham and active TBS cohorts. While limited by the small number of subjects in the post-mortem evaluation, these results, in conjunction with the in vivo assessment, suggest there is no activation of glial cells following chronic TBS. Furthermore, the unchanged concentrations of NAA indicate the absence of injurious processes affecting neuronal integrity. The results presented in this chapter were accompanied by changes in cortical excitability, as shown in Chapter 2. These changes were revealed by RMT modulation, a measurement that represents the intensity of stimulation needed to produce a motor response. Specifically, we found that chronic delivery of cTBS increases RMT, indicating a decrease in cortical excitability. These findings, along with results from the current chapter, suggest that even when sustained changes in cortical excitability are observed, there is no glial activation or cellular damage. Our findings align with previous studies in healthy rodents, in which authors reported no changes in microglia and astrocyte reactivity after 3 and 5 sessions of high and low rTMS stimulation (Liebetanz et al. 2003; Zorzo et al. 2019). Conversely, in rat models of spinal cord injury and chronic pain and depression, rTMS decreased microglia activation and inflammatory markers after 8 and 4 weeks of daily rTMS (Kim et al. 2013; Zuo et al. 2022). This discrepancy might suggest that rTMS modulates microglia activity when it is already in an active state, as observed in the injured central nervous system, and might have no effects when delivered in healthy subjects. Differences in results could also be derived from the area stimulated (since 112 rTMS in rodents with 70 mm- and 360 mm-diameter coils is likely not focalized) or the number of stimulation sessions, indicating that more than 3 weeks of daily rTMS might be necessary to modulate glial activity. Alternatively, discrepancies between our results and those from Kim, Zuo, Yang, and colleagues (Kim et al. 2013; Yang et al. 2020; Zuo et al. 2022) could be the result of the different neuroinflammatory markers used. We evaluated TSPO expression, which is upregulated in activated microglia but also expressed in astrocytes endothelial cells and macrophages (Betlazar et al. 2018; Nutma et al. 2021), decreasing the specificity of our measurements. The previously cited rodent studies used immunofluorescent and immunohistochemical approaches to evaluate markers such as glial fibrillary acidic protein (GFAP, a marker of astroglial injury) (Eng and Ghirnikar 1994) and pro-inflammatory cytokines that are released during the inflammatory cascade by reactive glia (Pekny et al. 2007; McKimmie and Graham 2010), likely providing higher sensitivity. While PET-TSPO imaging has been proven to be a useful tool and is widely used in clinical populations, several limitations should be considered when interpreting the current study. As previously mentioned, TSPO measurements are not only indicative of microglia activation. Still, they are likely the summation of a broader spectrum of glia responses from diverse cells like macrophage, astrocytes, microglia, along with the expression of TSPO from vascular endothelial cells(Betlazar et al. 2018; Nutma et al. 2021). Furthermore, PET-TSPO is affected by poor test-retest reliability, even when assessed in healthy controls (Collste et al. 2016; Ottoy et al. 2018; Aceves-Serrano et al. 2021), decreasing its statistical power and sensitivity, ultimately increasing the sample size required to observe any changes. Several other PET tracers exist to label TSPO with similar kinetic characteristics and could be employed in the evaluation of rTMS 113 effects. For example, [11C]PK11195 is a first-generation tracer that prompted the development of other TSPO tracers due to its nonspecific binding (Chauveau et al. 2008). The second and third-generation tracers, [11C] PBR28 included, seem to show improved specific binding (Vivash and O’Brien 2016) but are also accompanied by their own sets of limitations (Tronel et al. 2017). One relevant limitation of [11C] PBR28 is the existence of a genetic polymorphism in humans that affects binding affinity. However, such polymorphism has not been observed in NHP studies and thus is not a limitation of this work. Other PET tracers for different markers of neuroinflammation and immune response components exist and could be used in future work to aid in understanding the interaction of rTMS stimulation, glial cells, and neuroinflammatory processes. For example, [¹¹C]CPPC (Horti et al. 2019) has been used to target colony-stimulating factor 1 receptors CSF1R, which controls the activation and survival of macrophages and is mainly expressed in microglia (Akiyama et al. 1994; Green et al. 2020; Neal et al. 2020). PET tracers have also targeted the purinergic ion channel receptor (P2X7R), whose activation has been associated with the release of pro-inflammatory cytokines and reactive oxygen species by peripheral macrophages, as well as microglia or astrocytes (Chakfe et al. 2002; Duan et al. 2003). While P2X7R and (CSF1R) seem to be promising for the evaluation of neuroinflammatory processes in vivo, these and other PET targets (e.g. matrix metalloproteinases and CB2R) are still in the processes of being validated (Majo et al. 2005; de Vries et al. 2008; Wagner et al. 2011; Contartese et al. 2012; Zinnhardt et al. 2015). The current study was designed to mimic clinical TBS delivery, but given the characteristics of our animal subjects, several differences between human and non-human primates should be considered when translating these results. One such difference is the presence 114 of facial muscles inserted at the top of the rhesus monkey’s head that, along with their thicker skulls, create a bigger gap between the coil and the stimulated cortex. In addition, a smaller head-to-coil ratio, due to the animal's head size and the size of the coil we used (a 70mm figure-eight human coil), affects the focality of stimulation, making the overall delivered stimulation less deep and focal than in human studies. Given that coil distance and positioning have been reported as a source of variability of rTMS effects in neuronal activity (Lang et al. 2006; D’Ostilio et al. 2016), it is unclear whether the same would be true for its effects on glial cells. 5.5 Conclusion In summary, in this chapter, we showed that chronic delivery of cTBS and iTBS in the healthy brain does not appear to increase the expression of markers for glial activation, suggesting a lack of measurable neuroinflammatory response. Furthermore, chronic rTMS did not induce injurious effects, as suggested by the unchanged marker values of cellular integrity in the putamen. Further studies should evaluate if cellular integrity is also maintained in the stimulated area. Our findings provide novel insight into the safety of TBS and might indicate the absence of deleterious effects, even after multiple daily stimulation sessions at a high frequency. Further studies should continue evaluating molecular and cellular markers of rTMS safety to assure ethical application in patient populations. 115 Chapter 6: Conclusion and Future Work In an effort to advance the current knowledge of the effects of TBS – a form of rTMS – we use a multimodal imaging approach to investigate the metabolic and functional effects of stimulation of the motor cortex. Healthy non-human primates were chosen as subjects given their comparable neuroanatomy to humans and their brain size. Using PET, MRI, and immunohistochemistry tools, we evaluated the effects of a clinical course of rTMS in neurotransmission (Chapter 2), functional and metabolic connectivity (Chapters 3 & 4), and glial cell activity (Chapter 5). This study was carried out in NHP randomly assigned to receive cTBS, iTBS, or sham stimulation. Neuroimaging sessions were carried out before, in between (dopamine evaluation), and one day after a clinical course of stimulation. Some animals underwent more than one, but no more than three, stimulation-neuroimaging trials and were euthanized immediately after the last trial to carry out post-mortem evaluations. Below, our findings are summarized, along with possible future directions. Figure 6.1 Summary of results Visual summary of results from Chapter 2 (A), Chapter 3 (B), Chapter 4 (C) and Chapter 5 (D). 116 6.1 Findings summary Chapter 2. Using [11C]raclopride, MRS, and immunofluorescence staining, we investigated the acute (immediate) and chronic effects of TBS on striatal dopaminergic neurotransmission and evaluated chronic changes of glutamate concentrations in the putamen. We also evaluated chronic changes in cortical excitability with RMT. Acute evaluation with [11C]raclopride revealed a decrease in dopamine release in the bilateral putamen following unilateral cTBS stimulation, while no changes in tracer binding were found after iTBS or sham delivery. The chronic assessment showed no changes in [11C]raclopride, glutamate concentrations, or D2R immunoreactivity after cTBS, iTBS, or sham delivery. Chronically we also found a decrease in cortical excitability following chronic cTBS, with no changes found following iTBS or sham stimulation. Our data were obtained from healthy subjects, and as such, it is possible that response to stimulation in patients may be different. However, as discussed in the relevant chapter, there is a remarkable similarity between our dopamine neurotransmission data and the sparse reports in patient with Parkinson’s disease and depression (Strafella et al. 2005; Pogarell et al. 2006). Indeed, taken together with the published rTMS literature, our findings overall suggest that, in a healthy brain, cTBS delivery consistently produces a decrease in dopamine release – likely through corticostriatal projections. These changes seem to be transient as they are not found one day after stimulation, even after chronic stimulation over several weeks. Since no evaluation was carried out immediately after the last stimulation session, we can not know if dopamine modulation happened immediately after the last stimulation session. However, other literature suggests dopamine might still have been modulated after the last session (Pogarell et al. 2006). If 117 so, dopamine modulation dissipated before the 24h hour evaluation, possibly by the second-hour post-stimulation (Lamusuo et al. 2017). Yet, changes in cortical excitability persist much longer, at least 24 hrs after stimulation, suggesting a cumulative neuroplastic effect in the cortex. The lack of sustained changes in dopamine release in the presence of reduced cortical excitability could indicate a homeostatic mechanism that modified synaptic strength or synaptic scaling and decreased the responsiveness to cortical excitability modulation (Turrigiano and Nelson 2004b). Intermittent TBS produced variable effects, in line with studies in human participants (Hamada et al. 2013), leading to an overall non-significant effect in our small sample in acute and chronic assessments. However, critical consideration of our data and the broader literature suggest that iTBS effects may be subject-dependent (Hamada et al. 2013; Goldsworthy et al. 2021) and may induce a therapeutically relevant response in selected cohorts: our figures (2. 7 and 2.8) show that iTBS response in our cohort was almost evenly split in half. Future studies in a much larger cohort may try to determine predictive markers of effects (i.e., baseline levels of dopamine release, cortical excitability, or functional connectivity). Chapter 3. The modulatory effects of rTMS delivery go beyond the modulation of activity in a single brain region. Studies have suggested that rTMS can modulate the intrinsic interaction between anatomically and functionally connected areas (Beynel et al. 2020). Using rsfMRI, we assessed the effects of chronic TBS delivery on regions within the CSTC motor loop at rest, namely the connectivity between motor cortex, putamen, and motor thalamus, before and one day after multiple days of unilateral stimulations of the cortical motor areas. Our seed-based analysis revealed a significant increase in connectivity between the left and right motor cortices after both cTBS and iTBS unilateral delivery. Even in our small cohort of anesthetized subjects, 118 we also showed modulation of connectivity between the stimulated cortex and ipsilateral putamen and between the ipsilateral putamen and motor thalamus after cTBS delivery, reinforcing the premise that cTBS may elicit a more consistent effect. These results overall showed TBS capacity to modulate connectivity between regions anatomically connected to the stimulated area. In terms of CSTC loops, these results would indicate that cTBS might be able to induce modulation of connectivity between the stimulated cortical area and its anatomically associated striatal region (e.g., DLPFC connectivity to caudate) and connectivity between the associated thalamic nucleus to the striatum (e.g., ventral anterior nucleus, mediodorsal and ventrolateral nucleus of the thalamus to caudate), as well as interhemispheric connectivity to its contralateral homologous (e.g., DLPFC connectivity to contralateral DLPFC). Interestingly, we found that baseline connectivity between the left and right putamen was correlated to changes in dopamine modulation. Higher connectivity was associated with a greater decrease in dopamine release after cTBS delivery. These results suggest that baseline corticostriatal connectivity influences the effect of cTBS on dopaminergic modulation in the putamen. One can hypothesize that baseline connectivity may play a role in the response of individual subjects to iTBS stimulation, and this would be an interesting question to investigate in a bigger subject sample. Our data indicated that cortical excitability was not related to interhemispheric connectivity, as evaluated by changes in RMT. There was increased connectivity between the bilateral motor cortical areas after iTBS and cTBS despite the lack of sustained changes in cortical excitability after weeks of iTBS stimulation. This suggests that changes in RMT are not an adequate predictive proxy for measuring effectiveness. 119 Chapter 4. Current analytical tools allow the assessment of metabolic activity at a connectivity level, which provides information about metabolic networks and how these might be altered by disease and in response to perturbations or interventions. While studies have shown rTMS ability to modulate glucose metabolism as a marker for synaptic activity, there is a lack of studies evaluating its impact on metabolic networks. Evaluation of functional metabolic connectivity is clinically relevant as metabolic profiles specific to different disorders have been found (Ma et al. 2007; Li et al. 2022). Based on our group experience estimating metabolic profiles in parkinsonian animals, we conducted an exploratory study in our small dataset to determine if it may be possible to characterize specific metabolic patterns associated with TBS stimulation. We used baseline and post-stimulation PET-FDG scans acquired in awake NHPs along with SSM-PCA to investigate changes in metabolic networks following stimulation. Somewhat surprisingly, we were able to determine a metabolic pattern specific to iTBS stimulation with an increase and decrease in metabolism in regions that are part of previously reported functional resting state networks (Seeley et al. 2007; Hutchison et al. 2011; Hutchison and Everling 2012; Seitzman et al. 2019), but no significant pattern was associated with cTBS (or sham). Due to our very small cohort, further analyses for validating the iTBS-pattern were not feasible as they would not have been meaningful in our small sample. These results show the feasibility of assessing specific metabolic patterns related to various stimulation paradigms. Clinically, determining a stimulation-associated pattern could facilitate the selection of stimulation paradigms that would best fit a given patient population given their disease-specific pattern (e.g., Parkinson’s disease-related pattern). 120 Chapter 5. Glial cells are a significant cellular population in the brain, involved in neurotransmission and neuroplasticity (Delpech et al. 2015; Shemer et al. 2015), yet there are limited studies evaluating their response to rTMS stimulation. Glial cell activation is a valuable marker of neuroinflammation presence that, as such, could be used to evaluate the safety of long-term rTMS delivery. Neuroinflammation is a hallmark of unhealthy brain function and is present in most neurodegenerative diseases and trauma conditions (i.e., stroke). While inflammatory processes can play a significant role in response to infection and healing, sustained inflammation can lead to abnormal handling of healthy responses, including cell death (Jayaraj et al. 2019). While rTMS and other non-invasive stimulation are generally considered safe (Rossi et al. 2009, 2021; Oberman et al. 2011), there is a paucity of confirmatory data, especially regarding prolonged exposure to stimulation (i.e., clinical courses of the situation). We took advantage of healthy NHPs to evaluate changes in glial activation following chronic TBS stimulation. We assessed PET-TSPO expression and myoinositol concentrations to evaluate glial activation and measured NAA concentration to investigate cellular integrity. Neither our in vivo measurements nor post-mortem validation revealed evidence of glial reactivity, confirming the belief that non-invasive stimulation is a safe procedure. There are limitations to our work as TSPO is not expressed exclusively on glial cells (Betlazar et al. 2018), and MRS in anesthetized animals in small structures could introduce variability that ultimately might have masked subtle changes in metabolite concentrations. We cannot exclude that using other markers of immune function might have led to different conclusions. However, in our current state of knowledge, our data suggest that long-term delivery of rTMS, in the form of TBS, a high-frequency patterned form, does not induce long-term expression of neuroinflammation and should be safe to apply to most patients. 121 6.2 Future directions The current dissertation highlights the relevance of neuroimaging techniques in studying rTMS effects. Using multiple techniques in a single subject allowed the comparison of results across modalities, prompting future research to take a similar approach. Regarding the evaluation of neurotransmission: Studies evaluating dopaminergic transmission, and other neurotransmitters, typically evaluate the immediate effects of rTMS delivery. As discussed in Chapter 2, the effects of rTMS on neurotransmission can be transient. As shown in work by Lamusuo et al., it can have different temporal profiles for different neurotransmitters (Lamusuo et al. 2017). Thus, we suggest further research evaluates the chronic effects of rTMS in neurotransmission to investigate the long-lasting consequences of stimulation and how these might be beneficial for different patient populations. Regarding rTMS effects on connectivity: This work also illustrates the complexity of rTMS effects and how it modulated brain neurophysiology at a network level. We carried two connectivity assessments regarding functional and metabolic information. These studies were carried out separately and independently, but similar analysis methods could be used to evaluate both datasets, albeit a much larger sample would be preferable. PET-FDG and fMRI data can be analyzed using ICA, for example. While the interpretation of results from both types of data might differ, this could facilitate the comparability and translation of results. Furthermore, functional and metabolic connectivity assessments could complement structural connectivity information acquired from MRI tractography studies, adding information regarding white matter connections. 122 Finally, connectivity can be investigated using other molecular PET tracers, opening the door to connectivity assessments of neurotransmission at the network level. Currently, network analyses have been applied to tracers such as [18F]FDOPA and [11C]SB217045 (Veronese et al. 2019), tracers that enable the assessment of dopamine synthesis and density serotonin receptors. Evaluation of these systems at a network level could lead to a deeper understanding of the topographical effects of rTMS. Regarding the effects of rTMS on glial cells and neuroinflammation: Other methods for neuroinflammation assessment exist. While PET-TSPO is the primary technique to evaluate glial activity in vivo, other PET tracers can evaluate different neuroinflammatory processes. Furthermore, PET/MR tools could facilitate the acquisition of PET scans and MRS during the same session. The acquisition of more than one neuroinflammation marker would make measurements more robust. Further studies should continue evaluating molecular and cellular markers of rTMS safety to ensure ethical application in vulnerable populations. 6.3 Conclusion In conclusion, this dissertation contributes to current research evaluating the effects of rTMS, specifically the effects of TBS. 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Thesis/Dissertation
eng
Neuroscience
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Doudet, Doris
Neuromodulatory effects of theta burst stimulation, a molecular and functional assessment
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