Altered Hippocampal Structure in Trigeminal Neuralgia

Altered Hippocampal Structure In Trigeminal Neuralgia

Alborz Noorani

A thesis submitted in conformity with the requirements for the degree of Master of Science Institute of Medical Science University of Toronto

Altered Hippocampal Structure In Trigeminal Neuralgia

Alborz Noorani

Master of Science

Institute of Medical Science University of Toronto

2020

Abstract

The hippocampus has long been studied for its crucial role in learning and memory. Recent findings suggest that the hippocampus also plays a role in shaping pain experience. This thesis aims to investigate hippocampal alterations in chronic neuropathic pain, using trigeminal neuralgia (TN) as a model. TN is a facial neuropathic pain syndrome that is highly debilitating but is amenable to surgical intervention. In this thesis, structural magnetic resonance images

(MRI) were used to measure grey matter volume in the hippocampus. Study 1 which includes

21 TN patients, demonstrated that the hippocampus is smaller in TN subjects and hippocampal subfields are selectively affected. Study 2 which includes 61 TN patients with MRI before and after surgery, shown that the hippocampal subfield abnormalities normalized after pain resolution following surgical interventions. This body of work highlights that the hippocampus can be dynamically altered in chronic pain conditions.

Acknowledgements

My journey towards my master’s thesis was impossible without the support and encouragement I have received from my supervisor, Dr. Mojgan (Moji) Hodaie. Moji’s kindness and clinical expertise have been the light that guided me ever since I joined the Hodaie Lab. She has always been there whether it was reviewing my slides at 5:45 am or asking how I feel at 11:30 pm when life gave me hard times. Having the opportunity to join her on her trip to Cambodia as well as observing her efforts at Baha’i Institute for Higher Education (BIHE) are priceless experiences that I will forever carry with me. It has truly been my fortunate to have her as my mentor and supervisor and I will forever be thankful for everything she has done for me.

I would also like to thank my parents and brother. They have been with me every step of the way, even though we are physically apart. The courage and perseverance that my brother, Sama, has showed to pursue education have been my inspiration in this challenging journey.

I would like to thank my aunt and uncle, Mitra Niroumand and Soheil Homayouni, who helped me to settle in Canada and supported me like their own child over the past six years in every situation.

I would like to thank my graduate committee members Drs. Barry Sessle, Karen Davis and Massieh Moayedi, for their invaluable feedback and support at all stages of my degree. I appreciate your insight and expertise.

I would also like to thank the current and past members of the Hodaie Lab with whom I have shared many joyful and unforgettable moments: Peter Hung, Jia Zhang, Dr. Adnan

iii

Waheed, Dr. Matthew Walker, Kaylee Sohng, Dr. Cathy Li, Sarasa Tohyama, Dr. Timur Latypov, Shaun Hanycz, Dr. Aisha Halawani, Powell Chu, and Erika Wharton-Shukster.

Peter Hung, Jia Zhang, and Lizbeth Ayoub: thank you for always being there to hear my stories, help me make the right decisions, and most importantly, for your true friendship.

I am thankful to receive support from the Canadian Institutes of Health Research (CIHR) Frederick Banting and Charles Best Canada Graduate Scholarships-Master’s, Ontario Graduate Scholarship, University of Toronto Centre for the Study of Pain Scientist Award, James F. Crother’s Family Fellowship in peripheral nerve damage, Unilever/Lipton graduate fellowships, and Institute of Medical Science Entrance Award.

Statement of Contribution

Alborz Noorani (author) – all aspects of the work including data collection, experimental design, data analysis, methodological development, data interpretation, and thesis preparation.

Dr. Mojgan Hodaie (supervisor) – mentorship, assistance with experimental design, assistance with data interpretation, preparing manuscripts and thesis.

Dr. Barry Sessle (committee member) – mentorship and assistance with thesis preparation.

Dr. Karen Davis (committee member) – mentorship and assistance with thesis preparation.

Dr. Massieh Moayedi (committee member) – mentorship, assistance with data interpretation in the Study II, and assistance with thesis preparation.

Peter Shih-Ping Hung – assistance with experimental design, and assistance with data interpretation.

Dr. Michael Vaculik (co-first author in Study I) – assistance with experimental design, data interpretation, and drafting the study I manuscript.

Jia Yan Zhang – assistance with data collection.

Table of Contents

ACKNOWLEDGEMENTS III

STATEMENT OF CONTRIBUTION V

TABLE OF CONTENTS VI

LIST OF ABBREVIATIONS X

LIST OF FIGURES XIII

LIST OF TABLES XV

CHAPTER 1 LITERATURE REVIEW 1

1.1 Pain 1 1.1.1 Nociception 1 1.1.2 Chronic pain 4 1.1.2.1 Chronic neuropathic pain 6 1.1.3 Trigeminal neuralgia 8 1.1.3.1 Trigeminal system anatomy 8 1.1.3.2 Trigeminal neuralgia pain 14 1.1.3.3 Treatment strategies for TN 16

1.2 The hippocampus and pain 18 1.2.1 Hippocampal formation anatomy 19 1.2.2 Hippocampal function and connection 22 1.2.2.1 Intrinsic hippocampal circuitry 22 1.2.2.2 Extrinsic hippocampal circuitry 25 1.2.3 The role of hippocampus in chronic pain conditions 26 1.2.3.1 Nociception and the hippocampus 28

1.2.3.2 Stress and anxiety, as moderators of chronic pain, induce changes in the hippocampal complex 30 1.2.4 Sex differences in the hippocampus 34

1.3 Structural brain imaging 37 1.3.1 Structural MRI 37 1.3.1.1 T1-Weighted imaging 37 1.3.1.2 Grey matter analysis 38 1.3.2 Hippocampal involvement in pain processing – evidence from neuroimaging 40

CHAPTER 2 AIMS & HYPOTHESES 42

2.1 Study I: Selective hippocampal subfield volume reductions in classic trigeminal neuralgia 42 2.1.1 Main Aim 42 2.1.2 Specific Aims 43 2.1.3 Hypotheses 43

2.2 Study II: TN pain relief reverses hippocampal abnormalities 44 2.2.1 Main Aim 44 2.2.2 Specific Aims 45 2.2.3 Hypotheses 45

CHAPTER 3 STUDY I: SELECTIVE HIPPOCAMPAL SUBFIELD VOLUME REDUCTIONS IN CLASSIC TRIGEMINAL NEURALGIA 46

3.1 Abstract 46

3.2 Introduction 47

3.3 Methods 49 3.3.1 Ethics 49 3.3.2 Participants 50 3.3.3 Imaging 50 3.3.4 Automated volumetric hippocampal segmentation 52 3.3.5 Intracranial Volume Correction 53 3.3.6 Manual volumetric hippocampal segmentation 53 3.3.7 Statistical analysis 54

3.4 Results 54 3.4.1 Subject Demographics 54

vii

3.4.2 Automated hippocampal subfield segmentation in R-TN subjects and matched controls 55 3.4.3 Sex dependent differences in hippocampal subfield volumes 59 3.4.4 Correlation of hippocampal subfields changes and pain duration 59 3.4.5 Manual hippocampal segmentation in R-TN subjects and controls 63

3.5 Discussion 64 3.5.1 Hippocampal subfield volume reductions in R-TN subjects correlate with CNS circuits involved in pain processing 65 3.5.2 Bilateral hippocampal subfield reductions in R-TN female subjects 66 3.5.3 Aberrant neurogenesis as the substrate for volume loss in hippocampal subfields 67 3.5.4 Study limitations 68

3.6 Conclusions 69

CHAPTER 4 STUDY II: PAIN RELIEF NORMALIZES HIPPOCAMPAL ABNORMALITIES IN TRIGEMINAL NEURALGIA 70

4.1 Abstract 70

4.2 Introduction 71

4.3 Methods 73 4.3.1 Participants 73 4.3.1.1 TN Patients 73 4.3.1.2 Healthy participants - Cam-CAN 74 4.3.1.3 Healthy controls validation 74 4.3.2 Automated subcortical segmentation 75 4.3.3 Surgical intervention and treatment responses 75 4.3.4 Subcortical volume correction 76 4.3.5 Volumetric percent change after surgery 77 4.3.6 Statistical Analysis 77

4.4 Results 78 4.4.1 Subject demographics 78 4.4.2 Pain relief increases hippocampal volume 80 4.4.3 Pain relief normalizes the hippocampal abnormalities 81 4.4.4 Hippocampal subfields increase significantly after pain relief 83 4.4.5 Sex dependent changes in the hippocampus 85

4.5 Discussion 86

viii

4.5.1 Anatomical segmentation reveals bilateral increase in subregions involved in pain modulation 86 4.5.2 Axial segmentation 88 4.5.3 Hippocampal increase in size may be a consequence of neurogenesis 89 4.5.4 Sex differences in response to pain relief 89 4.5.5 Study Limitations 90

CHAPTER 5 GENERAL DISCUSSION 92

5.1 Summary of findings 92

5.2 Trigeminal neuralgia as a model of evoked pain 93

5.3 Hippocampal alterations in TN 94

5.4 Hippocampal alterations may be related to altered hippocampal cellular mechanisms including neurogenesis and/or microglia regulation 96

5.5 Limitations 98

CHAPTER 6 CONCLUSION 100

CHAPTER 7 FUTURE DIRECTIONS 101

REFERENCES 103

List of Abbreviations

ACC Anterior Cingulate Cortex

ACV Anticonvulsant

AHN Adult Hippocampal Neurogenesis

ANOVA Analysis Of Variance

BEST Bayesian Estimation Supersedes the t-test

BNI Barrow Neurological Institute

BNZ Benzodiazepine

CA Cornu Ammoris

Cam-CAN Cambridge Centre For Ageing And Neuroscience

CBZ Carbamazepine

CIHR Canadian Institutes Of Health Research

CNS Central Nervous System

DG Dentate Gyrus

EC Entorhinal Cortex eTIV Estimated Total Intracranial Volume fMRI Functional Magnetic Resonance Imaging

GBP Gabapentin

GC DG Granule Cell Layer Of Dentate Gyrus

GC-ML-DG Granule Cell And Molecular Layer Of The Dentate Gyrus

GKRS Gamma Knife Radiosurgery

GM Grey Matter

HATA Hippocampus–Amygdala-Transition-Area

HDI Highest Density Interval

HPA Hypothalamic-Pituitary-Adrenal

IASP International Association For The Study Of Pain

ICV Intracranial Volume

IHS International Headache Society

LTP Long-Term Potentiation

MCC Midcingulate Cortex

ML HP Molecular Layer Of Hippocampal Proper

MNI Montreal Neurological Institute

MR Magnetic Resonance

MS Multiple Sclerosis

MRI Magnetic Resonance Imaging

MVD Microvascular Decompression

NRS Numeric Rating Scale

NVC Neurovascular Compression

PAG Periaqueductal Grey

PaS Para-Subiculum

PFC Prefrontal Cortex

PGB Pregabalin

PrS Pre-Subiculum

REZ Root Entry Zone

RF Radiofrequency

R-TN Right Sided Trigeminal Neuralgia

S Subiculum

S1 Primary Somatosensory Cortex

S2 Secondary Somatosensory Cortex

SD Standard Deviation sMRI Structural Magnetic Resonance Imaging

SNI Spared Nerve Injury

T1w T1-Weighted

TCA Tricyclic Antidepressant

TN Trigeminal Neuralgia

TNF Tumor Necrosis Factor

UHN University Health Network

VBM Voxel Based Morphometry

VBNC Trigeminal Brainstem Nuclear Complex

Vc Subnucelus caudalis

Vi Subnucleus interpolaris

Vo Subnucleus oralis

VOI Volume Of Interest

WM White Matter

VPL Ventral PosteroLateral

VPM Ventral PosteroMedial

xii

List of Figures

Figure 1-1 Ascending nociceptive pathways...... 3 Figure 1-2 Brain structures involved in pain perception...... 3 Figure 1-3 Peripheral and central sensitization...... 5 Figure 1-4 Nociceptive spinal pathways in peripheral neuropathy...... 6 Figure 1-5 Neuropathic pain...... 7 Figure 1-6 Trigeminal brainstem sensory nuclear complex ...... 11 Figure 1-7 Trigeminal nerve anatomy...... 12 Figure 1-8 Trigeminal somatosensory pathways to the CNS...... 14 Figure 1-9 Neurosurgical treatment options for TN...... 17 Figure 1-10 3D model of the hippocampus in an average template of 70 healthy individual T1 scans...... 19 Figure 1-11 Subiculum complex acts as a gateway to the hippocampus...... 21 Figure 1-12 Hippocampal circuitry depicting intrinsic and extrinsic hippocampal connections to different brain regions...... 23 Figure 1-13 Intrinsic hippocampal circuitry...... 24 Figure 1-14 Hippocampal gross anatomy and connections to other brain regions (extrinsic circuitry)...... 26 Figure 1-15 Ascending and descending nociceptive transmission and modulation pathways in the CNS in relation to the hippocampus...... 29 Figure 1-16 Dentate Gyrus neurogenesis affects mood, cognition and memory consolidation. Neurogenesis is negatively affected via the hypothalamic-pituitary-adrenal axis...... 32 Figure 3-1 Representative images of FreeSurfer 6.0 automated hippocampal subfield segmentation in a control subject...... 52 Figure 3-2 Automated hippocampal segmentation showing reduced ipsilateral whole hippocampal volume in R-TN patients compared to matched controls...... 56 Figure 3-3 Summary of automated hippocampal segmentation in 22 R-TN and matched control subjects...... 58 Figure 3-4 Hippocampal subfield volumetric changes in R-TN patients...... 61

xiii

Figure 3-5 Correlation between hippocampal subfield volume reduction and pain duration...... 62 Figure 3-6 Manual hippocampal segmentation in 5 R-TNs and matched controls...... 63 Figure 4-1 Hippocampal volumetric changes after treatment...... 81 Figure 4-2 Automated hippocampal segmentation for 47 TN responders and their age- and sex-matched healthy controls...... 82 Figure 4-3 Automated hippocampal subfields segmentation using FreeSurfer 6.0 and its developmental package...... 84 Figure 4-4 Automated hippocampal segmentation stratified by sex in the responder cohort...... 85

xiv

List of Tables

Table 3-1 Demographic summary of the 21 right-sided TN patients included in this study...... 51 Table 3-2 Summary of automated hippocampal segmentation in R-TN and control subjects...... 57 Table 3-3 Summary of automated hippocampal segmentation in left and right hemispheres in R-TN and control subjects...... 60 Table 3-4 Summary of manual hippocampal segmentation in R-TN and their matched controls...... 64 Table 4-1 Demographic summary of the TN patients included in this study...... 78 Table 4-2 Summary of hippocampal subfield changes after surgical intervention in the responder cohort...... 83

Chapter 1 Literature Review

1.1 Pain

Pain is defined as “an unpleasant sensory and emotional experience associated with actual or potential tissue damage, or described in terms of such damage” (Merskey and Bogduk 1994). Pain can serve as a warning of potential or actual damage to the body and is one of the major functions of the nervous system (Reddi, Curran, and Stephens 2013). Pain can be described as a complex sensory and cognitive-emotional experience, and is a major symptom in many clinical conditions (Melzake and Casey 1968). However, pain is more than mere nociception and is considered to be a social, emotional, and cognitive experience (Garland 2012).

1.1.1 Nociception

Nociception refers to processing of a noxious stimuli by the central nervous system (CNS) and peripheral nervous system (PNS) (Dubin and Patapoutian 2010). Noxious stimuli, define as a stimulus that is damaging or threatens damage to normal tissues (Merskey and Bogduk 1994), activate nociceptors and their pathways (Kendroud and Bhimji 2018).

Nociception transmission depends on the neural circuits in the somatosensory system. Nociceptive stimuli activate unmyelinated C or thinly myelinated Aδ primary sensory neurons. In turn, these neurons transfer the info to the CNS (Woolf and Ma 2007). Briefly, in the ascending spinal nociceptive pathway the primary afferent neurons are activated by the noxious stimuli and sends signals to the dorsal horn of the spinal cord. Subsequently, neurons relay information to the thalamus, including the ventral posterolateral (VPL) nucleus, via the Chapter 1. Literature Review 2

spinothalamic tract and in turn, the thalamus transmits the information to cortical regions including primary (S1) and secondary (S2) somatosensory cortices, the posterior insular cortex, the anterior cingulate cortex (ACC), and midcingulate cortex (MCC) (Bushnell, Čeko, and Low 2013; F. Wang et al. 2016; Woller et al. 2017; Das 2015; Vogt 2005). Subsequently, these cortical regions send the information and engage other brain regions, including the limbic system and the prefrontal cortex (PFC) (Bushnell, Čeko, and Low 2013). Figure 1-1 depicts ascending nociceptive pathways and figure 1-2 illustrates brain structures involved in pain perception.

Chapter 1. Literature Review 3

Figure 1-1 Ascending nociceptive pathways.

(a, b) Depicts spinothalamic nociceptive pathway to thalamus and somatosensory cortex for localizing the stimuli and detect the intensity. Pathways involved in the affective aspect of the nociceptive stimuli. (c) Spinomesencephalic tract projection to the amygdala. The image is adapted from (Malinowski 2019) with Copyright License ID: 4847660864602.

The descending anti-nociceptive pathways engage several CNS structures. The activation of the descending pathways involve cortical regions, such as dorsolateral prefrontal cortex, the ACC, the MCC, and the limbic system, including structures like amygdala (Millan 2002; Fields, Heinricher, and Mason 1991; Vogt 2005). These structures communicate with different brainstem nuclei such as the periaqueductal grey (PAG) which integrates information from amygdala, hypothalamus, and brain cortices (Yam et al. 2018; Dubin and Patapoutian 2010).

Figure 1-2 Brain structures involved in pain perception.

Chapter 1. Literature Review 4

This image depicts cortical and subcortical regions involved in pain perception and their inter- connectivity and ascending nociceptive pathways. Abbreviations: ACC: anterior cingulate, PCC: posterior cingulate, PF: prefrontal cortex, M1: primary motor cortices, SMA: supplementary motor cortices, PPC: posterior parietal cortex, BG: basal ganglia, HT: hypothalamus, AMYG: amygdala, PB: parabrachial nuclei, and PAG: periaqueductal gray (PAG). This image was adapted from (Apkarian et al. 2005) with Copyright License ID: 4847680827893.

Although the nociceptive pathways share many similarities, however, the trigeminal sensory and nociceptive pathways are different from the general nociceptive pathway discussed in this section. The trigeminal sensory and nociceptive pathways are discussed in detail in sections to follow.

1.1.2 Chronic pain

Chronic pain is considered a condition in which acute pain progresses to a chronic state that persists beyond the normal healing period (Yang and Chang 2019), typically more than 3 to 6 months (Treede et al. 2015). It has been estimated that approximately 20% of Canadians live with chronic pain and the direct and indirect annual costs of chronic pain in Canada is estimated to be ~50 to 60 billion dollars (Canadian Pain Task Force 2019; Wilson, Lavis, and Ellen 2015). Chronic pain conditions negatively interfere with normal body function and the pain no longer serves its normal purpose of protecting the body from further harm.

Multiple mechanisms have been proposed to explain the acute to chronic pain transition including peripheral and central sensitization, gliopathy, genetic priming, and alterations in the corticolimbic circuitry (Glare, Aubrey, and Myles 2019; Chapman and Vierck 2017; Voscopoulos and Lema 2010). Specifically, in central and peripheral sensitization, cellular changes results in nociceptive pathway sensitization and impaired nociceptive processing mechanisms in the CNS.

Chapter 1. Literature Review 5

The term sensitization refers to increased responsiveness of nociceptive neurons to either their normal input (abnormally increased response to noxious stimuli), and/or responding to normally subthreshold input (responding to non-noxious stimuli), and/or the development of ongoing activity without any overt stimuli (ectopic activity) (Latremoliere and Woolf 2009; Hucho and Levine 2007; Graven-Nielsen and Arendt-Nielsen 2002; Bolay and Moskowitz 2002). Sensitization can occur in both the CNS, called central sensitization, and the PNS, referred to as peripheral sensitization (Costigan, Scholz, and Woolf 2009) (see Figure 1-3). The sensitization of the nervous system could lead to the development and maintenance long- term pain states such as chronic neuropathic pain conditions (Maggi, Lowe, and Mackinnon 2003). In a clinical setting, the term sensitization (which is a neurophysiological phenomenon) is most often used in explaining to the behavioral phenomena of allodynia and hyperalgesia. Hyperalgesia is defined as increased pain from a stimulus that normally provokes pain, and allodynia is defined as Pain due to a stimulus that does not normally provoke pain.

Figure 1-3 Peripheral and central sensitization.

With increased synaptic efficacy and reduced inhibition, the stimuli are amplified, and hyperalgesia and/or allodynia occur. The image is adapted from (Costigan, Scholz, and Woolf 2009) and was reproduced with permission from with Copyright Order ID: 1028307.

Chapter 1. Literature Review 6

1.1.2.1 Chronic neuropathic pain

Neuropathic pain can arise from a lesion or injury to the nervous system, either peripherally or centrally (J. N. Campbell and Meyer 2006; Treede et al. 2019). Compared to nociceptive pain which results from neuronal activity due to actual tissue damage or painful stimuli, neuropathic pain is linked to a damaged nervous system (Nicholson 2006). The nociception related to peripheral neuropathy follows a similar pathway as general nociceptive pathways as illustrated in Figure 1-4.

Figure 1-4 Nociceptive spinal pathways in peripheral neuropathy.

Ascending nociceptive and descending anti-nociceptive spinal pathways involve multiple PNS and CNS structures. Briefly, Nociceptive stimuli activate primary sensory neurons which in turn projected via spinothalamic to the VPL nucleus of the thalamus. Thalamus relays the information to the somatosensory cortex, including S1 and S2 regions. Spinal cord also projects the nociceptive stimuli

Chapter 1. Literature Review 7

via the spinoreticular projections and the dorsal column pathway to the cuneate nucleus and nucleus gracilis. Additionally, nociceptive stimuli are relayed in the parabrachial nucleus and are forwarded to the hypothalamus and amygdala, where the emotional aspects of the stimuli are processed. In the descending anti-nociceptive pathway, the amygdala and hypothalamus drive the periaqueductal grey nucleus and the locus coeruleus. Lastly, these brainstem areas project to the spinal cord. This figure is adapted (Colloca et al. 2017) with Copyright License ID: 4743740666865.

Neuropathic pain is caused by damage or lesion in the somatosensory nervous system and can be of central or peripheral origin, depending on the location of the disease (Gierthmühlen and Baron 2016). Features of neuropathic pain include burning pain, spontaneous or evoked painful episodes, and abnormal temporal summation with a progressive buildup in pain in response to repeated stimuli, and reduced pain thresholds (Gierthmühlen and Baron 2016; Costigan, Scholz, and Woolf 2009) (see figure 1-5).

Figure 1-5 Neuropathic pain.

Neuropathic pain could occur as a result of ectopic action potential generation and/or evoked by a noxious or non-noxious stimulus within the nociceptive pathway. Neuropathic pain is maladaptive and commonly persistent. The image is adapted from (Costigan, Scholz, and Woolf 2009) and was reproduced with permission from with Copyright License ID: 1028307.

Chapter 1. Literature Review 8

Central neuropathic pain can occur in people who have conditions that affect the brain, including cerebrovascular diseases (e.g., post-stroke pain), and neurodegenerative diseases (e.g., Parkinson’s disease), or the spinal cord, including spinal cord injury, demyelinating diseases (e.g., multiple sclerosis (MS), transverse myelitis) (Borsook 2012). In contrast, peripheral neuropathic pain can occur from damage or diseases in the unmyelinated C fibers and/or myelinated Aβ and Aδ fibers which can be due to mechanical trauma, or metabolic diseases such as diabetic neuropathy (Dzung and De Leon-Casasola 2010; Gierthmühlen and Baron 2016; Costigan, Scholz, and Woolf 2009; Woolf and Mannion 1999).

1.1.3 Trigeminal neuralgia

Trigeminal neuralgia (TN) is one of the most common types of chronic neuropathic facial pain affecting 4 to 13 per 100,000 people (Kumar et al. 2013; Katusic et al. 1991; MacDonald 2000). TN is a chronic neuropathic pain that has a distribution in one or more branches of the trigeminal nerve. Clinically, TN is defined as “a disorder characterized by recurrent unilateral brief electric shock-like pains, abrupt in onset and termination, limited to the distribution of one or more divisions of the trigeminal nerve and triggered by innocuous stimuli” (“Headache Classification Committee of the International Headache Society (IHS) The International Classification of Headache Disorders, 3rd Edition” 2018). TN is regarded as one of the most painful afflictions known to medical practice and is debilitating in its nature (Prasad and Galetta 2009; Love and Coakham 2001).

1.1.3.1 Trigeminal system anatomy

The trigeminal nerve is the fifth cranial nerve and has both sensory and motor components. The sensory portion conveys information from the oral and craniofacial regions to the brainstem, and the motor component innervates muscles involved in mastication. The trigeminal nerve emerges at the mid-lateral surface of the pons in the brainstem. The name trigeminal refers to the fact that the fifth cranial nerve has three major branches: ophthalmic

Chapter 1. Literature Review 9

(V1), maxillary (V2), and mandibular (V3). All three branches of the trigeminal nerve carry sensory information from the periphery into the CNS, while the third subdivision subserves motor functions as well. The sensory component of the trigeminal system is comprised of myelinated A and unmyelinated C fibers (Shankland 2000).

The ophthalmic or the first subdivision of the trigeminal nerve is the smallest branch of three and is purely afferent in function. Its sensory branches innervate the superior regions of the face including eyelids, forehead, nose, the frontal sinus, portions of the nasal cavity, the lacrimal gland, the ciliary body, the cornea, and the iris. The ophthalmic branch is the most superior division that appears from the trigeminal ganglion, passes through the cavernous sinus and reaches the orbit through the superior orbital fissure. The V1 is further divided to three major branches: the frontal, lacrimal, and nasociliary nerve (Shankland 2001a; Martin 2012; Wilson-Pauwels et al. 2013).

The second branch of the trigeminal nerve is intermediate in size compared to other trigeminal subdivisions and similar to V1, is purely sensory in function. It innervates all structures around the maxillary bone and midfacial area. These structures include the lower eyelids, maxillary sinus, soft palate, palatine tonsil, roof of the mouth, maxillary gingivae, and maxillary teeth. Neurons comprising the V2 reside in the middle of the trigeminal ganglion, between the mandibular and ophthalmic subdivisions. The V2 branch appears from the skull through the foramen rotundum. The maxillary branch further divides into 4 smaller nerves: zygomatic, infraorbital, superior alveolar, and palatine nerves (Wilson-Pauwels et al. 2013; Shankland 2001b; Singh 2019).

The third and largest branch of the trigeminal nerve is the mandibular subdivision (V3). Unlike V1 and V1, V3 is a mixed nerve with both sensory and motor components. The sensory component of the V3 is further divided into 4 smaller nerves: the buccal, lingual, alveolar, and the auriculotemporal nerves. The sensory component provides afferent information from the

Chapter 1. Literature Review 10

lower regions of the face including the teeth, the gingivae of the mandible, the skin of the temporal region, the ear, the lower lip, the anterior two third of the tongue, and the floor of the mouth. The motor component of the V3 innervates the muscles of first branchial arch, including the muscles of mastication, the tensor veli palatini and tympani, the mylohyoid muscle, and the anterior portion of the digastric muscle. The mandibular division has two separate roots, a large sensory root originates from the inferior part of the trigeminal ganglion, and a motor root that is located in the pons of the brain stem. The mandibular nerve leaves the cranium through the foramen ovale (Wilson-Pauwels et al. 2013; Shankland 2001c; Jannetta 1967). A schematic overview of the trigeminal nerve and its three subdivisions is provided in Fig 1.3.

The three subdivisions of the trigeminal nerve come together at the trigeminal ganglion (also known as Gasserian, or semilunar ganglion) which contains all the sensory afferent cell bodies (Vilensky, Robertson, and Suárez-Quian 2015). This ganglion resides in the Meckel’s cave located at the posterolateral aspect of the cavernous sinus. The axons of the sensory neurons project to the trigeminal brainstem nuclear complex (VBNC) (Hu and Woda 2013; Sessle 2006). These axons synapse onto the second-order sensory neurons at the VBNC. The sensory nuclei of the trigeminal nerve are the largest of the cranial nerve nuclei and are stretched over the midbrain, pons, medulla and upper two segments of the cervical cord (Shankland 2000). The sensory portion of the trigeminal system consists of three major nuclei: mesencephalic nucleus (in the midbrain), main/principle sensory nucleus (in the upper part of pons) and spinal nucleus (lower parts of pons, medulla and upper two cervical segments of the spinal cord).

The mesencephalic nucleus is a column of primary afferent sensory cell bodies and receives proprioceptive information from the muscles of mastication (Shankland 2000). The principle (main) trigeminal nucleus consists of secondary sensory neurons and is mainly involved in discriminative touch sensation from the face. The spinal nucleus of the trigeminal

Chapter 1. Literature Review 11

nerve receives nociceptive stimuli, temperature, and touch sensation from the skin of the head and face (Walker 1990) (see figure 1-7).

The spinal nucleus of the trigeminal nerve can be further subdivided into three subnuclei: oralis (Vo), interpolaris (Vi) and caudalis (Vc) (please refer to figure 1-6) (Sessle 2006). The most caudal of these subnuclei is Vc which is a laminated structure that extends caudally to into the dorsal horn of the spinal cord. Hence, Vc is also known as medullary dorsal horn (Hockfield and Gobel 1982). Almost all of the afferent C fibers in the trigeminal nerve have their terminal distributed in Vc and Vi/Vc transition zone (Hu and Woda 2013). Afferent Aδ fibers terminals are also found in Vc, Vo, and Vi. Additionally, Vc contains nociceptive neurons including wide dynamic range (WDR) or nociceptive specific (NS) neurons (Bereiter, Hirata, and Hu 2000).

Figure 1-6 Trigeminal brainstem sensory nuclear complex

This image depicts nociceptive somatosensory organization of the trigeminal brainstem nuclear complex. Trigeminal afferent neurons have their cell bodies in the trigeminal ganglion and project to

Chapter 1. Literature Review 12

second-order neurons in the brainstem sensory nuclear complex. This image was adapted from (Hu and Woda 2013) with Copyright License ID: 4847321131367.

The trigeminal motor nuclei are located in the tegmentum of the pons, medial to the principle trigeminal nucleus. The cell bodies for the motor component of the trigeminal nerve are located in this region and their axons innervate muscles of mastication and are bundled with the V3 sensory fibers (see figure 1-7).

Figure 1-7 Trigeminal nerve anatomy.

(A) Trigeminal nerve nuclei in the brainstem. (B) Trigeminal nerve course and ganglion. The images were adapted from (Singh 2019) with Copyright License ID: 4750851418698.

Chapter 1. Literature Review 13

In humans, the afferent sensory neurons in the trigeminal system carry sensory information to the CNS. The first-order neurons synapse with the second-order neurons in the VBNC. Subsequently, the second-order neurons carry the information to the ventral posteromedial nucleus (VPM), where they synapse with third-order neurons (Martin 2012). Third-order neurons project via the posterior limb of the internal capsule and corona radiata to relay the information to the cortex, including the face area of the primary sensory cortex, secondary somatosensory cortex, the midcingulate cortex, and posterior insula where the sensory signals (including nociception) are further processed (Singh 2019; Shankland 2001c; Vilensky, Robertson, and Suárez-Quian 2015) (see figure 1-8).

Nociceptive and thermal information are carried by the trigeminal system to the CNS (Sessle 2006). Furthermore, the nociceptive pathway in the trigeminal nerve utilizes three steps to relay sensory information to the CNS: First, the primary afferent neurons (first-order neurons) carry the information to the brainstem via the trigeminal root entry zone (REZ) to the VBNC where it synapses with second-order neurons within the spinal trigeminal nucleus (Walker 1990; Sessle 2000). Second, around 80% of the axons of the second-order neurons decussate midline and join the spinal lemniscus and project to the thalamus where they synapse with the third-order neurons at the VPM nucleus of the thalamus. Notably, in the trigeminal system, 20% of axons remain ipsilateral, and project onto the ipsilateral thalamus (Martin 2012). Some of the second-order neurons send collateral axons to the reticular formation in the brainstem and are involved in autonomic reflex responses to craniofacial stimuli (Sessle 2000)s. Third, the thalamic neurons relay the information to cortical regions including primary somatosensory cortex and insula where the nociceptive signals are processed. The following picture provides an overview of this pain and temperature pathway utilized in the trigeminal system.

Chapter 1. Literature Review 14

Figure 1-8 Trigeminal somatosensory pathways to the CNS.

The trigeminal nerve carries nociceptive stimuli from the face to the spinal trigeminal nucleus in the brainstem. Subsequently, the signal decussate at the brainstem to reach the medial dorsal and ventral medial posterior nuclei of the thalamus. Lastly, thalamic nuclei relay the signals to various cortical regions. The image is adapted from (Wilson-Pauwels et al. 2013), © Linda Wilson-Pauwels 2013.

1.1.3.2 Trigeminal neuralgia pain

TN is characterized by sudden, unilateral, stabbing pain face and is debilitating in nature (Hodaie and Coello 2013). TN annual incidence is 4 to 13 per 100,000 people (Katusic et al. 1991; MacDonald 2000). TN onset is usually after age 50, although younger individuals can also be affected. TN disproportionally affects females, with the male-to-female prevalence ratio approximately 1:1.5 (Katusic et al. 1991; Maarbjerg et al. 2014).

Chapter 1. Literature Review 15

TN can be divided into the following categories: I) classical TN; II) secondary TN; III) Idiopathic (“Headache Classification Committee of the International Headache Society (IHS) The International Classification of Headache Disorders, 3rd Edition” 2018). According to the International Headache Society (IHS): Classical TN is defined as cases caused by an aberrant blood vessel that exerts pressure onto the trigeminal nerve at its entry zone in the pons. Secondary TN is defined as TN that is present along with other major conditions such as MS, tumors, herpes zoster infection, or post-traumatic neuralgia. Idiopathic TN is defined as TN cases with “neither electrophysiological tests nor [Magnetic Resonance Imaging] MRI showing significant abnormalities” (“Headache Classification Committee of the International Headache Society (IHS) The International Classification of Headache Disorders, 3rd Edition” 2018). Advanced brain imaging may help us understand abnormalities in different TN categories. For example, our group has recently shown that a subgroup of TN patients have lesions only seen in the brainstem pontine region (Tohyama et al. 2020). These TN patients cannot be categorized into any of the previously known TN classification and empirical evidence suggests that surgical interventions do not lead to pain relief in these patients (Tohyama et al. 2020).

Many theories have been proposed to explain TN pain. Majority of TN cases are believed to be due to compression of the trigeminal nerve at its REZ (Haines, Jannetta, and Zorub 1980; McLaughlin et al. 1999; Love and Coakham 2001). A vascular loop in contact with the REZ can be identified in up to 80% to 90% of the TN cases (Nurmikko and Eldridge 2001; Love and Coakham 2001). The most common vessels involved in neurovascular compression are the superior cerebellar artery, anterior inferior cerebellar artery, and dolichoectatic vertebral artery (Yoshino et al. 2003; De Lange, Vielvoye, and Voormolen 1986).

The neurovascular compression primarily occurs at the REZ of the trigeminal nerve. The dorsal REZ is the boundary between the central and peripheral nervous system where the myelination changes from Schwann cells of the periphery to oligodendrocytes of the CNS.

Chapter 1. Literature Review 16

Morphological changes have been reported in the trigeminal nerve of TN patients. These changes include demyelination of the nerve at REZ, nerve deviation, distortion, and atrophy (Hilton et al. 1994; Nurmikko and Eldridge 2001).

1.1.3.3 Treatment strategies for TN

The first line of treatment for classical TN is oral pharmacotherapy. The antiepileptic drugs such as carbamazepine are known to be effective in managing pain in the majority of people with TN (Bennetto, Patel, and Fuller 2007; Gronseth et al. 2008; Wiffen et al. 2014). Other medications such as baclofen, gabapentin, and pregabalin have also been utilized to relieve the symptoms of TN (Hodaie and Coello 2013; Agarwal and Tripathi 2019).

Patients who are refractory to pharmacotherapies or cannot tolerate their side effects are potential candidates for surgery. A variety of surgical methods, both invasive and non-invasive, have been used to relieve TN symptoms. Invasive procedures to treat TN include microvascular decompression (MVD) of the trigeminal nerve. MVD involves approaching the trigeminal nerve root through a craniotomy to correct the neurovascular conflict by removal or separation of vascular structures away from the trigeminal nerve. This procedure was primarily developed by Peter J. Janetta and is one of the first procedures focused on hyperactive cranial nerve syndromes (Jannetta 1985).

Other surgical options to treat TN include stereotactic radiosurgery such as Gamma Knife Radiosurgery (GKRS). GKRS is an ablative procedure that uses focused gamma radiation to induces lesions. The treatment targets the proximal trigeminal root, which is the usual location of neurovascular conflict (Nurmikko and Eldridge 2001). The aiming of the beams is guided by magnetic resonance imaging (MRI) and a stereotactic frame (Sheehan et al. 2005). During the procedure, a sub-necrotic dose of 70-90 Gy is delivered to the nerve. If pain relief occurs after GKRS, it is typically delayed by one month after surgery. Around 70%-

Chapter 1. Literature Review 17

90% of patients report complete pain relief one year after surgery (Gronseth et al. 2008; Karam et al. 2014).

Figure 1-9 Neurosurgical treatment options for TN.

Two surgical interventions include (A) microvascular decompression (MVD) and Gamma Knife Radiosurgery (GKRS). MVD aims to physically reduce the compression at the trigeminal nerve root entry zone (REZ). GKRS targets the trigeminal nerve deploying 200 radioactive cobalt-60 sources focused on the REZ. The image is adapted from (Desouza, Hodaie, and Davis 2016) with permission, ©2016 DeSouza, Hodaie and Davis.

Chapter 1. Literature Review 18

1.2 The hippocampus and pain

As a multidimensional experience, pain processing and transmission engage multiple cortical and subcortical brain regions (Bingel et al. 2002). Pain perception is also associated with emotional processes such as fear, stress, and anxiety. The limbic system is a complex set of structures which is primarily involved in emotional processing, memory formation, and behavior regulation. Findings have suggested that the limbic system, specifically the hippocampus, is activated during processing of noxious stimuli and pain perception (G. Ji et al. 2010; Mutso et al. 2012; Ayoub et al. 2019).

Poor performance on memory and cognitive tests and complain about memory have been reported in chronic pain patients (Sjogren et al. 2005; J. M. Grisart and Van der Linden 2001; Park et al. 2001; J. Grisart, Van Der Linden, and Masquelier 2002; Ling et al. 2007; Mifflin, Chorney, and Dick 2016; Oosterman et al. 2011; Dick and Rashiq 2007; Schnurr and MacDonald 1995) [more detailed review is provided in the “role of hippocampus in pain processing” section of this thesis]. Similarly, impaired spatial memory performance is reported in animal models of neuropathic pain (Cardoso-Cruz, Lima, and Galhardo 2013). Additionally, many chronic pain patients also suffer from anxiety- and depression-related disorders (De Heer et al. 2014; Gureje et al. 2008; Maletic and Raison 2009). These findings suggest a relationship between the hippocampus and other pain processing centers in the CNS.

The hippocampus receives sensory and cognitive information from different regions of the brain and the limbic system and has various connections to other cortical and subcortical regions (Knierim 2015). The hippocampus is comprised of anatomical subregions with distinct cytoarchitecture and connections. While there is an increasing body of evidence suggesting hippocampal involvement in pain processing (Mutso et al. 2014, 2012; Ayoub et al. 2019; Apkarian 2008), there are however no studies of the effect of chronic neuropathic pain on the hippocampal subfields. Additionally, considering there are few models that can adequately

Chapter 1. Literature Review 19

study the potential dynamic nature of the structural changes in the hippocampus after successful pain resolution, the effect of pain relief on the hippocampus is less studied.

In the following chapters, I will explore the anatomy of the hippocampus and its functional connection to other brain regions and will review the current evidence on the role of the hippocampus in pain processing.

1.2.1 Hippocampal formation anatomy

Deep within the temporal lobe, below the floor of the temporal horn of the lateral ventricle lies two elongated C shaped structures called the hippocampus (figure 1-10).

Figure 1-10 3D model of the hippocampus in an average template of 70 healthy individual T1 scans.

The hippocampus is located in the medial temporal lobe of the brain beneath the cortical surface. These paired structures have the shape of a curved tube and resemble seahorses in shape. © Alborz Noorani 2020.

Chapter 1. Literature Review 20

The hippocampus is one of the most studied brain structures as it is involved in many diverse fundamental processes such as memory formation, stress, neurogenesis, and aging. The hippocampal formation consists of three major regions: I) Dentate Gyrus (DG); II) Cornu Ammoris (CA); III) Subiculum. Compared to the neocortex, the hippocampus appears earlier in the phylogenesis. Unlike the neocortex which has 6 major layers, the hippocampus is a type of allocortex called archicortex which has 3 principal layers: I) polymorphic layer; II) pyramidal layer (in hippocampus and subiculum)/granule cell layer (in DG); III) molecular layer (Duvernoy et al. 2005).

The hippocampus proper can be divided into three cytoarchitecturally distinct fields, CA1, CA2, and CA3. Although many texts include CA4 as a subfield of the hippocampus, CA4 refers to the polymorphic layer of the DG and is best to be classified with the DG (David and Pierre 2009).

The DG has three major cell layers. From the most superficial, there is a largely acellular layer called molecular layer. This molecular layer mostly holds the dendrites of the neurons in the granule cell layer. The middle cell layer of the DG is the granule cell layer which is considered the principal layer in the DG, is densely packed: it contains around 15x106 neurons in humans (West et al. 1994; Šimić et al. 1997). The DG, particularly its granule cell layer, is one of the two regions responsible for neurogenesis (addition of new neurons) in the adult brain (Toda et al. 2019). The third and the deepest layer of the DG is the polymorphic layer which sometimes is referred to as CA4. CA4 cells, also called hilus cells, only project to the DG (Laurberg and Sørensen 1981) and border the CA3 subregion of the hippocampus.

The subiculum borders the CA1 subregion of the hippocampus and the entorhinal cortex (EC) ventrally, and CA1 and the retrosplenial cortex dorsally (Insausti and Amaral 2012). The

Chapter 1. Literature Review 21

subicular complex is divided into three major subdivisions: the subiculum proper, presubiculum (PrS), and para-subiculum (PaS) (O’Mara et al. 2001). Like other hippocampal formation subregions, the subiculum has three major cell layers, with its principle layer being populated by large pyramidal neurons (O’Mara 2005). The subiculum acts as a hub to connect the hippocampus to other brain regions. The subiculum receives a massive input from CA1 and has projections to both cortical and subcortical regions of the brain. The subiculum connections to the cortex include connections to the EC, perirhinal cortex, and retrosplenial cortex (O’Mara et al. 2001). The subcortical regions that are connected to the subiculum include mammillary bodies, hypothalamus, amygdala, septal complex, nucleus accumbens, and thalamic nuclei such as interanteromedial nucleus (O’Mara 2005; O’Mara et al. 2001). Figure 1-11 depicts the anatomical location of the subiculum proper(S), PaS, and PrS, in relation to other subregions within the hippocampal formation.

Figure 1-11 Subiculum complex acts as a gateway to the hippocampus.

On the right a line drawing of a horizontal section of the hippocampus is depicted. The subiculum (S), preubiculum (PrS), and parasubiculum (PaS) are located between the hippocampus subregions and the entorhinal cortex (EC). The dotted lines depict borders around the subregions. These images were adapted from (O’Mara et al. 2001) with Copyright License ID: 4752001381845.

The entorhinal cortex (EC) is another important region in the hippocampal formation. Although not part of the hippocampal formation, the EC plays an important role in connecting the hippocampal formation to other brain areas (Insausti et al. 1995). The EC is ventromedial

Chapter 1. Literature Review 22

limbic region and is a part of the parahippocampal gyrus that has bilateral connections to a large number of limbic cortices (Tracey and Leknes 2013). Because of its unique location in relation to the hippocampus, the EC serves as an interface between the hippocampal formation and limbic cortices (Solodkin, Van Hoesen, and Insausti 2014). Unlike the hippocampus, the laminar structure of the EC consists of six layers. However, these layers are more rudimentary than the neocortex (Hannula and Duff 2017). Layer I of the EC receives input from the cortical regions of the brain (Insausti and Amaral 2008). Layer II is highly characteristic of the EC: the pyramidal and stellate cells that make up this layer send their projections to the molecular layer of DG (Witter and Amaral 1991).

1.2.2 Hippocampal function and connection

The hippocampal formation has unique and diverse connections to different areas of the brain, both cortical and subcortical. These connections can be divided into two major divisions. First are the intrinsic connections in which the focus is the hippocampal subfields connections to each other and the EC. Second, are the bilateral connections between the hippocampus and other areas of the brain, primarily via the fornix and parahippocampal gyrus (please refer to figure 1-12). This section provides a brief review of hippocampal connectivity.

1.2.2.1 Intrinsic hippocampal circuitry

The intrinsic hippocampal pathway follows a serial and mostly a unidirectional path which is largely excitatory (i.e., glutamatergic) (Bach et al. 2019). This circuitry connects different hippocampal subfields in a closed loop. The hippocampus has three major intrinsic pathways.

Chapter 1. Literature Review 23

Figure 1-12 Hippocampal circuitry depicting intrinsic and extrinsic hippocampal connections to different brain regions.

(a) Depicts the hippocampal formation, (b) shows the intrinsic pathways superimposed on the hippocampal anatomy, (c) patten of intrinsic hippocampal pathways and with their cortical projections. Alv: Alveus; CA1-CA3: sectors of the Ammons horn; DG: dentate gyrus; EC: entorhinal cortex; FF: fimbria/fornix; h: hilus of the dentate gyrus; mf: mossy fibers; pp: perforant pathway; sub: subiculum; PRC: perirhinal cortex; sc: Schaffer collaterals. These images were adapted from (Schultz and Engelhardt 2014) with Copyright License ID: 4847670518346.

The first major pathway is called the perforant pathway. The perforant pathway connects layer II and III of the EC to different areas of the hippocampal formation (Eberhard and Miles 2009). This pathway travels caudally from the EC and passes through the subiculum and the hippocampus, to reach its destinations at different subregions of the hippocampal formation (Witter 2007). The neurons in layer II of the EC project to the DG and CA3, while the neurons in layer III project to the CA1 and subiculum via temporoammonic pathway (Remodes and Schuman 2004; Vago and Kesner 2008). The temporoammonic pathway of the perforant pathway mediates spatial memory consolidation (Remodes and Schuman 2004) and chronic stress in animal models (Kallarackal et al. 2013). Additionally, it has been proposed that the perforant pathway plays a role in epileptic temporal lobe seizures (Scimemi et al. 2006).

The second major intrinsic hippocampal pathway is called the mossy fiber pathway. This pathway connects the DG to CA3 region of the hippocampus. The cells in the DG do not project

Chapter 1. Literature Review 24

outside of the hippocampus (Iglesias et al. 2016). The granule cells of the DG use their axons to project to the nearby CA3 pyramidal neurons (Kondo, Lavenex, and Amaral 2008). This pathway innervates all portions of the CA3 hippocampal subfield (Nicoll and Schmitz 2005). As such, it has been proposed that the mossy fibers synapse onto CA3 cells act as detonator, meaning that when a GC cell initiates an action potential in a mossy fiber, all CA3 cells that are innervated by that fiber fire action potentials (Henze, Urban, and Barrionuevo 2000; Lisman 1999). It has been suggested that the mossy fibers play a role in learning and memory, especially spatial learning (Crusio and Schwegler 2005) (see figure 1-13).

Figure 1-13 Intrinsic hippocampal circuitry.

(A) Depicts a drawing of the hippocampus and its intrinsic pathways. The fimbria and the subicular complex act as gateway to rely information to and from the hippocampus to other brain regions. This image was adapted from (Harry and D’Hellencourt 2003) with Copyright License ID: 4761961284321.

Chapter 1. Literature Review 25

(B) Depicts a schematic overview of major intrinsic hippocampal pathways in relation to the subicular and entorhinal cortex (EC). Abbreviations: DG: Dentate gyrus.

The third major pathway that connects together different subfields of the hippocampus is called Schaffer collateral pathway. CA3 pyramidal cells send their axons via the Schaffer collateral pathway to the pyramidal cells of the CA1 region (David and Pierre 2009; Hannula and Duff 2017). From there, the CA1 projects to all subregions of the subicular complex (PrS, subiculum, and PaS) (see figure 1-13).

1.2.2.2 Extrinsic hippocampal circuitry

The hippocampus receives afferent input from various regions of the brain and forwards this information through the fimbria, the fornix, and the subicular complex to cortical and subcortical areas of the brain (Schultz and Engelhardt 2014).

Corticohippocampal projections carry multimodal sensory information into the hippocampal formation. These inputs usually get processed in the following brain regions before they reach the hippocampal formation: the perirhinal and posterior parahippocampal cortices; and the EC (Libby et al. 2012; Solodkin, Van Hoesen, and Insausti 2014; Knierim 2015). The EC also has reciprocal connections to several cortical areas including the superior temporal gyrus, the ventral insular cortex, the posterior orbitofrontal cortex, the dorsolateral frontal cortex, the medial frontal cortex, and the cingulate cortex.

The main efferent connection in the hippocampal formation is through the fornix (David and Pierre 2009). The fornix is composed of axons mostly from the subicular complex and pyramidal cells of the hippocampus. This structure has both projections and commissural fibers. The commissural fibers converge at the crura of the fornix forming the hippocampal commissure and connect the two hippocampi to each other. Anteriorly, the fornix is split into

Chapter 1. Literature Review 26

two columns (Martin 2012). First are the pre-commissural fibers, which mostly originate from pyramidal cells of the hippocampus and proceed to the septal area (Hannula and Duff 2017; Insausti and Amaral 2012). Second are the post-commissural fibers which originate from the subicular complex and project to the hypothalamus and mammillary bodies (Andersen et al. 2009) (see figure 1-14). Through these connections, the hippocampus forwards the information to other subcortical areas of the brain where emotional responses are evoked. The following figure provides an overview of intrinsic and extrinsic connections of the hippocampus.

Figure 1-14 Hippocampal gross anatomy and connections to other brain regions (extrinsic circuitry).

This image is adapted from (Insausti and Amaral 2012) with Copyright License ID: 4847670645147.

1.2.3 The role of hippocampus in chronic pain conditions

As noted earlier, the hippocampus plays a significant role in forming/consolidating memories (Lynch 2004). Therefore, it is pertinent to ask whether chronic pain could affect

Chapter 1. Literature Review 27

memory and cognitive functions when investigating the role of the hippocampus in chronic pain conditions.

Indeed, memory complaints have been reported previously in chronic pain patients (Schnurr and MacDonald 1995). Additionally, around two-third of patients with chronic pain exhibit disruption in attention and working memory (Dick and Rashiq 2007). Chronic pain patients perform worse compared to healthy controls on tests of working memory and verbal episodic memory (Oosterman et al. 2011) with the same findings being replicated in female adolescences with chronic pain compared to their age and sex matched pain free peers (Mifflin, Chorney, and Dick 2016). The same trend of general decline in memory performance has been reported in chronic pain patients of other etiology including lower back pain (Ling et al. 2007), fibromyalgia (J. Grisart, Van Der Linden, and Masquelier 2002; Park et al. 2001), and mixed chronic pain patient samples (Sjogren et al. 2005; J. M. Grisart and Van der Linden 2001).

Some studies have proposed that the decrease in memory performance in chronic pain patients could be related to attentional capacity (Dick and Rashiq 2007; Eccleston and Crombez 1999; J. M. Grisart and Van der Linden 2001). However, according to Oosterman et al. (2011), a decline in attention would only explain some but not all differences in memory performance observed in chronic pain patients (Oosterman et al. 2011). Therefore, we need to consider chronic pain as more than mere persistent nociception.

Mansour et al. (2014) proposed a new explanation for pain chronification that could partially explain functional abnormalities reported in the hippocampus (Mansour et al. 2014). This theory argues that chronic pain is related to a shift in processing from sensory to emotional circuits. Nociceptive inputs in healthy individuals are transient and evoke acute pain perception by activating CNS pain processing centers including anterior cingulate cortex and the insula. However, when the nociceptive input is prolonged and persistent, it engages structures within

Chapter 1. Literature Review 28

the limbic system including the nucleus accumbens, the amygdala, and the hippocampus, leading to functional/structural alterations in these structures (Mansour et al. 2014).

Another theory that could explain the abnormalities observed in the hippocampus is that chronic states upregulate stress-related responses including dysregulation of the hypothalamic–pituitary–adrenal (HPA) axis (McEwen and Kalia 2010a; Sapolsky 1985; Vachon-Presseau et al. 2013). Stress hormones have potent growth-inhibiting effects and could inhibit neurogenesis in the hippocampus (Mirescu and Gould 2006). Interestingly, neurogenesis at the hippocampal formation is impacted in animal models of neuropathic pain, and there are reports of volumetric abnormalities in the hippocampus in chronic pain patients (Apkarian et al. 2017; Mutso et al. 2012). The effect of stress on the hippocampus in the context of chronic pain is further explored in the following sections.

Following sections review how the hippocampus is affected in chronic pain conditions and how, in return, the hippocampus shape the experience of pain in chronic states.

1.2.3.1 Nociception and the hippocampus

Nociceptive signals are received by different cortical regions, thalamic nuclei and limbic areas, including the hippocampus, for further processing (McCarberg and Peppin 2019). It has been suggested that the hippocampus receives indirect nociceptive input from the periphery through the spinothalamic and parabrachial ascending pathways (Duric and McCarson 2006), while septohippocampal neurons receive direct nociceptive input from the spinal cord (Cliffer, Burstein, and Giesler 1991; Dutar, Lamour, and Jobert 1985; Khanna and Sinclair 1989). For example, it has been reported that noxious stimuli, either mechanical or thermal, can activate septohippocampal neurons in anesthetized rats (Dutar, Lamour, and Jobert 1985) (please refer to figure 1-15).

Chapter 1. Literature Review 29

The hippocampus plays a critical role in consolidation of information from short- to long- term memory as well as associating emotions to these memories. Neuronal plasticity due to long-term potentiation (LTP) is believed to be the underlying mechanism for memory consolidation (Lynch 2004). Animal studies have shown that noxious stimuli can directly affect the hippocampus by decreasing the excitability of hippocampal CA1 pyramidal cells (Khanna and Sinclair 1989; Khanna 1997).

Figure 1-15 Ascending and descending nociceptive transmission and modulation pathways in the CNS in relation to the hippocampus.

The hippocampus receives painful stimuli directly from the thalamus or indirectly from other brain regions including the limbic system, parahippocampal gyri, and entorhinal cortex. This picture is adapted from (Zhuo 2008) with Copyright License ID: 4771710018226. Abbreviations: ACC: anterior cingulate cortex; DRG: dorsal root ganglion; GABA: gamma aminobutyric acid; Glu: glutamate; HC: hippocampus; IC: insular cortex; NRM: nucleus raphe magnus; PAG: periaqueductal gray; PFC: prefrontal cortex; S1: primary somatosensory cortex; S2: secondary somatosensory cortex; SDH: spinal dorsal horn; VPL: ventral posterolateral nucleus of the thalamus.

Chapter 1. Literature Review 30

Animal studies using the spared nerve injury (SNI) animal model found that there was impaired frequency facilitation, a presynaptic form of short-term plasticity, and LTP at the CA3-CA1 synaptic junctions – suggesting short- and long-term memory deficits in mice and rats (Ren et al. 2011). Similarly, Kodama et al. (2011) reported that partial sciatic nerve ligation in mice leads to cognitive dysfunction (Kodama, Ono, and Tanabe 2011). In this experiment, recognition memory by novel-object recognition was assessed and the authors showed that animals exhibit impaired recognition ability for novelty after a peripheral nerve injury. Additionally, long-term potentiation of CA1 hippocampal synaptic transmission was impaired in a murine animal model of neuropathic pain following peripheral nerve injury which suggests that there are abnormalities in hippocampal synaptic plasticity in chronic pain conditions (Kodama, Ono, and Tanabe 2007). Similarly, other studies have also reported that low- intensity shocks to the paws in experimental animal models impair LTP in the hippocampus (Shors et al. 1989).

1.2.3.2 Stress and anxiety, as moderators of chronic pain, induce changes in the hippocampal complex

Another thread binding the hippocampus to chronic pain is the role of anxiety, stress, and depression. Some chronic pain conditions are highly comorbid with anxiety and/or depressive disorders (De Heer et al. 2014; Gureje et al. 2008). In particular, over half of patients with chronic neuropathic pain conditions suffer from mood disorders such as depression and anxiety (Maletic and Raison 2009; McWilliams, Cox, and Enns 2003). Additionally, several studies have reported smaller hippocampal volume in patients with stress-like behaviors, including post-traumatic stress disorder, compared to healthy individuals (Gilbertson et al. 2002; Bonne et al. 2001; Villarreal et al. 2002; Schoenfeld et al. 2017; Sheline, Gado, and Kraemer 2003; Kitayama et al. 2005; Bremner et al. 1995).

The hippocampus plays a major role in depression and modulating stress (Wingenfeld and Wolf 2014; S. Campbell and MacQueen 2004). Stress can negatively affect memory and

Chapter 1. Literature Review 31

hippocampal plasticity (E. J. Kim, Pellman, and Kim 2015). In particular, stress can alter firing rates of hippocampal place cells (J. J. Kim et al. 2007), which are responsible for spatial navigation and memory (O’Keefe and Dostrovsky 1971; Eichenbaum et al. 1999; Moser, Rowland, and Moser 2015). Additionally, prolonged stress, similar to chronic neuropathic pain conditions, affects the hippocampal plasticity by altering the LTP (J. J. Kim and Diamond 2002; Shors 2006).

Stress hormones such as corticosteroids, and immune mediators, including tumor necrosis factor (TNF), are proposed to be the main mediators of the effect of stress on the hippocampus (E. J. Kim, Pellman, and Kim 2015; Dellarole et al. 2014). Neuroendocrine hormones such as glucocorticoids are synthesized and secreted by the HPA axis in response to stress (see figure 1-16). The high- and low-affinity glucocorticoid receptors are found in abundance in the hippocampus. Both high and low levels of the glucocorticoid hormones can impair the LTP in the hippocampus and change hippocampal morphology (McEwen and Sapolsky 1995; Vaher et al. 1994; Diamond et al. 1992). In particular, Alfarez et al. (2002) have reported reduction of LTP in the CA1 subregion of the hippocampus after application of corticosterone (Alfarez et al. 2002).

TNF is involved in pathogenic mechanisms of chronic pain and is an integral component of nociception (Xu et al. 2006; Zelenka, Schäfers, and Sommer 2005; Deleo, Colburn, and Rickman 1997; Covey et al. 2002, 2000; Sommer, Marziniak, and Myers 1998; Sommer et al. 1997; Martuscello et al. 2012). It has been reported that TNF expression increases in the brain during persistent pain (Covey et al. 2002). Furthermore, increasing TNF level in the hippocampus of rats can produce persistent pain like symptoms (Martuscello et al. 2012). Similarly, abnormal levels of TNF has been observed in depressive-like conditions (Mikova et al. 2001). Additionally, TNF has been proposed as one of the key modulators of neurogenesis (Borsini et al. 2015) and TNF-R1, one of the two TNF receptors, is reported to exert a negative effect on progenitor proliferation in adult hippocampal neurogenesis (Iosif et al. 2006). In

Chapter 1. Literature Review 32

particular, in neuropathic pain conditions, Dellarole et al. (2014) have reported that neuropathic pain induces depressive-like behavior and disrupts hippocampal plasticity and neurogenesis via the TNF receptor signaling (Dellarole et al. 2014).

In adults, the DG subregion of the hippocampus can generate new neurons from neuronal stem cells, a process known as neurogenesis. Neurogenesis plays a critical role in hippocampal plasticity and functions such as memory encoding and mood regulation (Toda et al. 2019). However, this process is highly sensitive to changes in environmental factors, pathological conditions – such as Alzheimer’s disease, Parkinson’s disease – and exogenous steroids (Haughey et al. 2002; Winner et al. 2012). In particular, depression and environmental stress have been proposed to negatively affect hippocampal neurogenesis mainly through the HPA axis (Eisch and Petrik 2012) (see figure 1-16).

Figure 1-16 Dentate Gyrus neurogenesis affects mood, cognition and memory consolidation. Neurogenesis is negatively affected via the hypothalamic-pituitary-adrenal axis.

This image is adapted from (Eisch and Petrik 2012). Reprinted with permission from AAAS.

A similar pattern of hippocampal changes has also been observed in chronic pain conditions. In particular, Durick et al. (2006) showed that long-term inflammatory nociception alters hippocampal gene expression profiles and significantly reduces neurogenesis, in line

Chapter 1. Literature Review 33

with other animal stress models (Duric and McCarson 2006). Similarly, an animal study using the SNI model of chronic pain showed decreased neurogenesis and altered short-term synaptic plasticity compared to controlled animals (Mutso et al. 2012). Consistent with this finding, a study using the chronic constriction injury animal model showed that neuropathic pain negatively influences hippocampal neurogenesis through the loss of neuroblasts (proliferation) and reduced survival of new neurons. The impacts were exacerbated when an additional stress factor was introduced (Romero-Grimaldi et al. 2015). Moreover, a recent study has proposed that neurogenesis downregulation can block persistent pain and its upregulation can prolong persistent pain in animal models (Apkarian et al. 2017). All in all, these findings attest that the hippocampal neurogenesis is altered in chronic neuropathic conditions. However, the exact mechanisms how chronic pain and/or the stress, accompanied by chronic pain conditions, can affect the hippocampal neurogenesis need further investigation.

In addition to alterations in neurogenesis, neurophysiological changes exerted by chronic pain conditions can also negatively affect other molecular and cellular aspects of the hippocampus. A recent study has shown that the structural and biochemical properties of the hippocampal extracellular matrix are altered in chronic pain conditions (Tajerian et al. 2018). Specifically, Tajerian et al. (2018) reported deficits in working and spatial memory in animal models in association with altered extracellular matrix microarchitecture and decreased hippocampal dendritic complexity. Similarly, another study suggested that neuropathic pain is coupled with microglial activation, changes in the hippocampal production of pro‑ and anti‑inflammatory cytokine, and ultimately – in agreement with others – altered neurogenesis. (Tyrtyshnaia et al. 2019).

Although the role of the hippocampus in development and maintenance of chronic pain needs to be further explored, the molecular changes reported in the literature so far suggest that this brain region participates in processes involved in perception of pain and is altered in these

Chapter 1. Literature Review 34

processes, suggesting that the hippocampus contributes to the pain processing and modulation procedure in the CNS.

1.2.4 Sex differences in the hippocampus

Studying sex differences in various disorders and disease conditions is important because increasing numbers of studies have identified sex differences in disease manifestation and treatment efficacy (Gutiérrez-Lobos et al. 2002; McPherson et al. 1999; Wiesenfeld-Hallin 2005). Several studies, especially in the past two decades, have also identified sex differences in the hippocampus, hippocampal neurogenesis, cognitive functions, the effect of stress, pain perception, and chronic pain conditions (Bale and Epperson 2015; Yagi and Galea 2019). This section examines the current literature on biological sex differences in the hippocampus in the light of chronic pain and stress.

Human studies have shown sex differences in functional brain connectivity (Zhang et al. 2016; Ingalhalikar et al. 2014; Joel et al. 2015; Scheinost et al. 2015; Firouzian et al. 2020; G. Wang, Erpelding, and Davis 2014). For instance, (Filippi et al. 2013) showed that males have increased connectivity in the parietal and occipital regions compared to females, whereas females showed increased connectivity in the frontal and temporal regions. Furthermore, functional MRI (fMRI) studies have reported sex differences in language processing with females showing greater activation in the temporal and frontal lobe regions compared to male (Kansaku, Yamaura, and Kitazawa 2000; Baxter et al. 2003). The sex differences are not limited to functional connectivity as large scale meta-analyses have shown structural sex differences in different brain regions including globus pallidus and putamen (Guadalupe et al. 2017).

Chapter 1. Literature Review 35

Sex differences exist in morphology, electrophysiology, activation, and connectivity properties of the hippocampus (Oberlander and Woolley 2016; Maren, De Oca, and Fanselow 1994; Harte-Hargrove et al. 2015; Gould, Woolley, et al. 1990; Galea et al. 1997; Mendell et al. 2017). While the whole hippocampal volume may not show sex differences (Tan et al. 2016; Guadalupe et al. 2017), subregional volumetric sex differences have been reported in humans. For example, a larger posterior hippocampus has been observed in females compared to males (Persson et al. 2014). Additionally, rodent studies have reported sex difference in morphology of the GC neurons and CA3 pyramidal neurons (Mendell et al. 2017; Gould, Woolley, et al. 1990; Woolley, Gould, and McEwen 1990; Woolley et al. 1990; Persson et al. 2014; Gould, Westlind-Danielsson, et al. 1990). Similarly, stressful situation and stress hormone synthesized and released by HPA exhibit different effects on the hippocampus in different sexes. For example, Shors, et al. (2001) reported that an acute stressful event has an opposite effect on dendritic spine density in different sexes, with females showing reduced spine density and males enhanced spine density in the hippocampus (Shors, Chua, and Falduto 2001).

Neurogenesis, another important cellular aspect of the hippocampus, is also under the influence of biological sex especially in stress conditions. For example, acute as well as repeated stress have shown to decrease cell proliferation and the number of proliferating stem cells in male but not female rats (Hillerer et al. 2013a; Falconer and Galea 2003). Interestingly, chronic early life stress can reduce neurogenesis in adult male but not female rats (Naninck et al. 2015).

Additionally, sex differences in pain perception, pain sensitivity, pain responses, pain relief have been reported in both chronic pain as well as healthy individuals (Kröner-Herwig et al. 2012; Racine et al. 2012a; Greenspan et al. 2007; Mogil and Bailey 2010; Hurley and Adams 2008; Ruau et al. 2012; Golden and Voskuhl 2017; Rosen, Ham, and Mogil 2017; Sorge and Totsch 2017; Sorge and Strath 2018; Mogil 2012; Fillingim et al. 2009; Pieretti et al. 2016; Wiesenfeld-Hallin 2005; G. Wang, Erpelding, and Davis 2014; Hashmi and Davis

Chapter 1. Literature Review 36

2010a, 2010b, 2009, 2014). Chronic pain is not equally prevalent in both males and females, with most chronic pain conditions occuring overwhelming more often in females than males (Mogil 2012). Similar trend has been reported in neuropathic conditions, with females significantly more likely to suffer from a chronic pain with neuropathic characteristics (Torrance et al. 2006; Harifi et al. 2013; Bouhassira et al. 2008). Several studies have shown that females and males have different pain sensitivity and pain perception (Racine et al. 2012b, 2012a; Paller et al. 2009; Vacca et al. 2014; Hashmi and Davis 2010a, 2010b, 2014). Additionally, in a rat model of trigeminal neuropathic pain, females showed more pronounced nociceptive behaviors compared to males (Korczeniewska et al. 2017).

Evidence discussed in this section overwhelmingly suggest that the sex of the patient can affect chronic pain conditions as well as the hippocampus. Therefore, when investigating the effect TN on the hippocampus, sex differences must be studied and considered.

Chapter 1. Literature Review 37

1.3 Structural brain imaging

Prior to surgical interventions for TN, all patients undergo MRI. In most cases, the brain imaging is also a part of post-surgical follow-ups. The MRI brain images can help clinicians to make clinical decisions and can assist researchers to non-invasively obtain structural and functional information. In this section, the fundamentals of structural brain imaging are briefly discussed, and studies utilizing hippocampal imaging are reviewed.

1.3.1 Structural MRI

1.3.1.1 T1-Weighted imaging

In MRI techniques, strong magnets and radiofrequency pulses are utilized to collect information about atomic nuclei within tissues of the body. Being the most abundant atom in the body, hydrogen nuclei (single proton) are mostly exploited in MRI techniques (Grover et al. 2015).

Protons are positively charged, and they act like small magnets with a north and south pole. Therefore, hydrogen protons are susceptible to external magnetic fields – such as the MRI scanner. Each proton rotates 360° around its own axis and spins with a certain speed – which is called Larmor frequency – and continuously changes phase.

When protons are put into a strong external magnetic field, they align themselves parallel to this external magnetic field. Therefore, when a subject is placed in an MRI scanner, most hydrogen protons are aligned to the magnetic field, pointing toward the subject’s head at the resting phase. This direction is called the Z axis or the B0. Subsequently, radiofrequency (RF)

Chapter 1. Literature Review 38

pulses are deployed to make the hydrogen protons spin in-phase and cause them to rotate their magnetization field from the Z axis to the XY axis which are at a right angle to the Z axis. This process is called excitation. When the RF pulses are switched off, the protons will return to their original state. This process is called relaxation.

In T1 relaxation, protons return to their original state and release the energy they received from the RF pulses to the surroundings. T1 relaxation time is considered as the time needed to achieve 63% of the original state and T1 describes what happens in the Z axis. In contrast, T2 describes the relaxation event in the XY axis and T2 relaxation time is defined as the time required to reach 37% of the original energy state after the RF pulses.

Different tissues have different relaxation time. Fat has shorter T1 relaxation time than water as it transfers the energy it received to the surrounding at a faster pace due to its hydrogen arrangements. T1 weighted sequences utilize the T1 relaxation time differences to create a contrast in the image – with fat having a higher signal intensity and appearing white on the image and water appearing black due to its lower signal intensity.

Therefore, T1-weighted (T1w) images is a basic pulse sequence in MRI and depicts differences in T1 relaxation times of tissues (Bitar et al. 2006). T1w images depict anatomical features of the brain and are exploited in various anatomical studies.

1.3.1.2 Grey matter analysis

Brain morphometry refers to the size and shape of the brain and its structures. The brain changes as it goes through development, decays with age, learning, and alters as undergoes diseases. Therefore, brain morphometry has been one of the most studied modalities of brain imaging. There are multiple features that can be utilized in a brain morphometry study such as grey matter (GM) volume, white matter (WM) volume, cortical thickness, cortical curvature, and cortical surface area, amongst others.

Chapter 1. Literature Review 39

One of the commonly used software packages for brain morphometry studies is FreeSurfer (can be downloaded from https://surfer.nmr.mgh.harvard.edu/) (Fischl 2012) which utilizes two major approaches to examine MRI images: surface-based (for cortical regions) and volume-based (for subcortical structures). The volume-based approach consists of multiple stages to analyze individual T1 weighted images. A complete discussion of the algorithms and mathematical models involved in this process are provided elsewhere (Fischl et al. 2002, 2004). Briefly, these stages include: I) Affine registration with MNI305 space (The MNI305 is a version of Montreal Neurological Institute (MNI) average brain space constructed from 305 T1-weighted MRI scans, that are linearly transformed to Talairach space (Evans et al. 1994). The MNI305 space is specifically designed to be insensitive to brain pathology and abnormalities to maximize the accuracy of the final segmentation. In this step, individual T1 weighted images are linearly aligned with the MNI305 template space.); II) Initial volumetric labelling, meaning specifying subcortical structures in the T1 images; III) Intensity normalization. This is done because MR images have different intensity and contrasts due to image acquisition protocols and scanners differences. Intensity normalization brings the intensities to a common scale across people. This ensures that the grey matter and white matter are consistently recognized and correctly labeled.); IV) Non-linear alignment to the MNI305 space (Individual subjects are aligned to the MNI305 template space using a non-linear transformation to achieve a more accurate registration to the template space.); V) Labelling the volume (An atlas is built from a set of subjects whose brains have been manually labeled. Later, these labels are mapped into the MNI305 space. For individual processing, probabilistic algorithms are employed to label brain structures in each subject.)

Through these measured steps, FreeSurfer labels brain subcortical structures and calculates volumetric values for each structure. While traditionally FreeSurfer has been used to categorize the structure of the neocortex, the most recent version of FreeSurfer is now able to anatomically segment the hippocampus into its subfields (Iglesias et al. 2015). This was

Chapter 1. Literature Review 40

demonstrated in a study in 2015 when fifteen autopsy samples were scanned at 0.13 mm isotropic resolution. These images were manually segmented into 13 different hippocampal subfields (alveus, presubiculum, subiculum, parasubiculum, CA1, CA2/3, CA4, granule cell layer of dentate gyrus (GC DG), hippocampus–amygdala-transition-area (HATA), fimbria, molecular layer of hippocampal proper (ML HP), hippocampal fissure, and hippocampal tail). Additionally, manual segmentation of the whole brain was obtained from a separate dataset of in vivo MRI scans with 1mm resolution. The manual labels from ex vivo and in vivo were combined into a computational atlas of the hippocampal formation. The resulting atlas is employed in the FreeSurfer 6.0 to automatically segment the hippocampal subregions in individual structural images (Iglesias et al. 2015).

1.3.2 Hippocampal involvement in pain processing – evidence from neuroimaging

The role of hippocampus in pain processing has been studied using functional and structural neuroimaging modalities. A fMRI study of acute pain responses suggested that hippocampal activation represented part of a pain modulation response (Ploghaus et al. 2001). Moreover, an fMRI study suggested that there is reorganization of hippocampal functional connectivity as patients transition from acute to chronic back pain (Mutso et al. 2014). Similarly, hippocampal functional changes were observed in patients with migraine (Maleki et al. 2013).

Structural MRI studies have reported GM abnormalities in the hippocampus in several chronic pain conditions. Voxel based morphometry (VBM) analyses have shown both hippocampal GM density is increased (Khan et al. 2014; Bagarinao et al. 2014; Seminowicz et al. 2010; Hubbard et al. 2014; J. Liu et al. 2015; Riederer et al. 2017) and decreased (Coppola et al. 2017; Y. Wang et al. 2019) in chronic pain patients compared to healthy controls. Additionally, two studies have shown both greater and lesser GM density in different hippocampal subregions in patients with of chronic pain compared to healthy controls (Naegel

Chapter 1. Literature Review 41

et al. 2014; Erpelding et al. 2016). Although VBM, which has been utilized in these studies, lacks the capacity to look at the hippocampal formation as a whole, these findings further highlight the hippocampal involvement in modulating and processing pain.

Structural changes have also been reported in chronic pain patients when investigating the hippocampus as a whole – i.e. performing a volumetric analysis, rather than a voxel wise approach. Specifically, our group has recently showed that the whole hippocampus is smaller in TN patients compared to healthy controls (Hayes et al. 2017).

Chapter 2 Aims & Hypotheses

The general aim of this work is to investigate the structure of the hippocampus and its subfields in TN patients. Towards this aim, the goals were to determine whether patients with TN exhibit abnormalities of hippocampal subfields compared to healthy individuals and whether these abnormalities are reversed after successful surgical treatment. To achieve this goal, structural MRI neuroimages were assessed before and after surgical intervention in TN patients and the results were compared with healthy controls. The specific aims and hypotheses for two thesis studies are provided below.

2.1 Study I: Selective hippocampal subfield volume reductions in classic trigeminal neuralgia

2.1.1 Main Aim

The hippocampus plays a role in modulating emotions, behaviors, and shaping the experience of pain in chronic pain conditions. Additionally, structural abnormalities in forms of whole hippocampal volume reduction have been identified in TN patients (Hayes et al. 2017). The complex organization of the hippocampus and its functions, point to the importance of going beyond investigating the entire structure of the hippocampus as a single volume, as has been the case in some previous studies. However, some neuroimaging techniques and Chapter 2. Aims & Hypotheses 43

imaging processing, can be used to examine the hippocampus in more details than done previously, and study the hippocampal subfields.

As such, the overarching aim of this work was to study the hippocampal subfields in TN patients. To our knowledge, this is the first study to look at the hippocampal subfields in chronic pain conditions. Thus, the study findings may further elucidate the relationship between chronic neuropathic pain and CNS changes.

2.1.2 Specific Aims

I. To determine if TN is associated with volumetric hippocampal subfield abnormalities and if so, which subfields are affected.

II. To determine the relationship between hippocampal volume changes (compared to healthy controls) and TN pain duration.

III. To determine the relationship between sex and hippocampal volume abnormalities.

2.1.3 Hypotheses

I. There are selective subfield hippocampus GM alterations associated with TN:

o Subfields associated with neurogenesis, such as DG and CA4 regions, and subregions such as CA1 and subiculum which are involved in encoding, processing of neuronal input, and hippocampal output are smaller in TN patients compared to healthy controls.

Chapter 2. Aims & Hypotheses 44

II. Smaller hippocampi and their subfields in TN patients compared to healthy controls are associated with TN pain duration.

III. The amount of GM volume reduction differs in TN males and females.

2.2 Study II: TN pain relief reverses hippocampal abnormalities

2.2.1 Main Aim

The role of the hippocampus in nociceptive processing and modulation has been studied in animal models using cellular and molecular approaches and in humans deploying neuroimaging techniques. Findings from the first study in this thesis reported GM abnormalities in the hippocampal subfields of TN patients. However, the effect of pain relief on the hippocampus and its subfields is yet to be studied. For this purpose, TN serves as an apt model because surgical treatments are effective in resolving TN pain. As such, the main goal of this study is to investigate hippocampal formation changes after successful pain treatment using brain structural neuroimages. The results of this study can further help us understand the role of the hippocampus in pain processing and shaping pain experience and delineate whether hippocampal abnormalities are reversable after pain relief.

Chapter 2. Aims & Hypotheses 45

2.2.2 Specific Aims

I. To determine if hippocampal abnormalities are normalized after pain relief.

II. To determine which hippocampal subfields change after pain resolution.

III. To determine whether there are sex differences in the extent of hippocampal changes following pain relief.

2.2.3 Hypotheses

I. There will be selective subfield hippocampus GM changes after pain relief:

o Subregions involved in neurogenesis – such as CA4 and DG – and neuronal input/out processing – such as CA1 and CA2/3 – will increase in size.

II. With pain relief, the hippocampal abnormalities will normalize and not be significantly different from controls’ hippocampal volumes changes.

III. The changes seen in the hippocampus following pain relief are sex dependent with females showing more increase in the hippocampal volume than males.

Chapter 3 Study I: Selective hippocampal subfield volume reductions in classic trigeminal neuralgia

This study was published in NeuroImage Clinical Journal © 2019. No text or figure has been modified from the published manuscript. Permission to reprint the manuscript has been obtained from the NeuroImage Clinical Journal.

Vaculik, M. F.*, Noorani, A.*, Hung, P. S.P., & Hodaie, M. (2019). Selective hippocampal subfield volume reductions in classic trigeminal neuralgia. NeuroImage: Clinical, 23, 101911. https://doi.org/10.1016/J.NICL.2019.101911 (*Co-first author)

3.1 Abstract

TN is a chronic neuropathic pain syndrome characterized by paroxysmal unilateral shock-like pains in the trigeminal territory most frequently attributed to neurovascular compression of the trigeminal nerve at its root entry zone. Recent advances in the study of TN suggest a possible CNS role in modulation and maintenance of pain. TN and other chronic pain patients commonly experience alterations in cognition and affect, as well as abnormalities in CNS volume and microstructure in regions associated with pain perception, emotional modulation, and memory consolidation. However, the microstructural changes in the hippocampus, an important structure within the limbic system, have not been previously studied in TN patients. Here, we use grey matter analysis to assess whether TN pain is associated with altered hippocampal subfield volume in patients with classic TN. Anatomical MR images of twenty-two right-sided TN patients and matched healthy controls underwent automated segmentation of hippocampal subfields using FreeSurfer v6.0. Right-sided TN patients had significant volumetric reductions in ipsilateral CA1, CA4, dentate gyrus, Chapter 3. Study I 47

molecular layer, and hippocampus-amygdala transition area – resulting in decreased whole ipsilateral hippocampal volume, compared to healthy controls. Overall, we demonstrate selective hippocampal subfield volume reduction in patients with classic TN. These changes occur in subfields implicated as neural circuits for chronic pain processing. Selective subfield volume reduction suggests aberrant processes and circuitry reorganization, which may contribute to development and/or maintenance of TN symptoms.

Keywords: Trigeminal Neuralgia; Chronic Pain; Facial Pain; Hippocampus; Structural MR Analysis

3.2 Introduction

TN is the most common chronic neuropathic facial pain disorder, characterized by paroxysmal unilateral electric shock-like pain in the trigeminal nerve subdivisions. TN is closely linked to trigeminal neurovascular compression at its root entry zone, which frequently necessitates surgical interventions to alleviate symptoms (Love and Coakham 2001; Nurmikko and Eldridge 2001). As a type of severe neuropathic pain, TN has several unique features that make it an ideal model for the investigation of the effect of pain on brain structure. TN overwhelmingly unilateral, severe and is generally not associated with numbness or sensory deficits reported in different chronic pain syndromes. This distinguishes TN from other syndromes where pain is more diffuse, or axial, and where there is greater inter-individual heterogeneity in the expression of pain.

GM and WM abnormalities within the CNS occur with chronic pain (Cauda et al. 2014; Henry, Chiodo, and Yang 2011; Smallwood et al. 2013). Likewise, chronic neuropathic pain

Chapter 3. Study I 48

including TN results in GM volume changes within areas such as insular cortex (Pan et al. 2015). GM abnormalities may occur as a consequence of chronic pain, as some abnormalities show reversibility with effective pain treatment (Gwilym et al. 2010; Rodriguez-Raecke et al. 2013; Seminowicz et al. 2011). Alternatively, chronic pain can produce a maladaptive stress response, which triggers functional reorganization of pain-related networks, including those involving the hippocampus (Baliki et al. 2010, 2011; Vachon-Presseau et al. 2013).

We have previously demonstrated that GM and WM changes in CNS structures are important for pain perception, pain modulation, and motor function (DeSouza et al. 2013; Desouza, Hodaie, and Davis 2014). Furthermore, altered diffusivities in the pontine segment of trigeminal nerve can help to predict and prognosticate responders from non-responders to surgical treatments (Hung et al. 2017). Recently, we reported that TN results in changes to specific affect-related circuits, and reduced GM volumes in multiple regions including the hippocampus (Hayes et al. 2017).

The hippocampus has been long investigated for its widespread anatomical connections, with key roles in processes including cognition, memory and the limbic circuitry of emotion (Fortin, Agster, and Eichenbaum 2002; S. Kim et al. 2015; Nestler et al. 2002). While its role has been studied in conditions such as dementia, stress, and cognitive disorders; its involvement in chronic pain has not been well defined. Yet, patients with chronic pain uniformly report cognitive, memory changes, and pain-associated negative affect (McCarberg and Peppin 2019). Thus, investigation of the role of the hippocampus in chronic pain is timely.

The hippocampus receives complex integrated sensory and cognitive information, including pain, from different regions of the brain and limbic system and has diverse cortical projections. It comprises different anatomical components, or subfields, with distinct morphologies and connections. As such, these subfields, notably the subiculum, CA1 – CA4, and DG, demonstrate functional specialization with key involvement in distinct processes such

Chapter 3. Study I 49

as verbal fluency, memory, spatial navigation, and emotional processing. For example, prior studies have suggested CA3 and DG involvement in memory encoding and early retrieval, whereas CA1 is primarily responsible for recognition and late retrieval (Acsády and Káli 2007; Hunsaker and Kesner 2008; Kesner and Hunsaker 2010; Rolls and Kesner 2006). Additionally, previous studies have delineated hippocampal circuit involvement in pain processing (M. G. Liu and Chen 2009) and neurogenesis deregulation in chronic pain animal models (Apkarian et al. 2017), however the potential level of functional specialization of the hippocampus with respect to pain has not been investigated. Assessing the impact of hippocampal subfields may further elucidate the relationship between chronic neuropathic pain and CNS changes, for which TN, a severe form of unilateral neuropathic pain, is a particularly apt model for study. Thus, in this study, we hypothesize there will be selective subfield hippocampus GM alterations associated with TN. Specifically, we anticipate reduction in subfields associated with neurogenesis, such as DG and CA4 regions, with similar effects on CA1 subregion which is primarily involved in encoding and processing of neuronal input. To study this, we aim to use MRI and grey matter analysis to segment the hippocampus and analyze individual subfield volume changes in TN patients. We further investigate the effect of sex as well as pain duration on hippocampal changes.

3.3 Methods 3.3.1 Ethics

The University Health Network (UHN) Research Ethics Board approved this retrospective study of classical TN patients. Patient data was analyzed retrospectively and there was no active participation by patients. Individual patient consent was not required for this retrospective study. In addition, the UHN Research Ethics Board approved recruitment of healthy control subjects and the procedure to obtain written informed consent. Each healthy

Chapter 3. Study I 50

control participant provided written informed consent. All MRI scans where anonymized prior to analysis and stored in secure databases.

3.3.2 Participants

Twenty-two TN subjects seen at the Toronto Western Hospital between May 2008 and February 2011 were selected for the study using the criteria for classic TN as outlined by The International Classification of Headache Disorders (“Headache Classification Committee of the International Headache Society (IHS) The International Classification of Headache Disorders, 3rd Edition” 2018). Briefly, the inclusion criteria were: 1) unilateral (right-sided) pain involving one or more branches of trigeminal nerve; 2) stereotypical pain attacks involving intense, sharp, superficial, or stabbing paroxysmal facial pain precipitated from trigger areas or by trigger factors, and not associated with clinical evidence of neurological or sensory deficits or another disorder; 3) no previous surgical procedures for TN. Demographic and clinical details for patients were obtained via retrospective chart reviews (Table 3-1). Patients were age- and sex-matched to a cohort of twenty-two healthy pain-free control participants.

3.3.3 Imaging

All imaging was conducted with a 3 T GE Signa HDx MRI system fitted with an eight- channel phased array head coil. Scans of T1-weighted 3D FSPGR axial brain images were obtained from the top of the cranium to below the foramen magnum (0.9 × 0.9 × 0.9 mm3 voxels derived from a 256 × 256 matrix and field of view of 24 cm, echo time = 5 ms, repetition time = 12 ms, inversion time = 300 ms).

Chapter 3. Study I 51

Table 3-1 Demographic summary of the 21 right-sided TN patients included in this study. Pain distribution delineates the affected peripheral branches of the trigeminal nerve (V1: ophthalmic branch, V2: maxillary branch, V3: mandibular branch). Abbreviations: ACV: Anticonvulsant; CBZ: carbamazepine; PGB: pregabalin; GBP: Gabapentin; TCA: tricyclic antidepressant; BNZ: Benzodiazepine.

Pain Age at Age TN Pain Patient Sex Duration Pain Onset Medication (yrs) Side Distribution (yrs) (yrs) P1 M 46 R V2, V3 8 38 Ibuprofen P2 F 52 R V2, V3 10 42 ACV, SNRI P3 M 43 R V2, V3 2 41 CBZ, BNZ P4 F 61 R V1, V2, V3 4 57 CBZ, GBP GBP, BNZ, Baclofen, P5 F 40 R V1, V2, V3 9 31 Opioid P6 F 33 R V2, V3 4 29 GBP, PGB P7 F 38 R V3 6 32 CBZ P8 M 52 R V1 5 47 CBZ, ACV, Opioid P9 F 59 R V2, V3 4 55 CBZ, PGB P10 F 38 R V3 5 33 CBZ, PGB P11 F 67 R V3 1 67 GBP, Opioid P12 F 63 R V2 7 56 CBZ P13 M 61 R V1, V2 2 59 PGB P14 F 45 R V2, V3 2 43 None P15 F 47 R V1, V2, V3 3 44 CBZ, GBP P16 F 76 R V1, V2 3 73 CBZ P17 M 38 R V3 1 37 CBZ, PGB P18 M 23 R V3 3 20 CBZ P19 F 52 R V1, V2 3 49 CBZ P20 F 52 R V2, V3 2 50 CBZ P21 M 24 R V3 2 22 CBZ, TCA P22 M 38 R V2 2 36 CBZ

Chapter 3. Study I 52

3.3.4 Automated volumetric hippocampal segmentation

Volumetric segmentation was performed with the FreeSurfer 6.0 image analysis suite as previously described by the software developers (http://surfer.nmr.mgh.harvard.edu/) (Fischl 2012; Iglesias et al. 2015). In addition, we used the Hippocampal Subfields segmentation protocol built into FreeSurfer 6.0 which automatically segments 12 subfields of the hippocampal formation in each hemisphere (Fig. 3-1). The segmentation procedure is based on previously established ex-vivo histological segmentation with ultra-high-resolution MRI data. The reliability and validity of the FreeSurfer 6.0 hippocampal segmentation protocol has been previously demonstrated (Iglesias et al. 2015).

Figure 3-1 Representative images of FreeSurfer 6.0 automated hippocampal subfield segmentation in a control subject. Right two panels are 5× magnified of the left panel. A-E are coronal views. F is a sagittal view.

Chapter 3. Study I 53

3.3.5 Intracranial Volume Correction

The estimated total intracranial volume (eTIV) is calculated by Freesurfer upon registration of images to the MNI305 Talairach space, as previously described (Buckner et al. 2004). The volume of the hippocampal formation scales with head size, or total intracranial volume. Hippocampal subfield volumes are corrected for natural inter-subject variability in TIV. Based on previous work suggesting the advantages of the residual method compared with the proportion method of assessment of inter-subject variability, the former was used in the present project (Sanfilipo et al. 2004). We adjusted whole hippocampal volume and its subfields using the residual method with regression analysis using the following formula as previously described (Buckner et al. 2004):

VOIadj = VOI – b (eTIV – eTIVm)

Here, VOIadj is the adjusted volume of interest, VOI is the output volume of interest from FreeSurfer automated hippocampal segmentation, b is the slope of the VOI linear regression on eTIV, and the eTIVm is the sample mean of the eTIV. Only the slope of the healthy controls’

VOIs were calculated, and subsequently used to calculate the VOIadj for both R-TN subjects and controls. All reported volumes are adjusted. Additionally, subfield volume difference between R-TNs and controls are calculated as the VOIadj of R-TN - ipsilateral VOIadj of matched control for each subfield.

3.3.6 Manual volumetric hippocampal segmentation

Methods for manual hippocampal segmentation have been previously described in detail (Kulaga-Yoskovitz et al. 2015). Briefly, T1-weighted scans were processed as described above. The hippocampal subfields in five randomly selected R-TN subjects and their respective controls were manually segmented by a neuroanatomist (MV) ` 3D Display software, part of the MINC tools (www.bic.mni.mcgill.ca/ServicesSoftwareVisualization/). Segmented areas

Chapter 3. Study I 54

include 1) Subiculum, 2) cornu ammois 1 (CA1), CA2, and CA3 (CA1-CA2-CA3); and 3) CA4 and dentate gyrus (CA4-DG). The volume of the whole hippocampus was calculated as the sum of the 3 segments. Anatomical landmarks used to guide segmentation are previously described (Kulaga-Yoskovitz et al. 2015).

3.3.7 Statistical analysis

All statistical analyses were performed using GraphPad Prism version 7.0c for Mac, GraphPad Software, La Jolla, California, USA (www.graphpad.com), including: 1) student's t-test to compare mean age of R-TN subjects versus controls; 2) linear regression of left and right VOI over eTIV of healthy controls for ICV correction; 3) linear regression of left and right subfield volume difference over pain duration; 4) one-way ANOVA with matching,

Geisser-Greenhouse's correction, and Bonferroni's multiple comparison tests to analyze VOIadj of R-TN subjects versus controls; and 5) two-way ANOVA with Tukey's multiple comparison to analyze differences in VOIadj of R-TN subjects versus controls separated by sex (males and females). First-stage analysis compared R-TN group (right or left VOIadj) to their respective control group, and this was followed with Bonferroni's multiple comparison test correction. All the reported p-values are corrected for multiple comparisons and statistical analyses were determined significant if p < .05.

3.4 Results 3.4.1 Subject Demographics

The R-TN group had a mean age ± SD of 47.6 ± 13.5 years and was comprised of 8 males and 14 females who had a mean age of 40.6 ± 13.0 years and 51.6 ± 12.5 years respectively, that was not statistically different (p = 0.0635). Male and female subjects had a

Chapter 3. Study I 55

mean right-sided TN pain duration for 3.1 ± 2.3 years and 4.5 ± 2.7 years respectively (p = 0.2350), and an average pain onset at 37.5 ± 12.6 years and 47.2 ± 13.5 years respectively (p = 0.1131). All patients with the exception of one had pharmacological therapy at the time of imaging, the most common being Carbamazepine (CBZ). Patients were sex and age matched to a healthy control group with a mean age of 46.0 ± 11.6 years (14F: 49.0 ± 9.9; 8M: 40.8 ± 11.6). The age is not, that was not statistically different between control group and from the R- TN group (p = 0.6952). Patient demographic information is shown in Table 3-1.

3.4.2 Automated hippocampal subfield segmentation in R-TN subjects and matched controls

FreeSurfer 6.0 automated hippocampal segmentation protocol was successful in segmenting 12 regions of the left and right hippocampus in all R-TN subjects and matched controls, including the granule cell and molecular layer of the dentate gyrus (GC-ML-DG), CA1, CA2/CA3, CA4, subiculum, presubiculum, parasubiculum, molecular layer of hippocampus proper (ML-HP), fimbria, hippocampal tail, hippocampal fissure, and hippocampal-amygdala transition area (HATA) (Figure 3-1). Segmentation results were visually inspected for errors by assessing alignment of subfield masks with processed T1 images, however, no manual edits were required. The right whole hippocampus was significantly smaller in R-TN subjects compared to control (p = 0.0024) (Figure 3-2). The right whole hippocampus was significantly larger than the left whole hippocampus in the control but not the R-TN group (p = 0.0027) (Table 3-2, Figure 3-2). We found specific subfield changes in the right, left and bilateral hippocampi, as follows. Right subfield volume reduction compared to controls was seen in the following: GC-ML-DG (p = 0.0012), CA4 (p = 0.0046), CA1 (p = 0.0014), subiculum (p = 0.0289), presubiculum (p = 0.0367), ML-HP (p = 0.0033), and the HATA (p = 0.0052) (Table 3-2, Figure 3-3). Left subfields were significantly smaller in R-TN subjects compared to controls in GC-ML-DG (p = 0.0096), CA4 (p = 0.0204), CA1 (p = 0.0145), and ML-HP (p = 0.0196) (Figure 3.3).

Chapter 3. Study I 56

 4000 **

) 3000

(

e 2000

l o

V 1000

0 Control R-TN Control R-TN Left Left Right Right

Figure 3-2 Automated hippocampal segmentation showing reduced ipsilateral whole hippocampal volume in R-TN patients compared to matched controls. * designates significant intergroup differences (R-TN vs. controls). θ designates significant intragroup differences. * p < .05, ** p < .01, with same value for θ.

We also found specific asymmetries in the hippocampal subfields. Controls had a larger right subfield volume compared to the left side in the following 7 subfields: GC-ML-DG (p = 0.0053), CA4 (p = 0.0119), CA2/CA3 (p = 0.0007), CA1 (p = 0.0047), ML-HP (p = 0.0241), hippocampal tail (p = 0.0224), and HATA (p = 0.0045) (Table 3-3). In comparison, R-TN subjects had a larger right subfield volume compared to the left side in 3 of 12 subfields including the GC-ML-DG (p = 0.0153), CA4 (p = 0.0137), CA2/CA3 (p = 0.0034), and a larger left side presubiculum (p = 0.0017) (Table 3-3). Intergroup hippocampal volume abnormalities are reported in Figure 3-3 and Table 3-2. Whole hippocampus findings are stated in Figure 3- 2.

Chapter 3. Study I 57

Table 3-2 Summary of automated hippocampal segmentation in R-TN and control subjects.

(* p < .05, ** p < .01) Subfield volume difference calculated as: VOIadj of R-TN - ipsilateral VOIadj of matched control. Abbreviations: GC-ML-DG: granule cell and molecular layer of the dentate gyrus; CA: cornu ammonis; ML-HP: molecular layer of hippocampus proper; HATA: hippocampal amygdala transition area.

Mean Mean Volume Difference Post-hoc Subfield Side Volume R- Significance Control (mm3) (mm3) P-value TN (mm3) Whole R 3308.57 3676.00 -367.42 0.0024 ** Hippocampus L 3260.83 3529.70 -268.86 0.0557 R 291.06 329.98 -38.92 0.0012 ** GC-ML-DG L 277.90 313.62 -35.72 0.0096 ** R 252.04 281.29 -29.25 0.0046 ** CA4 L 240.07 268.42 -28.35 0.0204 * R 212.94 232.79 -19.84 0.0767 CA2/CA3 L 193.78 208.54 -14.76 0.3607 R 607.34 692.85 -85.51 0.0014 ** CA1 L 591.73 655.47 -63.73 0.0145 * R 401.66 440.86 -39.21 0.0289 * Subiculum L 409.81 439.00 -29.19 0.1641 R 270.94 297.07 -26.13 0.0367 * Presubiculum L 289.63 306.41 -16.78 0.4390 R 58.66 58.49 0.17 >0.9999 Parasubiculum L 63.02 58.28 4.74 0.7317 R 545.48 609.67 -64.19 0.0033 ** ML-HP L 535.61 587.12 -51.51 0.0196 * R 77.70 89.93 -12.24 0.2470 Fimbria L 75.57 85.95 -10.38 0.2734 Hippocampal R 535.45 579.08 -43.63 0.1963 Tail L 529.79 547.57 17.78 >0.9999 Hippocampal R 142.60 144.24 -1.64 >0.9999 Fissure L 139.73 134.68 5.05 >0.9999 R 55.31 63.98 -8.67 0.0052 ** HATA L 53.93 59.34 -5.41 0.1459

Chapter 3. Study I 58

Figure 3-3 Summary of automated hippocampal segmentation in 22 R-TN and matched control subjects. Right panels represent hippocampal segmentation. A-D are coronal views. F is a sagittal view. * p < .05, ** p < .01.

Chapter 3. Study I 59

3.4.3 Sex dependent differences in hippocampal subfield volumes

Female R-TN subjects had significantly smaller right and left whole hippocampal volume compared with female controls, however this change was not observed in males (Figure 3-4). Female R-TN subjects showed reduced right subfield volumes compared to female controls in the GC-ML-DG (p = 0.0060), CA4 (p = 0.0209), CA1 (p = 0.0120), ML- HP (p = 0.0114), and the HATA (p = 0.0076). Additionally, female R-TN subjects showed smaller left subfields compared to controls in the GC-ML-DG (p = 0.0159), CA4 (p = 0.0380), and ML-HP (p = 0.0459). In comparison, male R-TN subjects did not show significant subfield volume changes compared to male controls. The sole significant volume change between males and females was a reduction in the left presubiculum (p = 0.0490) in R-TN females compared to R-TN males. Subset analysis of hippocampal subfield volume by sex are shown in Figure 3-4.

3.4.4 Correlation of hippocampal subfields changes and pain duration

Linear regression performed on the subfield volume differences over the reported pain duration showed significant correlation between pain duration and amount of hippocampal volume reduction in right hippocampus (p = 0.0494), but not the left (Figure 3-5). The right CA1 (p = 0.0239), subiculum (p = 0.0218), ML-HP (p = 0.0261), and HATA (p = 0.0138), also demonstrated a significant correlation in volume reduction over time. Other subfields, including the GC-ML-DG and the CA4 showed a similar trend, but not statistically significant, towards reduction. Lastly, both the subiculum (p = 0.0258) and presubiculum (p = 0.0015) demonstrated correlation between left (contralateral) subfield reduction and pain duration.

Chapter 3. Study I 60

Table 3-3 Summary of automated hippocampal segmentation in left and right hemispheres in R- TN and control subjects.

(* p < .05, ** p < .01, *** p < .001). Subfield volume difference calculated as: VOIadj of ipsilateral (right) - VOIadj of contralateral (left). Abbreviations: GC-ML-DG: granule cell and molecular layer of the dentate gyrus; CA: cornu ammonis; ML-HP: molecular layer of hippocampus proper; HATA: hippocampal amygdala transition area.

Mean Volume Mean Difference Post-hoc Subfield Group Right-side Volume Left- Significance (mm3) P-value (mm3) side (mm3) Whole TN 3308.57 3260.83 47.74 0.5120 Hippocampus CL 3676.00 3529.70 146.30 0.0027 ** TN 291.06 277.90 13.16 0.0153 * GC-ML-DG CL 329.98 313.62 16.36 0.0053 ** TN 252.04 240.07 11.97 0.0137 * CA4 CL 281.29 268.42 12.87 0.0119 * TN 212.94 193.78 19.16 0.0034 ** CA2/CA3 CL 232.79 208.54 24.25 0.0007 *** TN 607.34 591.73 15.61 0.6206 CA1 CL 692.85 655.47 37.38 0.0047 ** TN 401.66 409.81 -8.15 0.7095 Subiculum CL 440.86 439.00 1.86 >0.9999 TN 270.94 289.63 -18.69 0.0017 ** Presubiculum CL 297.07 306.41 -9.34 0.4754 TN 58.66 63.02 -4.36 0.0842 Parasubiculum CL 58.49 58.28 0.21 >0.9999 TN 545.48 535.61 9.87 0.5087 ML-HP CL 609.67 587.12 22.55 0.0241 * TN 77.70 75.57 2.13 >0.9999 Fimbria CL 89.93 85.95 3.98 0.9141 Hippocampal TN 535.45 529.79 5.66 >0.9999 Tail CL 579.08 547.57 31.51 0.0224 * Hippocampal TN 142.60 139.73 2.87 >0.9999 Fissure CL 144.24 134.68 9.56 0.1074 TN 55.31 53.93 1.38 >0.9999 HATA CL 63.98 59.34 4.64 0.0045 **

Chapter 3. Study I 61

Whole Hippocampus Granule Cell & Molecular Layer of DG 4000 * ** 400 * ** Male Female

3000 300

)

(

2000 e 200

V V 1000 100

0 0 Control R-TN Control R-TN Control R-TN Control R-TN Left Left Right Right Left Left Right Right

CA4 CA1 * * 300 800 *

600

)

) 3

200 3

(

e 400

l o

100 o

V V 200

0 0 Control R-TN Control R-TN Control R-TN Control R-TN Left Left Right Right Left Left Right Right

Subiculum Presubiculum 500 400

400

300

)

3 m

300 m

(

e 200

u l

200 l

V V 100 100

0 0 Control R-TN Control R-TN Control R-TN Control R-TN Left Left Right Right Left Left Right Right

Molecular Layer Hippocampus Proper Hippocampal Amygdala Transition Area 800 80 * * **

600 60

)

(

400 e 40

V V 200 20

0 0 Control R-TN Control R-TN Control R-TN Control R-TN Left Left Right Right Left Left Right Right

Figure 3-4 Hippocampal subfield volumetric changes in R-TN patients. Automated hippocampal segmentation stratified by sex shows hippocampal subfield reduction in female R-TNs compared to matched controls. * designates significant intergroup differences (R-TN vs. controls). * p < .05, ** p < .01.

Chapter 3. Study I 62

Figure 3-5 Correlation between hippocampal subfield volume reduction and pain duration. Results of linear regression of pain duration and the volumetric differences between R-TN and matched controls. Subfield volume difference calculated as VOIadj in R-TN - ipsilateral VOIadj in controls. * p < .05.

Chapter 3. Study I 63

3.4.5 Manual hippocampal segmentation in R-TN subjects and controls

Manual hippocampal segmentation showed that the right whole hippocampus (p = 0.0337) and the right CA1-CA2-CA3 (p = 0.0166) subfield volume are significantly smaller in TN subjects compared to controls (Figure 3-6). A similar difference was seen when comparing the left whole hippocampus (p = 0.0236) and left CA1-CA2-CA3 (p = 0.0199) subfield volume in TN subjects and controls. There was a trend towards bilateral volume reduction in the CA4-DG and subiculum segmentations of TN subjects compared to controls, however these were not significantly different. Manual segmentation findings are summarized in Table 3-4.

Figure 3-6 Manual hippocampal segmentation in 5 R-TNs and matched controls. Manual hippocampal segmentation shows volumetric reduction in the whole hippocampus as well as hippocampal subfields in R-TN patients compared to matched controls. * designates significant intergroup differences (R-TN vs. controls). * p < .05.

Chapter 3. Study I 64

Table 3-4 Summary of manual hippocampal segmentation in R-TN and their matched controls.

(* p < .05). Subfield volume difference calculated as: VOIadj of R-TN - ipsilateral VOIadj of matched control. Abbreviations: DG: dentate gyrus; CA: cornu ammonis.

Mean Mean Volume Difference Post-hoc Subfield Side Volume R- Significance Control (mm3) (mm3) P-value TN (mm3) Whole R 2757.4 3445 -687.6 0.0337 * Hippocampus L 2699 3425.6 -726.6 0.0236 * R 336.8 408.4 -71.6 0.3240 CA4-DG L 345.4 413.8 -68.4 0.3768 CA1-CA2- R 1600 1997 -397 0.0166 * CA3 L 1503.8 1919.4 -415.6 0.0119 * R 820.6 1039.6 -219 0.2788 Subiculum L 849.8 1092.4 -242.6 0.1875

3.5 Discussion

There have been increasing reports examining the role of the CNS in contributing or maintaining TN pain (DeSouza et al. 2013; Tohyama et al. 2018; Zhong et al. 2018). While these reports have primarily focused on white matter and neocortical structures, hippocampal abnormalities have not been linked to TN pain before. Yet TN is an excellent model for the study of the effect of neuropathic pain on the hippocampus, given its strictly unilateral representation of pain, as well as severity, leaving virtually no ambiguity as to the severity of the pain (Love and Coakham 2001). Using TN as a model of neuropathic pain, our current study demonstrates significant changes in the hippocampus and its subregions. Specifically, we observe ipsilateral hippocampal whole and subregional volume reduction when compared with a cohort of healthy controls. The reduction in hippocampal subregions is further associated with duration of pain as well as sex, highlighting sex specific hippocampal plasticity in TN.

Chapter 3. Study I 65

3.5.1 Hippocampal subfield volume reductions in R-TN subjects correlate with CNS circuits involved in pain processing

The hippocampus is composed of cytoarchitecturally and functionally distinct subfields with important roles such as the cognitive-affective processing of pain (Bushnell, Čeko, and Low 2013; Duvernoy et al. 2005; Simons, Elman, and Borsook 2014). Reductions in hippocampal GM has previously been reported in other chronic pain diseases (Cauda et al. 2014), and recently in TN (Hayes et al. 2017). Considering the complex organization of the hippocampus and its varied functions, treating the entire structure of the hippocampus as a single volume likely ignores critical information now obtainable through MRI volumetric analysis techniques.

Previous studies have delineated the hippocampal afferent and efferent pathways involved in pain processing (for a detailed review please see Liu & Chen, 2009) (M. G. Liu and Chen 2009). Afferents from the entorhinal cortex (EC) via the perforant path are composed of two distinct inputs. The first arises from layer II EC neurons that synapse on DG dendrites and input into the trisynaptic circuit (Dolorfo and Amaral 1998). The second input, called the temporoammonic path, is comprised of layer II and III EC neurons that synapse directly on the distal dendrites of the CA1 and subiculum, and CA3, respectively (Empson and Heinemann 1995; Köhler 1985; Steward 1976; Witter et al. 1988). We demonstrate that subfields directly innervated by the perforant path, including the DG, CA1, and subiculum, have reduced volume in TN. Interestingly, the CA2/CA3 volume is not reduced, which suggests the EC could relay pain stimuli preferentially through projections that input into the CA1, DG, and subiculum. These findings are in contrast with a study by Ezzati et al. 2014 (Ezzati et al. 2014), who report that older female subjects with chronic pain had smaller right CA2-CA3 and CA4-DG volumes. However, this study did not assess chronic pain from TN, and used an earlier version of FreeSurfer hippocampal segmentation with inferior accuracy (Iglesias et al. 2015; Schoene- Bake et al. 2014).

Chapter 3. Study I 66

Additional circuits in pain processing may provide afferents to the EC or directly to the hippocampal formation (M. G. Liu and Chen 2009). For instance, the Papez circuit, which contributes to emotional expression, connects the hypothalamus (mammillary bodies), anterior thalamic nuclei, cingulate cortex, and the hippocampus (Papez 1937). Within this circuit, the anterior cingulate cortex (ACC) projects fibers directly to the subiculum and the EC (Henke 1982). Our finding of reduced volume of the ipsilateral subiculum, presubiculum, and the subfields associated with perforant path inputs, align with this circuit. Additionally, this builds upon our previous findings of GM changes in affective circuits in TN subjects (Desouza, Hodaie, and Davis 2014; Hayes et al. 2017).

Hippocampal outputs occur through two major pathways; the dorsal pathway involving the fimbria-fornix system, and the ventral pathway which connects the hippocampal formation and EC (M. G. Liu and Chen 2009). Fibers of the fornix originate mainly from the CA1, whereas fibers of the fimbria originate in CA2, CA3, CA4 and the subicular complex (Meibach and Siegel 1977; Swanson and Cowan 1977). In TN subjects, the fimbria volume is unchanged, despite significant volume reduction of the CA4 and subiculum. This builds upon our prior work analyzing white matter changes with diffusion tensor imaging tractography in TN subjects where we found no changes associated with the structure of the fornix.

3.5.2 Bilateral hippocampal subfield reductions in R-TN female subjects

Female R-TN subjects have bilateral volume reduction in the GC-ML-DG, CA4, ML- HP, and whole hippocampus (Fig. 3.4). We have previously reported that bilateral hippocampal volume reduction occurs in patients with right-sided or left-sided TN, without stratifying by sex (Hayes et al. 2017). Currently, evidence conflicts as to whether chronic pain disorders produce bilateral (Cauda et al. 2014; Mutso et al. 2012), or unilateral (Ezzati et al. 2014) hippocampal volume reduction, with a similar discrepancy in animal studies (Belcheva

Chapter 3. Study I 67

et al. 2009; Mutso et al. 2012). Although TN produces ipsilateral pain symptoms, nociceptive inputs quickly cross the brainstem and present bilaterally (Dick and Rashiq 2007). Our results show subfield volume reductions of greater significance ipsilaterally vs. contralaterally (Fig. 3.2), which coincides with the laterality of TN pain experience.

Chronic pain can lead to the development of a maladaptive stress and systemic hormonal changes via the hypothalamic–pituitary–adrenal (HPA) axis (McEwen and Kalia 2010b). The hippocampus regulates the HPA axis through feedback via mineralocorticoid and glucocorticoid receptors concentrated in the dentate gyrus (Galea et al. 2013). Recent evidence shows that elevated levels of cortisol through a maladaptive stress response in chronic pain is associated with smaller hippocampal volumes bilaterally (Vachon-Presseau et al. 2013). This may be another mechanism by which TN produces bilateral hippocampal subfield volume changes. Additionally, animal studies suggest that stress influences hippocampal neural plasticity differently in females compared to males (Galea et al. 2013), and sex hormones may explain differences in the hippocampal responses to aversive stimuli (Aloisi, Ceccarelli, and Herdegen 2000). Hormonal differences may contribute hippocampal subfield changes that are limited to female R-TN patients (Fig. 3.4). This finding supports a previous report demonstrating sex specific hippocampal volume reduction in chronic pain (Ezzati et al. 2014).

3.5.3 Aberrant neurogenesis as the substrate for volume loss in hippocampal subfields

GM volume reduction in the CNS as a result of chronic pain may manifest through changes in various substrates, including neuronal or glial turnover. A mechanism gaining increasing attention is the role of adult hippocampal neurogenesis (AHN). Disrupted AHN is associated with learning and memory deficits, and mood disorders. Depression and anxiety are highly comorbid with chronic pain (Gerrits et al. 2015), and patients often demonstrate learning and memory deficits (Dick and Rashiq 2007). Apkarian et al. (Apkarian et al. 2017)

Chapter 3. Study I 68

demonstrated that AHN disruption in mice diminished persistent pain, while mice with AHN upregulation had prolonged persistent pain. Additionally, other studies reported decreased AHN in rodent models of chronic pain (Mutso et al. 2012). Thus, it has been proposed that downregulation of neurogenesis in chronic pain may serve to reduce pain-related memory formation as a self-protective mechanism (Zheng, Yi, and Wan 2016). Interestingly, we show that TN patients have bilateral volume reduction in the GC-ML-DG (Fig. 2), the primary location of AHN. It is possible that TN patients have aberrant AHN, which could contribute to volume reduction and maintenance of chronic pain. Vachon-Presseau et al. support this notion, suggesting that in patients with chronic back pain, elevated cortisol levels due to a maladaptive stress response may alter hippocampal circuitry via aberrant neurogenesis (Vachon-Presseau et al. 2013).

In agreement with others (Blankstein et al. 2010; Moayedi et al. 2011), we also demonstrate that GM volume reduction in R-TN subjects correlates with pain duration, specifically in the ipsilateral CA1, subiculum, ML-HP, HATA, and the whole hippocampus (Fig. 5). This supports the role of the CA1 and subiculum in pain processing (M. G. Liu and Chen 2009), and the notion that chronic pain in the form of repetitive pain attacks can drive neuroplasticity (Teutsch et al. 2008). However, in the context of neurogenesis, we did not observe a similar correlation in the GC-ML-DG (although there was a trend of p = .0673). Although granule cells do not account for the entire DG structure, it is however plausible that a chronically reduced rate of neurogenesis could reach a steady state and stable DG volume over time. Future studies are required to delineate the role of AHN in chronic pain.

3.5.4 Study limitations

Our study utilizes FreeSurfer's hippocampal subfields segmentation protocol to investigate the effect of the neuropathic chronic pain in trigeminal neuralgia patients. Previous studies have reported hippocampal volumetric changes in chronic pain, in agreement with

Chapter 3. Study I 69

findings reported in this aspect of our current study (Apkarian et al. 2017; Mutso et al. 2012; Romero-Grimaldi et al. 2015). Nonetheless, the interpretation of these findings, particularly the male alone cohort, may be limited by the sample size. Additionally, most TN patients were undergoing pharmacological therapy for TN, often with anticonvulsants such as carbamazepine (Table 3.1). A recent study suggests that chronic administration of gabapentin and carbamazepine may cause increase in neurodegenerative changes in the brain of animal models (Olaibi, Osuntokun, and Lijomone 2014). Furthermore, long-term use of antiepileptics in patients with temporal lobe epilepsy results in reduced hippocampal betweenness centrality (a measure of connectivity) (Haneef, Levin, and Chiang 2015). Although the aforementioned studies suggest that anticonvulsants may affect the hippocampal neuronal circuits, however, the direct effect of these medications on the hippocampus has not been previously studied and further investigation is required. Given the severity of TN pain, it is also not tenable to study a medication free patient cohort and the population investigated in our study therefore reflects the typical TN population.

3.6 Conclusions

Our results support our hypothesis of selective alterations to hippocampal GM in TN patients, with associated effects based on sex and pain duration. How these changes arise may be due to the distinct cytoarchitecture, and functions of hippocampal subfields. Pain duration can enhance stress and trigger alterations in affect-related circuitry, involving specific hippocampal subfields. This study contributes to the increasing body of evidence suggesting hippocampal involvement in pain modulation and future studies should be aimed at elucidating the potential dynamic nature of the structural changes in the hippocampus in chronic pain. Additionally, TN as a distinctive form of neuropathic facial pain with high pain severity should be considered as a unique model in investigating the role of the hippocampus in pain modulation.

Chapter 4 Study II: Pain relief normalizes hippocampal abnormalities in trigeminal neuralgia

4.1 Abstract

Memory complaints, poor performance on memory and cognitive tests, anxiety- and depression-related disorders are far too common in chronic pain patients to be overlooked. Recent evidence has suggested convergence between chronic pain and memory problems onto the hippocampus. The hippocampus, canonically known for its role in memory, is also an important structure in the limbic system. It consists of heterogenous subfields involved in various roles including behavior regulation, stress modulation, and pain perception. Hippocampal morphological changes including neurogenesis dysregulation and selective subfield volume reduction have been reported in chronic pain patients. However, the effect of pain relief on hippocampal abnormalities remain elusive because complete pain resolution is rarely achieved in chronic pain conditions. Yet, TN provides us with a unique opportunity to investigate the effect of pain relief. TN is a chronic orofacial pain disorder affecting the trigeminal nerve and is highly amenable to surgical interventions. As such, our current study investigated for the first time the effect of pain relief on hippocampal subfields structure. Anatomical MR images of 61 TN patients were examined before and 6 months after surgical intervention. We show that in 47 patients, who experienced pain resolution after the surgery, overall hippocampal volume abnormalities are normalized. Additionally, hippocampal subregions involved in memory consolidation and neurogenesis, including CA1, CA4 and dentate gyrus, significantly increase in size after pain relief. These volumetric changes indicate that hippocampal volume is dynamic and responsive to changes in chronic pain conditions. Chapter 4. Study II 71

4.2 Introduction

Pain processing adversely affects cognitive performance and chronic pain significantly impacts quality of life (Loeser and Melzack 1999; Mazza, Frot, and Rey 2018). Patients who suffer from chronic pain experience poor memory and concentration, often accompanied by increased anxiety and depression (Mazza, Frot, and Rey 2018; Vachon-Presseau et al. 2013; McCarberg and Peppin 2019; De Heer et al. 2014; Gureje et al. 2008; Sjogren et al. 2005; Park et al. 2001; J. Grisart, Van Der Linden, and Masquelier 2002; Ling et al. 2007; Mifflin, Chorney, and Dick 2016; Schnurr and MacDonald 1995; Bair et al. 2003; Romero-Grimaldi et al. 2015). The hippocampal formation consists of functionally distinct subfields including subiculum, CA1 – CA4 and DG. This subcortical region plays a significant role in memory formation (Knierim 2015), emotional processing (Wingenfeld and Wolf 2014), and modulating stress (Wingenfeld and Wolf 2014). In particular, prolonged exposure to stress, similar to chronic neuropathic pain conditions that can act as chronic stressors, have adverse effects on memory, and this has been related to blunted hippocampal plasticity (E. J. Kim, Pellman, and Kim 2015; J. J. Kim et al. 2007; O’Keefe and Dostrovsky 1971; J. J. Kim and Diamond 2002; Shors 2006). Specifically, microenvironmental changes imposed by neuroendocrine hormones synthesized and secreted by the HPA axis (Eisch and Petrik 2012) suppress plasticity. Similarly, previous studies have reported hippocampal changes in chronic pain conditions and have reported microstructural changes in its subregion (Vaculik et al. 2019; Mansour et al. 2014; Duric and McCarson 2006; Ezzati et al. 2019, 2014). Notably, studies using rodent models of neuropathic pain have shown that the painful nerve injury is related to alterations in hippocampal gene expression profiles and blunted neurogenesis (Romero-Grimaldi et al. 2015; Apkarian et al. 2017; Duric and McCarson 2006; Mutso et al. 2012).

Hippocampal volumetric abnormalities have also been reported in different chronic pain conditions, including TN (Hayes et al. 2017; Mutso et al. 2012). TN is a debilitating chronic

Chapter 4. Study II 72

neuropathic facial pain related to the trigeminal nerve root at the level of the pons (M Heir and Eliav 2008; Zakrzewska and Linskey 2014). TN disorder is characterized by intense electric- like pain episodes (Hodaie and Coello 2013; Leclercq, Thiebaut, and Héran 2013; D. Q. Chen et al. 2016; M Heir and Eliav 2008) and has several unique features that distinguish it as an ideal model for study of chronic pain: TN has largely unilateral symptomatology; is severe in its nature; and is not associated with other sensory deficits, such as numbness, observed in other chronic pain disorders. Using TN as a model, our group recently investigated the impact of chronic pain on hippocampal subfields in neuropathic pain (Vaculik et al. 2019). We reported volumetric reduction in some hippocampal subfields—with changes being positively related with the pain duration (Vaculik et al. 2019).

Other studies have also delineated the effect of chronic pain on the hippocampus and its subfields (Romero-Grimaldi et al. 2015; Mutso et al. 2014, 2012; Apkarian et al. 2017), however whether pain relief alters hippocampal structure remains unclear. This is not surprising, since most chronic pain syndromes do not completely resolve after surgical intervention. TN, in contrast, provides an excellent model to investigate the effects of pain on hippocampal volume, as interventions such as GKRS are highly effective and often lead to for complete pain relief in TN patients (Kondziolka et al. 2010; Regis et al. 2016; Martínez Moreno et al. 2016). Therefore, we can investigate the abnormalities in during TN pain, and how these change in pain relief.

Here, we aim to investigate the structure of the hippocampus and its subfields in TN patients before and after undergoing surgery, and determine the effect of pain relief on these structures. We hypothesize that pain relief leads to an overall increase in hippocampal volume, and normalizes the abnormalities observed previously (Vaculik et al. 2019). Furthermore, as neurogenesis is negatively affected in chronic pain conditions (Eisch and Petrik 2012; Apkarian et al. 2017), we further hypothesize that pain relief will affect subfields important in

Chapter 4. Study II 73

neurogenesis, such as DG and CA4. For this goal, we plan to investigate structural MRI of TN patients pre and post pain relief. Considering the sex differences in hippocampal neurogenesis, stress physiology, and hippocampal subfields in TN patients (Bale and Epperson 2015; Yagi and Galea 2019; Hillerer et al. 2013a; Falconer and Galea 2003; Naninck et al. 2015; Vaculik et al. 2019), we additionally hypothesize that there are sex difference in the effect of pain relief in TN patients.

4.3 Methods 4.3.1 Participants

4.3.1.1 TN Patients

This retrospective study was approved by the UHN ethics board. A total of 61 patients were included in this study who were treated at Toronto Western Hospital in Canada. Patients in this study met the following criteria: I) diagnosis of classical TN; II) GKRS treatment with no prior surgical intervention for TN; III) structural MRI of the brain prior to and 6 months after GKRS; IV) clinical follow-up 6 months after surgery. Patients with neurodegenerative disorders, TN secondary to multiple sclerosis, stroke, other chronic pain conditions, cranial tumors, and other neurological diseases were excluded from this study.

Images acquisition All T1-weighted images of TN patients were acquired with a 3 Tesla GE Signa HDx MRI scanner (General Electric, Boston, MA) fitted with an 8-channel head coil (fast-spoiled gradient echo, TE = 5.1 ms, TR = 12.0 ms, flip angle = 20°, voxel size = 0.86 mm × 0.86 mm × 1.00 mm, 256 × 256 matrix, field of view = 22 cm, 146 slices). It should be noted that TN patients scheduled for GKRS are usually scanned on the day of surgery. These images are used to guide the stereotactic surgery. However, in some cases, due to limited scanner time availability, some scans only captured subcortical regions of interest. In these cases, all

Chapter 4. Study II 74

subcortical regions, including the entire hippocampus was capture, and some cortical regions were lost.

4.3.1.2 Healthy participants - Cam-CAN

We have previously shown hippocampal abnormalities in TN compared to healthy controls(Vaculik et al. 2019). To assess whether hippocampal abnormalities are normalized after pain relief, 61 neurologically healthy individuals from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) dataset (Shafto et al. 2014) were used as age- and sex-matched controls (age difference < 2 years ). Exclusion criteria included: (1) depression, and (2) any report of pain. The ipsi- and contralateral side for healthy individuals were determined based on their matched TN subjects: for example, if a healthy subject matched to a right TN patient, the right hemisphere is marked as ipsilateral. We use Cam-CAN dataset instead of healthy controls collected on site as we were not able to sex- and age-match all TN patients to our healthy control cohort.

Images acquisition All T1-weighted images of subjects from the Cam-CAN dataset were acquired with a 3 Tesla SIEMENS MAGNETOM TrioTim syngo MR B17 32-channel head coil (fast-spoiled gradient echo, TE = 2.99 ms, TR = 2250 ms, flip angle = 9°, voxel size = 1.0 mm isotropic, 256x240 matrix, field of view =25.6 cm, 192 slices).

4.3.1.3 Healthy controls validation

In order to validate our approach to include Cam-CAN subjects in our analyses, we compared 76 healthy controls with T1 anatomical scans collected at Toronto Western Hospital and 76 age- and sex-matched (age difference < 1 year) neurologically healthy individuals from the Cam-CAN database. Both groups underwent the same brain segmentation, parcellation, and hippocampal subfield segmentation using FreeSurfer 6.0. The volumetric results were compared at group level using Wilcoxon test as well as Bayesian Estimation Supersedes the t-

Chapter 4. Study II 75

test (BEST) test (Kruschke 2013). All p-values > 0.05 in the Wilcoxon tests of the hippocampus and its subfields comparing the two groups. Additionally, the 95% Highest Density Interval (HDI) of true difference in means included zero in all BESTs tests. As such, we showed that none of the studied brain regions nor hippocampal subregions are statistically different between the examined groups. Therefore, these two datasets, collected with different scanning protocols on different scanners, were not statistically different at the group level when comparing volumetric segmentations.

4.3.2 Automated subcortical segmentation

FreeSurfer 6.0 (https://surfer.nmr.mgh.harvard.edu/) was employed for subcortical segmentation (Fischl 2012) (including hippocampus and amygdala). Additionally, we used the Hippocampal Subfields segmentation (Iglesias et al. 2015) protocol to automatically extract the volumetric values from 12 hippocampal subfields. Given recent evidence suggesting that the hippocampus has functionally meaningful subregions along its longitudinal axis (Poppenk et al. 2013; Adnan et al. 2016; Strange et al. 2014; Ayoub et al. 2019), we evaluated the volume of the head, body and tail of the hippocampus using the FreeSurfer developmental package (Saygin et al. 2017). It should be noted that the TN subjects who did not have the whole brain MRI correctly underwent the subcortical segmentation stream in FreeSurfer and results were individually inspected for accuracy.

4.3.3 Surgical intervention and treatment responses

All patients underwent GKRS at Toronto Western Hospital, using an Elekta Perfexion system utilizing 4 mm collimators. One single 80 Gy radiation isodose was delivered to the cisternal segment of the symptomatic trigeminal nerve. To minimize the radiation effects, brainstem radiation was restricted to 15 Gy/mm3.

Chapter 4. Study II 76

Pain intensity and clinical outcomes were assessed before surgery, and at a 6-month post- treatment follow-up visit. Pain intensity was measured using two instruments: a Numeric Rating Scale (NRS) (Rodriguez 2001; Jensen and McFarland 1993) and the Barrow Neurological Institute (BNI) scale (Rogers et al. 2000). The NRS was an 11-point scale, rated between 0 and 10, with the anchors: 0=no pain and 10=the worst imaginable pain. The BNI scale comprises five categories of pain for TN: class I–no trigeminal pain, no medication; class II–occasional pain, no medication; class III–some pain, adequately controlled with medication; class IV–some pain, not adequately controlled with medication; and class V–severe pain, no pain relief. In accordance to the previous literature (Li et al. 2004; Hung et al. 2019; Tohyama et al. 2018), patients who achieved either at least 75% reduction in pain (or complete pain resolution) and BNI score of I-III at follow-up were classified as responders; whereas those who achieved less than 25% pain improvement and BNI score of IV-V were classified as non- responders. Patients who fulfilled only one of the criteria mentioned above were reviewed in detail by a neurosurgeon (M.H.) to assess their treatment response. All TN subject demographics are summarized in Table 4-1.

4.3.4 Subcortical volume correction

To account for head size differences in our participants, we employed the residual approach explained by Buckner et al.(Buckner et al. 2004). Given that some participants did not have whole brain MRI scans, we normalized the volume of structures of interest using subcortical grey volume (SGV). As previously described (Buckner et al. 2004; Sanfilipo et al. 2004; Vaculik et al. 2019), we adjusted whole hippocampal volume using the residual method with the following formula:

VOIadj = VOI – b(SGV – SGVmean)

Chapter 4. Study II 77

Where VOIadj is the adjusted volume of interest, VOI is the output volume from the FreeSurfer pipeline, b is the slope of the linear regression between VOI and on SGV, and the

SGVmean is the sample mean of the SGV. To account for possible structural abnormalities in TN subjects, we only calculated the regression slope of the healthy controls' VOIs, and subsequently used to calculate the VOIadj for both TN subjects and controls. As such, this approach normalizes the hippocampal and amygdala volume by removing the influence of the subcortical grey volume. All reported volumes are adjusted with this method.

4.3.5 Volumetric percent change after surgery

To assess the effects of pain relief in TN on hippocampal volumes, we additionally calculated the percentage of volumetric change in each VOI using the following formula:

VOIchange = [(VOIpost-treatment – VOIpre-treatment)/VOIpre-treatment] X 100

Where VOIchange is the volumetric percent change after the surgery compared to pre- surgery time point (no change baseline).

4.3.6 Statistical Analysis

All statistical analyses were conducted in R 3.5.1 (R Core Team 2018). The non- parametric Wilcoxon test was used in our analyses for data that were not normally distributed, such as the percent of volumetric change after surgery across hippocampal subregions. The statistical analyses include

I) Student's t-test to compare mean age of TN subjects and healthy controls.

II) To assess whether hippocampal volumetric abnormalities are normalized after pain relief, we used Mann-Whitney U Test(McKnight and Najab 2010) to compare the corrected volumetric results in TN subjects to the healthy controls.

Chapter 4. Study II 78

III) To assess the effect of pain relief, we used Wilcoxon signed-rank test to compare the volumetric percent change after treatment to pre-treatment time point (no change baseline).

IV) To determine sex difference in hippocampal changes after pain relief, we used Wilcoxon signed-rank test to compare the volumetric percent change in males and females.

All the reported p-values are corrected for multiple comparisons using Bonferroni's test with statistical analyses determined significant if p < 0.05.

4.4 Results 4.4.1 Subject demographics

A total of 61 classical TN patients were included in this study (36F, 25M). All patients experienced unilateral pain (26L, 35R). All patients underwent GKRS as their first surgical treatment. The average pain duration prior to surgical intervention was 9.25 ± 1.79 (mean ± SD, NRS scale). The average age at the time of surgery is 64.9 ± 12.0 years (F: 66.8 ± 10.1; M: 62.0 ± 14.1). Age was not statistically different between males and females (P=0.14). The healthy cohort selected from the Cam-CAN dataset is 64.8 ± 12.1 years old (36F: 66.8 ± 10.1; 25M: 62.0 ± 14.2 years old). The age was not statistically different between the healthy and TN cohort (P=0.99). Patient demographic information is depicted in Table 4-1.

Table 4-1 Demographic summary of the TN patients included in this study.

Laterality delineates the affected side. Distribution indicates the affected peripheral branches of the trigeminal nerve with (V1: ophthalmic branch; V2: maxillary branch; V3: mandibular branch). NRS corresponds to the 0-10 Numeric Rating Scale (0: no pain; 10: worst imaginable pain). BNI is Barrow Neurological Institute scale (lass I: no trigeminal pain, no medication; class II: occasional pain, no medication; class III: some pain, adequately controlled with medication; class IV: some pain, not adequately controlled with medication; class V: severe pain, no pain relief). Pain duration is the years

Chapter 4. Study II 79

between pain onset and the surgery date. Groups are based on the pain relief and BNI scale 6 months after the surgical intervention (Resp: responders; Non-Resp: non-responders).

ID Sex Age Laterality Distribution NRS BNI Pain Group Pre Post Pre Post Duration (years) TN1 M 59 Right V2, V3 10 0 V III 3 Resp TN2 M 79 Left V2, V3 10 3 V III 10 Resp TN3 M 70 Left V1, V2, V3 10 3 IV III NA Resp TN4 M 53 Left V2 10 0 IV I 21 Resp TN5 M 71 Right V2, V3 10 0 V I 12 Resp TN6 M 58 Right V2 10 0 IV I 3 Resp TN7 M 63 Right V3 10 0 V III NA Resp TN8 M 31 Left V2 10 0 IV III 2 Resp TN9 M 66 Left V3 10 0 V III 5 Resp TN10 M 40 Right V2, V3 10 0 IV III 2.5 Resp TN11 M 63 Left V2, V3 7 0 NA I 3 Resp TN12 M 84 Right V3 5 0 IV I NA Resp TN13 M 72 Right V1, V2 10 0 NA III 40 Resp TN14 M 62 Right V2, V3 NA 0 NA I 9 Resp TN15 M 61 Right V1, V2 NA 0 NA I 20 Resp TN16 M 38 Right V3 NA 0 NA III 1.5 Resp TN17 M 73 Left V1, V2, V3 NA 0 NA I 1 Resp TN18 M 73 Right V2, V3 8 2 V III 2.5 Resp TN19 M 43 Left V2 10 2 IV III 1 Resp TN20 F 82 Right V2, V3 8 3 III III NA Resp TN21 F 69 Left V2, V3 10 3 IV III NA Resp TN22 F 65 Right V1, V2, V3 10 3 V III 30 Resp TN23 F 72 Left V2 0 0 III I 3 Resp TN24 F 70 Right V1 8 0 IV I 6.5 Resp TN25 F 74 Right V3 10 0 V I 2.5 Resp TN26 F 56 Left V3 10 0 IV III 4 Resp TN27 F 79 Right V2 10 0 V III 3 Resp TN28 F 79 Left V3 10 0 NA III 2 Resp TN29 F 60 Right V2, V3 10 0 IV II 1.5 Resp TN30 F 67 Left V3 10 0 V I 3 Resp TN31 F 49 Left V1, V2, V3 10 0 V I 3 Resp TN32 F 46 Right V2 10 0 IV III 4 Resp TN33 F 55 Right V2 10 0 V I 1.5 Resp TN34 F 71 Left V1, V2, V3 8 0 IV III 2 Resp TN35 F 68 Right V1, V2 10 0 IV III 16 Resp TN36 F 61 Right V1, V2, V3 10 0 V II 7 Resp TN37 F 63 Right V2, V3 8 0 NA II NA Resp TN38 F 76 Right V1, V2, V3 8 0 IV II 7 Resp TN39 F 71 Left V2, V3 NA 0 NA III 15 Resp TN40 F 70 Left V2, V3 NA 0 NA II 6 Resp TN41 F 79 Left V2 NA 0 IV I NA Resp TN42 F 79 Right V3 8 1 IV II 3 Resp TN43 F 74 Right V2, V3 10 1 IV III 8 Resp

Chapter 4. Study II 80

TN44 F 70 Left V2, V3 10 2 NA III NA Resp TN45 F 66 Left V3 NA 0 NA III 2 Resp TN46 F 68 Right V2, V3 NA 0 NA III NA Resp TN47 F 49 Left NA NA 0 NA III NA Resp TN48 M 78 Right NA 10 4 IV IV 8 Non-Resp TN49 M 63 Left V3 10 4 IV IV 4 Non-Resp TN50 M 65 Left V3 5 6 IV IV 4 Non-Resp TN51 M 73 Right V2 10 7 IV IV 3 Non-Resp TN52 M 59 Right V2 10 8 V IV 12 Non-Resp TN53 M 38 Left V1, V2 10 9 V V 1 Non-Resp TN54 F 58 Right V1, V2, V3 10 3 IV III 3 Non-Resp TN55 F 81 Right V2 10 3 IV III 10 Non-Resp TN56 F 65 Left V3 10 4 V IV 7 Non-Resp TN57 F 71 Right V2, V3 10 4 V IV 1 Non-Resp TN58 F 68 Left V2, V3 9 6 IV V 1 Non-Resp TN59 F 59 Right V2, V3 10 6 V IV 2 Non-Resp TN60 F 52 Right V2, V3 10 6 IV IV 5 Non-Resp TN61 F 46 Right V1, V2, V3 10 NA NA IV 4 Non-Resp

4.4.2 Pain relief increases hippocampal volume

The FreeSurfer 6.0 automated protocol delineated the volumetric values for the hippocampus. The change in hippocampal volume after surgery determined for responders and non-responders, and evaluated based on pain laterality (i.e., ipsilateral referring to the reported pain and surgical side) (see Fig 4-1). In the responder group, the whole hippocampus volume increase post-treatment compared to pre-treatment was 3.23% ± 4.12 and 3.47% ± 4.28 on the ipsi- and contralateral side, respectively. These changes were statistically different from no change compared to pre-treatment (pipsilateral < 0.001; pcontralateral <0.001). In the non-responder group, the changes in the ipsi and contralateral side were not statistically different from pre- treatment baseline (Pipsilateral = 0.067; Pcontralateral = 0.095).

Chapter 4. Study II 81

Figure 4-1 Hippocampal volumetric changes after treatment.

Y-axis depicts percent of volume changes calculated as: VOIchange = [(VOIpost-treatment – VOIpre- treatment)/VOIpre-treatment] X 100. Results are compared to pre-treatment values using Wilcoxon test. Volumetric results show that the whole hippocampus increased bilaterally in TN responders but not the non-responders 6 months after GKRS. 4.4.3 Pain relief normalizes the hippocampal abnormalities

We utilized the Cam-CAN database to normalize and compared our TN patients to healthy individuals. As the number of subjects in the non-responder cohort is limited, we focused on our aim to study the effect of pain by analyzing only the responder cohort. We

Chapter 4. Study II 82

showed that the responder cohort has significantly smaller ispi and contralateral hippocampus compared to healthy individuals (pipsilateral = 0.021 pcontralateral < 0.001). Six months after the surgical intervention, which was followed by pain relief, the responder cohort showed no significant differences in the whole hippocampus (Pipsilateral = 0.021 pcontralateral = 0.508). The ipsi and contralateral hippocampus are not asymmetric in either groups, prior or after surgery (all p = 1). Results are summarized in Fig 4-2.

Figure 4-2 Automated hippocampal segmentation for 47 TN responders and their age- and sex- matched healthy controls.

Automated hippocampal segmentation for 47 TN responders and their age- and sex-matched healthy controls. Results indicate bilateral volume reduction in TN patients prior to the surgery which are normalized after pain relief. No asymmetry was observed in ipsi- and contra-lateral side of the hippocampus. P-values are corrected for multiple comparison using Bonferroni correction (* p < 0.05, *** p < 0.001).

Chapter 4. Study II 83

4.4.4 Hippocampal subfields increase significantly after pain relief

In the responder cohort, the CA1, CA2/3, CA4, granule cell layer of dentate gyrus (GC DG), and subiculum showed significant bilateral changes compared to prior to the treatment. Similarly, in the axial subregions, head and body showed significant bilateral changes compared to the baseline. However, the pre-subiculum, para-subiculum, and tail subregions did not show significant changes after pain relief. Results are summarized in Table 4-2 and Fig 4-3.

Table 4-2 Summary of hippocampal subfield changes after surgical intervention in the responder cohort.

Subfield volume changes are calculated as: VOIchange = [(VOIpost-treatment – VOIpre-treatment)/VOIpre-treatment] X 100. Wilcoxon test is used for statistical analyses and p-values are corrected for multiple comparison using Bonferroni correction. (* p < 0.05, ** p < 0.01, *** p < 0.001).

Subfield Side Mean Change Corrected P- Significance (%) value CA1 ipsi 2.90 0.0012 ** contra 2.90 0.0133 * CA2/3 ipsi 6.26 <0.001 *** contra 8.17 <0.001 *** CA4 ipsi 5.61 <0.001 *** contra 6.40 <0.001 *** ML HP ipsi 3.77 <0.001 *** contra 3.80 <0.001 *** GC ML DG ipsi 5.36 <0.001 *** contra 6.39 <0.001 *** Pre-Sub ipsi 0.44 1 contra 0.66 1 Subiculum ipsi 3.03 0.0019 ** contra 2.33 0.0091 ** Para-Sub ipsi -3.19 0.283 contra -3.33 0.490 Head ipsi 4.91 0.0103 * contra 2.96 <0.001 *** Body ipsi 2.29 <0.001 *** contra 5.01 <0.001 *** Tail ipsi 2.86 0.406 contra 2.21 1

Chapter 4. Study II 84

Figure 4-3 Automated hippocampal subfields segmentation using FreeSurfer 6.0 and its developmental package.

Volume changes are calculated as: VOIchange = [(VOIpost-treatment – VOIpre-treatment)/VOIpre-treatment] X 100. Results are compared to pre-treatment using Wilcoxon test. P-values are corrected for multiple comparison using Bonferroni correction (* p < 0.05, ** p < 0.01, *** p < 0.001). A-D are coronal views. F is a sagittal view. Abbreviations: CA: Cornu Ammonis; ML-HP: Molecular Layer Of Hippocampus Proper; GC-ML-DG: Granule Cell And Molecular Layer Of The Dentate Gyrus; Pre-Sub: pre-subiculum; Para-Sub: parasubiculum.

Chapter 4. Study II 85

4.4.5 Sex dependent changes in the hippocampus

Both male and female TN responders showed significant increase in the whole hippocampus after pain relief (see Fig 4-4). However, female TN responders showed greater increase compared to males, which was significantly different on the ipsilateral side (p = 0.031).

Figure 4-4 Automated hippocampal segmentation stratified by sex in the responder cohort.

(* p < 0.05, *** p < 0.001).

Chapter 4. Study II 86

4.5 Discussion

Hippocampal involvement in chronic pain conditions has been extensively explored in animal models and chronic pain patients (Mutso et al. 2014; Apkarian et al. 2005, 2017; Romero-Grimaldi et al. 2015; Maleki et al. 2013; Duric and McCarson 2006). Additionally, we have recently investigated this interplay at the hippocampus subfield level in TN patients (Vaculik et al. 2019). In contrast, the effect of pain relief on the hippocampus remains elusive because complete pain resolution is rarely achieved in majority of chronic neuropathic pain conditions. Yet, TN is an excellent model to address this limitation since this chronic pain condition is highly amenable to surgical interventions (Hodaie and Coello 2013). TN provides us with a unique opportunity to investigate the brain at both ends of the spectrum: excruciating chronic pain state and pain resolution. Using TN as a model, our current study shows for the first-time changes in the hippocampus and its subregions after pain resolution. We report that pain relief normalizes abnormalities in the hippocampus, characterized by volumetric reduction, 6 months after surgical intervention. Notably, the changes in the hippocampus is sex dependent, highlighting sex specific hippocampal plasticity in TN. Importantly, pain relief causes bilateral increase in the hippocampal subregions responsible for neurogenesis signaling neuronal plasticity as a pain modulating factor.

4.5.1 Anatomical segmentation reveals bilateral increase in subregions involved in pain modulation

Chronic pain is a debilitating disease and has a high comorbidity with depression(Currie and Wang 2004; Bair et al. 2003). It has been proposed that unpredictable recurrence pain and fluctuation in pain state, which are also the hallmarks of classical TN attacks, increase anxiety in chronic pain patients (Borsook et al. 2012; Apkarian, Hashmi, and Baliki 2011). At the same time, patient who suffer from chronic pain exhibit cognitive dysfunction including deficits in

Chapter 4. Study II 87

learning and memory (Berryman et al. 2013; Whitlock et al. 2017; Moriarty et al. 2017; Moriarty, McGuire, and Finn 2011).

The hippocampus, a central component of the limbic system, plays an essential role in learning and memory formation and is critically involved in anxiety and depression (Barkus et al. 2010; Baliki et al. 2011). Previous studies reported hippocampal abnormalities such as volume reduction in animal models and chronic pain patients including TN (Apkarian et al. 2017; Hayes et al. 2017; Romero-Grimaldi et al. 2015; Vaculik et al. 2019). Here we show that the whole hippocampus bilaterally increases in size after pain relief in the responder cohort. However, in the non-responder cohort, where they still suffer from persistent TN attacks, these changes are non-significant. Additionally, the bilateral changes reported in the responder cohort bring the hippocampus volume to the level of healthy individuals. These changes suggest that pain relief could reverse the abnormalities previously seen in the hippocampus even in the older individuals who are at risk of cognitive decline characterized chiefly by hippocampus atrophy (Mueller et al. 2010; Apostolova et al. 2006; Kälin et al. 2017).

The hippocampus consists of heterogenous subfields involved in various roles including behavior regulation, stress, and pain processing (Thompson and Neugebauer 2019; Tajerian et al. 2018; Berger et al. 2018; Bach et al. 2019). Morphological changes including atrophy in hippocampal CA3 pyramidal neurons have been observed in stress-induced situations (Watanabe, Gould, and McEwen 1992; Woolley, Gould, and McEwen 1990; Duman, Malberg, and Thome 1999). Interestingly, our current study shows bilateral increase in the CA3 hippocampal subregions which suggests pain relief which is followed by reduced TN attacks and stress could rescue the changes in CA3 hippocampal subregion.

The hippocampus has complex afferent and efferent connections to diverse brain regions including entorhinal cortex, cingulate cortex, prefrontal cortex, anterior thalamic nucleus, hypothalamic mammillary bodies. It has been proposed that these pathways are involved in

Chapter 4. Study II 88

processing painful stimuli and chronic pain (M. G. Liu and Chen 2009). Both the sensory afferent pathway – through the performant path – and the efferent outputs – through the fornix fibers – directly innervates the CA1 hippocampal subregion (Schultz and Engelhardt 2014; Witter 2010; Empson and Heinemann 1995). We have previously reported bilateral reduction in this region (Vaculik et al. 2019). Therefore, it is expected that pain relief affects such a major anatomical subregion of the hippocampus. Indeed, our current study shows bilateral increase after successful pain relief in the responder cohort. This confirms our hypothesis that pain relief leads to hippocampal neuroplasticity and changes could be reversed after pain resolution.

4.5.2 Axial segmentation

Recent studies have suggested that the functional connectivity in the human hippocampus differs along the anterior-posterior axis (Dalton, McCormick, and Maguire 2019; Beaujoin et al. 2018; Poppenk et al. 2013). Ayoub et al. also reported right anterior hippocampus has reduced connectivity to prefrontal cortex in chronic back patients compared to healthy individuals (Ayoub et al. 2019). Similarly, Vachon-Presseau et al. showed that pain intensity is associated with a stronger pain response in the anterior hippocampus (Vachon- Presseau et al. 2013). Considering the complexity of anterior-posterior (AP) hippocampal connectivity to other brain region, we decided to utilize the developmental package of the FreeSurfer 6.0 and automatically segment the hippocampus along its AP axis: head and body.

Anatomical studies have proposed that the anterior hippocampus is involved in anxiety and fear-like behaviors and the posterior subregions are mostly involved in memory and learning (Fanselow and Dong 2010; Bannerman et al. 2004; Kjelstrup et al. 2002). Our analyses delineate that the head (corresponding to the anterior hippocampus) and the body (mostly overlapping with the posterior subregions) bilaterally increase in size after pain relief. Our findings suggest that both anatomical and functional subregions of the hippocampus benefit from pain relief and further delineates the role of the hippocampus in pain processing.

Chapter 4. Study II 89

4.5.3 Hippocampal increase in size may be a consequence of neurogenesis

Plasticity in the grey matter can be traced to both neuronal and non-neuronal activity- dependent changes. The mechanisms include neurogenesis, gliogenesis, synaptogenesis, and other neuronal morphological changes (Zatorre, Fields, and Johansen-Berg 2012). Subventricular zone of the lateral ventricles and the subgranular zone of the dentate gyrus (DG) in the hippocampus are the two specific brain regions which provide the niche for adult neurogenesis (Lledo, Alonso, and Grubb 2006). Previous studies have reported altered adult hippocampal neurogenesis (AHN) in chronic pain animal models (Grilli 2017; Vasic and Schmidt 2017). Multiple studies have reported neuropathic pain negatively affects neurogenesis (Romero-Grimaldi et al. 2015; Terada et al. 2008; Dimitrov et al. 2014; Dellarole et al. 2014). Similarly, other studies reported decreases AHN in persistent pain conditions (Apkarian et al. 2017; Mutso et al. 2014; Duric and McCarson 2006). Additionally, we have previously reported significant bilateral volume loss in the CA4, GC-DG, and molecular layer of hippocampus proper (ML-HP) – primary hippocampal subfields for AHN – in TN patients (Vaculik et al. 2019).

Interestingly, in our current study we show bilateral increase in GC DG, CA4, ML-HP after successful pain relief in TN subjects. Although it is not possible to pinpoint which mechanisms – neurogenesis, gliogenesis, or synaptogenesis – have caused the GM increases, the evidence suggests that the volume increase is could be partially driven by neurogenesis. However, future studies are required to delineate the effect of pain relief on neurogenesis.

4.5.4 Sex differences in response to pain relief

Previous studies have delineated sex difference in cognitive tasks and neurogenesis (for a detailed review, please refer to Yagi & Galea, 2019) (Yagi and Galea 2019). Hillerer et al. have reported sex dependent neurogenesis under chronic stress (Hillerer et al. 2013b). In

Chapter 4. Study II 90

prolonged stress conditions, females showed reduction in neurogenesis compared to males, suggesting stress exposure has more impact on females compared to males (Hillerer et al. 2013b). Interestingly, our previous study reported females but not males suffer from bilateral hippocampal volume reduction (Vaculik et al. 2019). In the current study, we show that both males and females benefit from bilateral hippocampal volume increase after pain relief (Fig 4- 4). However, females showed larger increase on average compared to male with ipsilateral side being statistically different. These results suggest that pain relief – which is followed by reduced stress – has more impact on females than males. Considering that neurogenesis in females is more impacted by chronic stress, it is possible that pain relief rescues neurogenesis to a greater extend in females but males. As our study is the first investigation of pain relief and its effect on the hippocampus, future studies are required to further delineate the mechanisms behind sex responses in pain relief.

4.5.5 Study Limitations

In the current study, we retrospectively recruited 61 TN subjects over past decade. As a result, clinical notes were missing information such as the duration of TN pain before surgical treatment. This prevented us from correlation analysis of pain duration and amount of volumetric changes after pain relief. However, compared to previous studies focused on understanding the TN pain, our cohort provides a comprehensive pre- and post-surgery view. Additionally, considering the number of non-responder patients who did not benefit from pain relief, we were statistically limited and had to focus on the responder cohort for subfield and sex-dependent analyses.

The onset for TN is usually after age 50 and the TN cohort investigated in the current study has an average age of 64.88 ± 12.01 years. Therefore, we were limited by the number of healthy aged controls collected on site and had to utilize the Cam-CAN online dataset. Although our analysis showed that the brain region volumes are not statistically different

Chapter 4. Study II 91

between healthy controls collected on site and Cam-CAN dataset, the different imaging protocols and scanners could be considered a compounding factor that our study was limited to account for.

TN patients suffer from a debilitating pain that requires them to use pain medications and anticonvulsant drugs including carbamazepine and gabapentin. However, surgical treatments such as GKRS are proven to be highly effective at reducing TN pain and patients often reduce their medications after pain relief. As such, we were not able to control for the effect of medications after pain relief.

Chapter 5 General discussion

5.1 Summary of findings

The main findings of this thesis are as follows:

I. Compared to healthy controls, TN patients have selective volumetric hippocampal subfield abnormalities. Specifically, subfields involved in memory encoding, pain processing, and neurogenesis are affected and are smaller in size compared to healthy controls.

II. The whole hippocampus is bilaterally affected in TN patients compared to healthy controls: TN patients have smaller hippocampi.

III. Pain duration correlates with hippocampal volume reduction and patients with a longer history of pain have smaller ipsilateral hippocampus. Additionally, volume reduction in ipsilateral CA1 and ML HP is related to pain duration.

IV. Pain resolution after successful surgical treatment can reverse structural abnormalities seen in the hippocampus and hippocampus increases in size after pain relief.

V. Hippocampal changes are sex-dependent, and males and females have different hippocampal volume reduction profile. Additionally, structural changes after pain relief are also sex-dependent and females have a magnified response compared to males after successful surgical intervention. Chapter 5. General Discussion 93

Taken together, our studies demonstrate that classical TN is associated with volumetric abnormalities at the hippocampus and its subfields. However, successful surgical treatment which lead to pain resolution, can normalize hippocampal volume abnormalities. The structural changes observed in the hippocampal subfields suggest that molecular processes such as neurogenesis could be negatively affected in chronic pain conditions.

5.2 Trigeminal neuralgia as a model of evoked pain

TN is a chronic pain disorder and has been described as one of the most severe painful conditions that one can suffer from. In addition to severity, TN has several unique features that distinguishes it from other neuropathic pain disorders and make TN an ideal model for investigation of pain. These features include, but are not limited to, the followings:

1. TN is overwhelmingly unilateral. Compared to other chronic pain disorders, such as lower back pain or migraine, the majority of TN cases present as a unilateral pain on one side of the face (Montano et al. 2015). This provides researchers with a unique opportunity to investigate pain laterality when studying structural/functional abnormalities in chronic pain conditions.

2. The pain of TN is severe in its nature. TN pain is considered one of the most painful conditions known to humankind. Additionally, TN pain carries the element of unpredictability for TN patients as attacks can appear abruptly without any reason. Thus, TN patients are more susceptible to anxiety related to chronic pain as discussed in the first chapter of this work.

3. Compared to other chronic pain conditions, such as carpal tunnel syndrome or chronic lower back pain, TN patients do not report other sensory deficits such as numbness.

Chapter 5. General Discussion 94

Therefore, it can be argued that the pain itself, not other sensorial abnormalities, is the main reason for the changes observed in the CNS.

4. TN is highly amendable to surgical interventions. Surgical interventions, such as GKRS, has been proven to be effective in around 70% of cases (Gronseth et al. 2008). Additionally, successful treatments lead to complete resolution of pain in most cases. This means that we can study TN patients in two states, one when they are in excruciating pain with 10/10 rating on the NRS rating system, and one when they are almost pain-free with ratings of 1/10 or 0/10 on the NRS rating system. Therefore, investigating TN patients pre- and post-surgery can reveal the brain changes upon pain relief and whether pain resolution normalizes the abnormalities of the TN brain.

5.3 Hippocampal alterations in TN

The present studies add to an increasing body of evidence suggesting the involvement of the hippocampus in chronic neuropathic pain. This thesis focuses on two specific studies, first on the structure of the hippocampus and its subfields in TN. A second study investigates the effect of surgical treatment of pain relief on the structural abnormalities reported in the first study.

The hippocampus receives neuronal inputs from various brain regions. As described previously, the hippocampal formation further processes these inputs and relay the information to other cortical and subcortical brain structures (Bach et al. 2019; Kondo, Lavenex, and Amaral 2008). The hippocampus is involved in modulating emotions, encoding memories, and regulating anxiety and stress. At the same time, chronic pain patients suffer from anxiety, stress, and depression – disorders highly regulated by the hippocampus (De Heer et al. 2014; Gureje et al. 2008). Additionally, memory complains are one of the symptoms vastly reported

Chapter 5. General Discussion 95

by chronic pain patients (McCarberg and Peppin 2019). Taken together, these evidences indicate that the hippocampus has a role in pain experience, and justify the aims in our studies.

The majority of hippocampal studies have investigated this brain region in animal models. However, with the advent of neuroimaging techniques, we are now able to explore this brain region in humans. So far, the evidence suggests reduction in hippocampal GM in chronic pain conditions (Mutso et al. 2012; Hayes et al. 2017). However, considering the complex organization of the hippocampus and its varied functions, treating the entire structure of the hippocampus as a single entity likely ignores critical information now obtainable through MRI volumetric analysis techniques. Therefore, this thesis focused on understanding hippocampal subfields in chronic pain conditions. For the first time, we demonstrate selective reduction in specific hippocampal subfields in patients with classical TN.

CA1 hippocampal subregions both receives input signals, mostly from the EC, and sends neuronal outputs to other brain regions, mostly through the perforant pathway and the fornix (David and Pierre 2009; Hannula and Duff 2017; Bach et al. 2019). This region is particularly important in encoding and consolidating new memories. We demonstrate in the first study that this hippocampal subregion is smaller in size in TN patients compared to healthy controls, which further signals the CA1 has a role in pain processing and shaping pain experience. This is for the first time that CA1 abnormalities have been reported in chronic pain patients. Interestingly, this region statistically increases in size after successful pain relief as was reported in the second study. These findings suggest that pain influences hippocampal neuronal connectivity and or plasticity in TN patients and the hippocampal plasticity may be a mechanism utilized by brain to modulate prolonged painful conditions.

Recently, Apkarian et al. (2017) suggested that hippocampal plasticity mediates chronic pain progression. This proposition is based on animal studies and needs to be investigated in chronic pain patients. One can do so by examining pain duration in relation to hippocampal

Chapter 5. General Discussion 96

changed observed in patients. We observed in the first study that pain duration is correlated with changes in ipsilateral whole hippocampus, CA1, and ML HP subregions. We report that TN patients who suffer for a longer period of time from this neuropathic pain have a greater reduction in the ipsilateral whole hippocampus, CA1, and ML HP subregions. As such, it may be suggested that hippocampal plasticity is a feature CNS utilizes to modulate prolonged painful conditions.

5.4 Hippocampal alterations may be related to altered hippocampal cellular mechanisms including neurogenesis and/or microglia regulation

Neurogenesis is one of the cellular hallmarks that separates hippocampus from other brain regions. However, neurogenesis is highly regulated and is sensitive to changes in environmental factors. Animal studies have suggested that neurogenesis is negatively affected in chronic pain conditions (Eisch and Petrik 2012; Apkarian et al. 2017; Mutso et al. 2012; Romero-Grimaldi et al. 2015). Alterations in neuroendocrine hormones secreted by the HPA axis is one of the leading theories underlying neurogenesis changes due to chronic pain conditions. Hormones like glucocorticoids are secreted in response to stressful conditions, such as chronic pain, in animal models (E. J. Kim, Pellman, and Kim 2015). At the same time, these hormones influence environmental factors regulating neurogenesis and negatively influence proliferation and reduce survival of new neurons. As such, neurogenesis alteration has been proposed and observed in chronic pain animal models.

Similarly, microglia activation and dysregulation have been observed in chronic neuropathic conditions (R. R. Ji and Suter 2007; G. Chen et al. 2018; Zhao et al. 2017; Inoue and Tsuda 2018). Activated microglia release cytokines and neuroinflammatory mediators, such as TNF, which could result in symptoms of neuropathic pain, such as allodynia, as well as affecting the hippocampal microenvironment (Zhao et al. 2017; Xu et al. 2006; Y. Liu et al.

Chapter 5. General Discussion 97

2017). Hippocampal neurogenesis, cell survival and proliferation are strongly regulated by microglia activity (Diaz-Aparicio et al. 2020; De Lucia et al. 2016; Lloyd and Miron 2019). As such, some of the structural changes that have been observed in our studies could be directly or indirectly related to alteration in microglia activity in the hippocampus.

Multiple mechanisms could explain the volumetric increase in brain structures quantified by neuroimaging analysis (Zatorre, Fields, and Johansen-Berg 2012). These mechanisms include axon sprouting/dendritic branching, neurogenesis, glial changes, and angiogenesis. Although pinpointing exactly which mechanism(s) is responsible for the size increase in the hippocampus requires pathological studies, current findings suggest neurogenesis alongside glial changes as probable reasons: I) Animal studies of chronic pain report that neurogenesis is negatively influenced in the hippocampus and suggest that reduced neurogenesis can modulate prolonged pain (Mutso et al. 2012; Apkarian et al. 2017; Romero-Grimaldi et al. 2015). II) we showed in study I that the GC DG and CA4 of the hippocampus are bilaterally smaller compared to healthy controls. III) we reported in Study II that pain free GC DG and CA4, which are regions in the brain capable of generating new neurons, are bilaterally bigger in size compared to pre-surgery when the brain was coping with TN pain. IV) Microglia activity is heavily altered in chronic neuropathic pain and glial changes, such as gliogenesis, could also increase hippocampal volume.

However, neurogenesis and/or glial changes cannot be measured in vivo in humans. Neuroimaging techniques could help us to find markers indicative of neurogenesis alterations. One of such markers could be increase in size in the hippocampus, especially the areas involved in neurogenesis such as GC of DG and CA4 as was reported in Study II. Taken together, our result suggests that neurogenesis and/or glial changes could be potential mechanisms for the hippocampal size alterations, specifically in CA4 and GC DG subregions.

Chapter 5. General Discussion 98

Although, our understanding is limited to explain hippocampal changes post pain relief. Therefore, the future animal studies can focus on the effects of pain relief on the hippocampus and pinpointing the exact mechanism(s) behind increase in the hippocampal size.

5.5 Limitations

There are some limitations in this work that need to be considered.

1. The majority of TN patients included in this study were on medications ranging from regular pain killers, such as acetaminophen, to anticonvulsants medications, such as carbamazepine or gabapentin, at the time of MR scans. This was the case for pre- surgical and some of post-surgical scans. Although there are a few studies (Olaibi, Osuntokun, and Lijomone 2014; Haneef, Levin, and Chiang 2015) suggesting that anticonvulsants may alter hippocampal neuronal circuits, the direct effects of these medications have never been studied before. Future studies are needed to examine the effects of medications on the hippocampal formation and its function.

2. TN patients scheduled for GKRS are usually scanned on the day of surgery. These images are used to guide the stereotactic surgery. However, because of the limits imposed on scan time due to clinical imaging scheduling, some of the scans in the second study did not capture the whole brain, in particular the entire cortex. Nonetheless, the scans covered all subcortical regions, including the hippocampus, and were properly analyzed by the subcortical stream of the FreeSurfer 6.0. Due to this limitation in study II, we had to utilize subcortical volume (not the intracranial volume) to normalize hippocampus size due to different brain sizes.

Chapter 5. General Discussion 99

3. The TN patients included in this work had been retrospectively recruited over the past decade. As such, some clinical notes had missing information, such as pain duration that prevented us in Study II to perform correlation analyses. Another constraint this limitation has imposed on this work is that psychological and/or memory performance tests were not a part of routine clinical visits. Therefore, we were unable to correlate the structural changes to potential functional abnormalities in the hippocampus.

4. 3T structural T1 images, including the ones were used in this thesis, have a resolution around 1mm3. As such, neuroimaging analyses cannot delineate changes at the cellular level and are limited in terms of resolution. Therefore, neuroimaging techniques may overlook possible cellular mechanisms and involvements.

5. TN usually begins after age 50 and this made recruiting healthy individuals for our studies particularly challenging. We were able to age- and sex-match all TN patients in Study I to healthy controls collected on-site, however, this was not the case for Study II. Therefore, we used the Cam-CAN online dataset to acquire age- and sex-matched MR scans of healthy individuals. Although we showed that the brain region volumes were not statistically different between healthy controls collected on site and the Cam- CAN dataset MR scans, the different imaging protocols and scanners could be considered a confounding factor for which the second study could not account for.

Chapter 6 Conclusion

This thesis provides evidence that TN patients have abnormal hippocampi, and that these abnormalities are present in a subset of the hippocampal subfields. These abnormalities normalize upon pain relief after surgical intervention. The findings contribute to the growing body of evidence suggesting hippocampal involvement in pain and highlights the hippocampus undergoes plasticity following chronic neuropathic pain resolution. Sex-dependent changes reported in our study further emphasize the need to explicitly investigate sex differences in studies of chronic pain. Additionally, TN as a unique neuropathic facial pain enabled us to study the hippocampus in severe pain as well as its complete resolution in the same individual. As such, TN should be considered as a unique model in investigating the role of the hippocampus in pain modulation.

Chapter 7 Future Directions

In addition to addressing the limitations mentioned in previous chapters, the findings reported in this work can guide future studies to unravel the mechanisms underlying hippocampal alterations in chronic pain conditions:

1. Diffusion tensor imaging (DTI) has provided us with invaluable findings on how brain WM fibers, including the trigeminal nerve itself, are abnormal in chronic pain conditions. However, recent studies have reported that DTI can detect microstructural abnormalities of the human hippocampus in different disorders (Treit et al. 2018). DTI can provide unique information about microstructural pathology that may proceed/coincide with structural changes such as volumetric abnormalities reported in this thesis. As such, future studies should incorporate this imaging modality when investigating hippocampal abnormalities in chronic pain conditions.

2. Multiple studies have reported GM abnormalities in other subcortical regions, including nucleus accumbens, in other chronic pain conditions. With the advances in neuroimaging techniques and TN as a unique model, future studies could focus on alterations in other subcortical regions pre- and post-surgery in TN patients.

3. Future studies should incorporate additional behavioral and memory tests in order to investigate functional aspects of hippocampal alterations in chronic pain conditions. Chapter 7. Future Directions 102

4. Animal studies are needed to examine the cellular mechanisms underlying structural changes after successful pain relief to investigate whether neurogenesis or other mechanisms are responsible for hippocampal recovery upon successful pain relief.

5. Functional imaging studies using resting and task-based connectivity approaches would provide a unique perspective into how hippocampal abnormalities affect hippocampal functional connectivity. As such, future studies could focus on hippocampal connectivity in pre- and post-surgical interventions in TN patients.

6. The effect of medications, regularly used to treat TN (including CBZ and GBP), on hippocampus remains elusive and future studies can investigate the of effect of other treatments on hippocampal GM alterations.

7. Other chronic pain disorders such as carpal tunnel syndrome are amenable to surgical interventions. Therefore, future studies can investigate whether pain relief has the same effect on the hippocampus in other chronic pain condition.

References

Acsády, László, and Szabolcs Káli. 2007. “Models, Structure, Function: The Transformation of Cortical Signals in the Dentate Gyrus.” Progress in Brain Research 163: 577–99. https://doi.org/10.1016/S0079-6123(07)63031-3.

Adnan, Areeba, Alexander Barnett, Massieh Moayedi, Cornelia McCormick, Melanie Cohn, and Mary Pat McAndrews. 2016. “Distinct Hippocampal Functional Networks Revealed by Tractography-Based Parcellation.” Brain Structure and Function 221 (6): 2999–3012. https://doi.org/10.1007/s00429-015-1084-x.

Agarwal, Ayush, and Manjari Tripathi. 2019. “Pharmacotherapy of Trigeminal Neuralgia.” In Handbook of Trigeminal Neuralgia, edited by Girija Prasad Rath, 63–68. Springer Singapore. https://doi.org/10.1007/978-981-13-2333-1_8.

Alfarez, D N, O Wiegert, M Joëls, and H J Krugers. 2002. “Corticosterone and Stress Reduce Synaptic Potentiation in Mouse Hippocampal Slices with Mild Stimulation.” Neuroscience 115 (4): 1119–26. https://doi.org/10.1016/s0306-4522(02)00483-9.

Aloisi, Anna Maria, Ilaria Ceccarelli, and Thomas Herdegen. 2000. “Gonadectomy and Persistent Pain Differently Affect Hippocampal C-Fos Expression in Male and Female Rats.” Neuroscience Letters 281 (1): 29–32. https://doi.org/10.1016/S0304-3940(00)00819-3.

Andersen, Per, Richard Morris, David Amaral, Tim Bliss, and John O’ Keefe. 2009. The Hippocampus Book. Edited by Per Andersen, Richard Morris, David Amaral, Tim Bliss, and John O’ Keefe. The Hippocampus Book. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195100273.001.0001.

Apkarian, A. Vania. 2008. “Pain Perception in Relation to Emotional Learning.” Current Opinion in Neurobiology. https://doi.org/10.1016/j.conb.2008.09.012.

Apkarian, A. Vania, M. Catherine Bushnell, Rolf-Detlef Treede, and Jon Kar Zubieta. 2005. “Human Brain Mechanisms of Pain Perception and Regulation in Health and Disease.” European Journal of Pain 9 (4): 463. https://doi.org/10.1016/j.ejpain.2004.11.001.

Apkarian, A. Vania, Javeria A. Hashmi, and Marwan N. Baliki. 2011. “Pain and the Brain: Specificity and Plasticity of the Brain in Clinical Chronic Pain.” Pain 152 (SUPPL.3). https://doi.org/10.1016/j.pain.2010.11.010.

Apkarian, A. Vania, Amelia A. Mutso, Maria V. Centeno, Lixin Kan, Melody Wu, Marjorie Levinstein, Ghazal Banisadr, et al. 2017. “Role of Adult Hippocampal Neurogenesis in Persistent Pain.” Pain 157 (2): 418–28. https://doi.org/10.1097/j.pain.0000000000000332.Role.

Apostolova, Liana G., Rebecca A. Dutton, Ivo D. Dinov, Kiralee M. Hayashi, Arthur W. Toga, REFERENCES 104

Jeffrey L. Cummings, and Paul M. Thompson. 2006. “Conversion of Mild Cognitive Impairment to Alzheimer Disease Predicted by Hippocampal Atrophy Maps.” Archives of Neurology 63 (5): 693–99. https://doi.org/10.1001/archneur.63.5.693.

Ayoub, Lizbeth J., Alexander Barnett, Aziliz Leboucher, Mitchell Golosky, Mary Pat McAndrews, David A. Seminowicz, and Massieh Moayedi. 2019. “The Medial Temporal Lobe in Nociception.” Pain 160 (6): 1245–60. https://doi.org/10.1097/j.pain.0000000000001519.

Bach, Dominik R., Martina Hoffmann, Carsten Finke, Rene Hurlemann, and Christoph J. Ploner. 2019. “Disentangling Hippocampal and Amygdala Contribution to Human Anxiety-Like Behavior.” The Journal of Neuroscience : The Official Journal of the Society for Neuroscience 39 (43): 8517–26. https://doi.org/10.1523/JNEUROSCI.0412-19.2019.

Bagarinao, Epifanio, Kevin A. Johnson, Katherine T. Martucci, Eric Ichesco, Melissa A. Farmer, Jennifer Labus, Timothy J. Ness, et al. 2014. “Preliminary Structural MRI Based Brain Classification of Chronic Pelvic Pain: A MAPP Network Study.” Pain 155 (12): 2502–9. https://doi.org/10.1016/j.pain.2014.09.002.

Bair, Matthew J., Rebecca L. Robinson, Wayne Katon, and Kurt Kroenke. 2003. “Depression and Pain Comorbidity.” Archives of Internal Medicine 163 (20): 2433. https://doi.org/10.1001/archinte.163.20.2433.

Bale, Tracy L., and C. Neill Epperson. 2015. “Sex Differences and Stress across the Lifespan.” Nature Neuroscience 18 (10): 1413–20. https://doi.org/10.1038/nn.4112.

Baliki, Marwan N., Paul Y. Geha, Howard L. Fields, and A. Vania Apkarian. 2010. “Predicting Value of Pain and Analgesia: Nucleus Accumbens Response to Noxious Stimuli Changes in the Presence of Chronic Pain.” Neuron 66 (1): 149–60. https://doi.org/10.1016/j.neuron.2010.03.002.

Baliki, Marwan N., Thomas J. Schnitzer, William R. Bauer, and A. Vania Apkarian. 2011. “Brain Morphological Signatures for Chronic Pain.” PLoS ONE 6 (10). https://doi.org/10.1371/journal.pone.0026010.

Bannerman, D. M., J. N.P. Rawlins, S. B. McHugh, R. M.J. Deacon, B. K. Yee, T. Bast, W. N. Zhang, H. H.J. Pothuizen, and J. Feldon. 2004. “Regional Dissociations within the Hippocampus - Memory and Anxiety.” Neuroscience and Biobehavioral Reviews 28 (3): 273– 83. https://doi.org/10.1016/j.neubiorev.2004.03.004.

Barkus, Christopher, Stephen B. McHugh, Rolf Sprengel, Peter H. Seeburg, J. Nicholas P. Rawlins, and David M. Bannerman. 2010. “Hippocampal NMDA Receptors and Anxiety: At the Interface between Cognition and Emotion.” European Journal of Pharmacology 626 (1): 49–56. https://doi.org/10.1016/j.ejphar.2009.10.014.

Baxter, L. C., A. J. Saykin, L. A. Flashman, S. C. Johnson, S. J. Guerin, D. R. Babcock, and H. A.

REFERENCES 105

Wishart. 2003. “Sex Differences in Semantic Language Processing: A Functional MRI Study.” Brain and Language 84 (2): 264–72. https://doi.org/10.1016/S0093-934X(02)00549-7.

Beaujoin, Justine, Nicola Palomero-Gallagher, Fawzi Boumezbeur, Markus Axer, Jeremy Bernard, Fabrice Poupon, Daniel Schmitz, Jean François Mangin, and Cyril Poupon. 2018. “Post-Mortem Inference of the Human Hippocampal Connectivity and Microstructure Using Ultra-High Field Diffusion MRI at 11.7 T.” Brain Structure and Function 223 (5): 2157–79. https://doi.org/10.1007/s00429-018-1617-1.

Belcheva, Iren, Margarita Ivanova, Roman Tashev, and Stiliana Belcheva. 2009. “Differential Involvement of Hippocampal Vasoactive Intestinal Peptide in Nociception of Rats with a Model of Depression.” Peptides 30 (8): 1497–1501. https://doi.org/10.1016/j.peptides.2009.05.015.

Bennetto, Luke, Nikunj K. Patel, and Geraint Fuller. 2007. “Trigeminal Neuralgia and Its Management.” British Medical Journal 334 (7586): 201–5. https://doi.org/10.1136/bmj.39085.614792.BE.

Bereiter, David A., Harumitsu Hirata, and James W. Hu. 2000. “Trigeminal Subnucleus Caudalis: Beyond Homologies with the Spinal Dorsal Horn.” Pain 88 (3): 221–24. https://doi.org/10.1016/S0304-3959(00)00434-6.

Berger, Sara E., Étienne Vachon-Presseau, Taha B. Abdullah, Alex T. Baria, Thomas J. Schnitzer, and A. Vania Apkarian. 2018. “Hippocampal Morphology Mediates Biased Memories of Chronic Pain.” NeuroImage 166 (February): 86–98. https://doi.org/10.1016/J.NEUROIMAGE.2017.10.030.

Berryman, Carolyn, Tasha R. Stanton, K. Jane Bowering, Abby Tabor, Alexander McFarlane, and G. Lorimer Moseley. 2013. “Evidence for Working Memory Deficits in Chronic Pain: A Systematic Review and Meta-Analysis.” Pain 154 (8): 1181–96. https://doi.org/10.1016/j.pain.2013.03.002.

Bingel, U., M. Quante, R. Knab, B. Bromm, C. Weiller, and C. Büchel. 2002. “Subcortical Structures Involved in Pain Processing: Evidence from Single-Trial FMRI.” Pain 99: 313–21. https://doi.org/10.1016/S0304-3959(02)00157-4.

Bitar, Richard, General Leung, Richard Perng, Sameh Tadros, Alan R. Moody, Josee Sarrazin, Caitlin McGregor, et al. 2006. “MR Pulse Sequences: What Every Radiologist Wants to Know but Is Afraid to Ask.” Radiographics 26 (2): 513–37. https://doi.org/10.1148/rg.262055063.

Blankstein, Udi, Jerry Chen, Nicholas E. Diamant, and Karen D. Davis. 2010. “Altered Brain Structure in Irritable Bowel Syndrome: Potential Contributions of Pre-Existing and Disease- Driven Factors.” Gastroenterology 138 (5): 1783–89. https://doi.org/10.1053/j.gastro.2009.12.043.

Bolay, Hayrunnisa, and Michael A. Moskowitz. 2002. “Mechanisms of Pain Modulation in Chronic

REFERENCES 106

Syndromes.” Neurology 59 (5 SUPPL. 2). https://doi.org/10.1212/wnl.59.5_suppl_2.s2.

Bonne, O., D. Brandes, A. Gilboa, J. M. Gomori, M. E. Shenton, R. K. Pitman, and A. Y. Shalev. 2001. “Longitudinal MRI Study of Hippocampal Volume in Trauma Survivors with PTSD.” American Journal of Psychiatry 158 (8): 1248–51. https://doi.org/10.1176/appi.ajp.158.8.1248.

Borsini, Alessandra, Patricia A. Zunszain, Sandrine Thuret, and Carmine M. Pariante. 2015. “The Role of Inflammatory Cytokines as Key Modulators of Neurogenesis.” Trends in Neurosciences. Elsevier Ltd. https://doi.org/10.1016/j.tins.2014.12.006.

Borsook, David. 2012. “Neurological Diseases and Pain.” Brain 135 (2): 320–44. https://doi.org/10.1093/brain/awr271.

Borsook, David, Nasim Maleki, Lino Becerra, and Bruce McEwen. 2012. “Understanding Migraine through the Lens of Maladaptive Stress Responses: A Model Disease of Allostatic Load.” Neuron 73 (2): 219–34. https://doi.org/10.1016/j.neuron.2012.01.001.

Bouhassira, Didier, Michel Lantéri-Minet, Nadine Attal, Bernard Laurent, and Chantal Touboul. 2008. “Prevalence of Chronic Pain with Neuropathic Characteristics in the General Population.” Pain 136 (3): 380–87. https://doi.org/10.1016/j.pain.2007.08.013.

Bremner, J. D., P. Randall, T. M. Scott, R. A. Bronen, J. P. Seibyl, S. M. Southwick, R. C. Delaney, G. McCarthy, D. S. Charney, and R. B. Innis. 1995. “MRI-Based Measurement of Hippocampal Volume in Patients with Combat- Related Posttraumatic Stress Disorder.” American Journal of Psychiatry 152 (7): 973–81. https://doi.org/10.1176/ajp.152.7.973.

Buckner, Randy L., Denise Head, Jamie Parker, Anthony F. Fotenos, Daniel Marcus, John C. Morris, and Abraham Z. Snyder. 2004. “A Unified Approach for Morphometric and Functional Data Analysis in Young, Old, and Demented Adults Using Automated Atlas-Based Head Size Normalization: Reliability and Validation against Manual Measurement of Total Intracranial Volume.” NeuroImage 23 (2): 724–38. https://doi.org/10.1016/j.neuroimage.2004.06.018.

Bushnell, M. Catherine, Marta Čeko, and Lucie A. Low. 2013. “Cognitive and Emotional Control of Pain and Its Disruption in Chronic Pain.” Nature Reviews Neuroscience 14 (7): 502–11. https://doi.org/10.1038/nrn3516.

Campbell, James N., and Richard A. Meyer. 2006. “Mechanisms of Neuropathic Pain.” Neuron 52 (1): 77–92. https://doi.org/10.1016/j.neuron.2006.09.021.

Campbell, Stephanie, and Glenda MacQueen. 2004. “The Role of the Hippocampus in the Pathophysiology of Major Depression.” Journal of Psychiatry and Neuroscience 29 (6): 417– 26.

Canadian Pain Task Force. 2019. “Chronic Pain in Canada: Laying a Foundation for Action.” https://www.canada.ca/content/dam/hc-sc/documents/corporate/about-health-canada/public-

REFERENCES 107

engagement/external-advisory-bodies/canadian-pain-task-force/report-2019/canadian-pain-task- force-June-2019-report-en.pdf.

Cardoso-Cruz, Helder, Deolinda Lima, and Vasco Galhardo. 2013. “Impaired Spatial Memory Performance in a Rat Model of Neuropathic Pain Is Associated with Reduced Hippocampus- Prefrontal Cortex Connectivity.” Journal of Neuroscience 33 (6): 2465–80. https://doi.org/10.1523/JNEUROSCI.5197-12.2013.

Cauda, Franco, Sara Palermo, Tommaso Costa, Riccardo Torta, Sergio Duca, Ugo Vercelli, Giuliano Geminiani, and Diana M.E. Torta. 2014. “Gray Matter Alterations in Chronic Pain: A Network- Oriented Meta-Analytic Approach.” NeuroImage: Clinical 4: 676–86. https://doi.org/10.1016/j.nicl.2014.04.007.

Chapman, C. Richard, and Charles J. Vierck. 2017. “The Transition of Acute Postoperative Pain to Chronic Pain: An Integrative Overview of Research on Mechanisms.” Journal of Pain 18 (4): 359.e1-359.e38. https://doi.org/10.1016/j.jpain.2016.11.004.

Chen, David Q., Danielle D. DeSouza, David J. Hayes, Karen D. Davis, Paul O’Connor, and Mojgan Hodaie. 2016. “Diffusivity Signatures Characterize Trigeminal Neuralgia Associated with Multiple Sclerosis.” Multiple Sclerosis 22 (1): 51–63. https://doi.org/10.1177/1352458515579440.

Chen, Gang, Yu Qiu Zhang, Yawar J. Qadri, Charles N. Serhan, and Ru Rong Ji. 2018. “Microglia in Pain: Detrimental and Protective Roles in Pathogenesis and Resolution of Pain.” Neuron 100 (6): 1292–1311. https://doi.org/10.1016/j.neuron.2018.11.009.

Cliffer, K. D., R. Burstein, and G. J. Giesler. 1991. “Distributions of Spinothalamic, Spinohypothalamic, and Spinotelencephalic Fibers Revealed by Anterograde Transport of PHA- L in Rats.” Journal of Neuroscience 11 (3): 852–68. https://doi.org/10.1523/jneurosci.11-03- 00852.1991.

Colloca, Luana, Taylor Ludman, Didier Bouhassira, Ralf Baron, Anthony H. Dickenson, David Yarnitsky, Roy Freeman, et al. 2017. “Neuropathic Pain.” Nature Reviews Disease Primers 3 (February). https://doi.org/10.1038/nrdp.2017.2.

Coppola, Gianluca, Barbara Petolicchio, Antonio Di Renzo, Emanuele Tinelli, Cherubino Di Lorenzo, Vincenzo Parisi, Mariano Serrao, et al. 2017. “Cerebral Gray Matter Volume in Patients with Chronic Migraine: Correlations with Clinical Features.” Journal of Headache and Pain 18 (1). https://doi.org/10.1186/s10194-017-0825-z.

Costigan, Michael, Joachim Scholz, and Clifford J. Woolf. 2009. “Neuropathic Pain: A Maladaptive Response of the Nervous System to Damage.” Annual Review of Neuroscience 32 (1): 1–32. https://doi.org/10.1146/annurev.neuro.051508.135531.

Covey, William C., Tracey A. Ignatowski, Paul R. Knight, and Robert N. Spengler. 2000. “Brain-

REFERENCES 108

Derived TNFα : Involvement in Neuroplastic Changes Implicated in the Conscious Perception of Persistent Pain.” Brain Research 859 (1): 113–22. https://doi.org/10.1016/S0006- 8993(00)01965-X.

Covey, William C., Tracey A. Ignatowski, Amy E. Renauld, Paul R. Knight, Nader D. Nader, and Robert N. Spengler. 2002. “Expression of Neuron-Associated Tumor Necrosis Factor Alpha in the Brain Is Increased during Persistent Pain.” Regional Anesthesia and Pain Medicine 27 (4): 357–66. https://doi.org/10.1053/rapm.2002.31930.

Crusio, Wim E., and Herbert Schwegler. 2005. “Learning Spatial Orientation Tasks in the Radial- Maze and Structural Variation in the Hippocampus in Inbred Mice.” Behavioral and Brain Functions 1 (1): 3. https://doi.org/10.1186/1744-9081-1-3.

Currie, Shawn R., and Jian Li Wang. 2004. “Chronic Back Pain and Major Depression in the General Canadian Population.” Pain 107 (1–2): 54–60. https://doi.org/10.1016/j.pain.2003.09.015.

Dalton, Marshall A., Cornelia McCormick, and Eleanor A. Maguire. 2019. “Differences in Functional Connectivity along the Anterior-Posterior Axis of Human Hippocampal Subfields.” NeuroImage 192 (March): 38–51. https://doi.org/10.1016/J.NEUROIMAGE.2019.02.066.

Das, Vaskar. 2015. “An Introduction to Pain Pathways and Pain ‘Targets.’” In Progress in Molecular Biology and Translational Science, edited by Theodore J. Price and Gregory Dussor, 131:1–30. Elsevier B.V. https://doi.org/10.1016/bs.pmbts.2015.01.003.

David, Amaral, and Lavenex Pierre. 2009. “Hippocampal Neuroanatomy.” In The Hippocampus Book. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195100273.003.0003.

Deleo, Joyce A., Raymond W. Colburn, and Amy J. Rickman. 1997. “Cytokine and Growth Factor Immunohistochemical Spinal Profiles in Two Animal Models of Mononeuropathy.” Brain Research 759 (1): 50–57. https://doi.org/10.1016/S0006-8993(97)00209-6.

Dellarole, Anna, Paul Morton, Roberta Brambilla, Winston Walters, Spencer Summers, Danielle Bernardes, Mariagrazia Grilli, and John R Bethea. 2014. “Neuropathic Pain-Induced Depressive-like Behavior and Hippocampal Neurogenesis and Plasticity Are Dependent on TNFR1 Signaling.” Brain Behavior Immunology 41: 65–81. https://doi.org/10.1016/j.bbi.2014.04.003.

Desouza, Danielle D., Mojgan Hodaie, and Karen D. Davis. 2014. “Abnormal Trigeminal Nerve Microstructure and Brain White Matter in Idiopathic Trigeminal Neuralgia.” Pain 155 (1): 37– 44. https://doi.org/10.1016/j.pain.2013.08.029.

———. 2016. “Structural Magnetic Resonance Imaging Can Identify Trigeminal System Abnormalities in Classical Trigeminal Neuralgia.” Frontiers in Neuroanatomy. Frontiers Media S.A. https://doi.org/10.3389/fnana.2016.00095.

REFERENCES 109

DeSouza, Danielle D., Massieh Moayedi, David Q. Chen, Karen D. Davis, and Mojgan Hodaie. 2013. “Sensorimotor and Pain Modulation Brain Abnormalities in Trigeminal Neuralgia: A Paroxysmal, Sensory-Triggered Neuropathic Pain.” PLoS ONE 8 (6). https://doi.org/10.1371/journal.pone.0066340.

Diamond, David M., M. Catherine Bennett, Monika Fleshner, and Gregory M. Rose. 1992. “Inverted‐ U Relationship between the Level of Peripheral Corticosterone and the Magnitude of Hippocampal Primed Burst Potentiation.” Hippocampus 2 (4): 421–30. https://doi.org/10.1002/hipo.450020409.

Diaz-Aparicio, Irune, Iñaki Paris, Virginia Sierra-Torre, Ainhoa Plaza-Zabala, Noelia Rodríguez- Iglesias, Mar Márquez-Ropero, Sol Beccari, et al. 2020. “Microglia Actively Remodel Adult Hippocampal Neurogenesis through the Phagocytosis Secretome.” The Journal of Neuroscience : The Official Journal of the Society for Neuroscience 40 (7): 1453–82. https://doi.org/10.1523/JNEUROSCI.0993-19.2019.

Dick, Bruce D., and Saifudin Rashiq. 2007. “Disruption of Attention and Working Memory Traces in Individuals with Chronic Pain.” Anesthesia and Analgesia 104 (5): 1223–29. https://doi.org/10.1213/01.ane.0000263280.49786.f5.

Dimitrov, Eugene L., Mumeko C. Tsuda, Ted B. Usdin, Heather A. Cameron, and Eugene L. Dimitrov. 2014. “Anxiety- and Depression-like Behavior and Impaired Neurogenesis Evoked by Peripheral Neuropathy Persist Following Resolution of Prolonged Tactile Hypersensitivity.” Journal of Neuroscience 34 (37): 12304–12. https://doi.org/10.1523/JNEUROSCI.0312- 14.2014.

Dolorfo, Cynthia L., and David G. Amaral. 1998. “Entorhinal Cortex of the Rat: Topographic Organization of the Cells of Origin of the Perforant Path Projection to the Dentate Gyrus” 398 (1): 25–48. https://doi.org/10.1002/(SICI)1096-9861(19980817)398:1<25::AID- CNE3>3.0.CO;2-B.

Dubin, Adrienne E., and Ardem Patapoutian. 2010. “Nociceptors: The Sensors of the Pain Pathway.” Journal of Clinical Investigation 120 (11): 3760–72. https://doi.org/10.1172/JCI42843.

Duman, Ronald S., Jessica Malberg, and Johannes Thome. 1999. “Neural Plasticity to Stress and Antidepressant Treatment.” Biological Psychiatry 46 (9): 1181–91. https://doi.org/10.1016/S0006-3223(99)00177-8.

Duric, Vanja, and Kenneth E. McCarson. 2006. “Persistent Pain Produces Stress-like Alterations in Hippocampal Neurogenesis and Gene Expression.” Journal of Pain 7 (8): 544–55. https://doi.org/10.1016/j.jpain.2006.01.458.

Dutar, P., Y. Lamour, and A. Jobert. 1985. “Activation of Identified Septo-Hippocampal Neurons by Noxious Peripheral Stimulation.” Brain Research 328 (1): 15–21. https://doi.org/10.1016/0006- 8993(85)91317-4.

REFERENCES 110

Duvernoy, Henri M., Françoise Francoise Cattin, Pierre-Yves Yves Risold, J. L. Vannson, M. Gaudron, TH. Naidich, G. Fatterpekar, Pierre-Yves Yves Risold, U. Salvolini, and ScarabinoT. 2005. The Human Hippocampus: Functional Anatomy, Vascularization and Serial Sections with MRI. Edited by Henri M. Duvernoy, Françoise Francoise Cattin, and Pierre-Yves Yves Risold. The Human Hippocampus: Functional Anatomy, Vascularization and Serial Sections with MRI, Fourth Edition. Third. Springer. https://doi.org/10.1007/978-3-642-33603-4.

Dzung, Ho, and Oscar A. De Leon-Casasola. 2010. “Neuropathic Pain: An Updated Grading System for Research and Clinical Practice.” The Essence of Analgesia and Analgesics 157 (8): 30–37. https://doi.org/10.1017/CBO9780511841378.007.

Eberhard, Buhl, and Whittington Miles. 2009. “Local Circuits.” In The Hippocampus Book, edited by Per Andersen, Richard Morris, David Amaral, Tim Bliss, and John O’ Keefe. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195100273.003.0008.

Eccleston, Chris, and Geert Crombez. 1999. “Pain Demands Attention: A Cognitive-Affective Model of the Interruptive Function of Pain.” Psychological Bulletin 125 (3): 356–66. https://doi.org/10.1037/0033-2909.125.3.356.

Eichenbaum, Howard, Paul Dudchenko, Emma Wood, Matthew Shapiro, and Heikki Tanila. 1999. “The Hippocampus, Memory, and Place Cells: Is It Spatial Memory or a Memory Space?” Neuron. Cell Press. https://doi.org/10.1016/S0896-6273(00)80773-4.

Eisch, Amelia J., and David Petrik. 2012. “Depression and Hippocampal Neurogenesis: A Road to Remission?” Science 338 (6103): 72–75. https://doi.org/10.1126/science.1222941.

Empson, R. M., and U. Heinemann. 1995. “The Perforant Path Projection to Hippocampal Area CA1 in the Rat Hippocampal‐entorhinal Cortex Combined Slice.” The Journal of Physiology 484 (3): 707–20. https://doi.org/10.1113/jphysiol.1995.sp020697.

Erpelding, Nathalie, Laura Simons, Alyssa Lebel, Paul Serrano, Melissa Pielech, Sanjay Prabhu, Lino Becerra, and David Borsook. 2016. “Rapid Treatment-Induced Brain Changes in Pediatric CRPS.” Brain Structure and Function 221 (2): 1095–1111. https://doi.org/10.1007/s00429-014- 0957-8.

Evans, A. C., D. L. Collins, S. R. Mills, E. D. Brown, R. L. Kelly, and T. M. Peters. 1994. “3D Statistical Neuroanatomical Models from 305 MRI Volumes.” In IEEE Nuclear Science Symposium & Medical Imaging Conference, 1813–17. Publ by IEEE. https://doi.org/10.1109/nssmic.1993.373602.

Ezzati, Ali, Andrea R. Zammit, Michael L. Lipton, and Richard B. Lipton. 2019. “The Relationship between Hippocampal Volume, Chronic Pain, and Depressive Symptoms in Older Adults.” Psychiatry Research - Neuroimaging 289 (July): 10–12. https://doi.org/10.1016/j.pscychresns.2019.05.003.

REFERENCES 111

Ezzati, Ali, Molly E. Zimmerman, Mindy J. Katz, Erin E. Sundermann, Jeremy L. Smith, Michael L. Lipton, and Richard B. Lipton. 2014. “Hippocampal Subfields Differentially Correlate with Chronic Pain in Older Adults.” Brain Research 1573 (July): 54–62. https://doi.org/10.1016/j.brainres.2014.05.025.

Falconer, Erin M., and Liisa A.M. Galea. 2003. “Sex Differences in Cell Proliferation, Cell Death and Defensive Behavior Following Acute Predator Odor Stress in Adult Rats.” Brain Research 975 (1–2): 22–36. https://doi.org/10.1016/S0006-8993(03)02542-3.

Fanselow, Michael S., and Hong Wei Dong. 2010. “Are the Dorsal and Ventral Hippocampus Functionally Distinct Structures?” Neuron 65 (1): 7–19. https://doi.org/10.1016/j.neuron.2009.11.031.

Fields, H L, M M Heinricher, and P Mason. 1991. “Neurotransmitters in Nociceptive Modulatory Circuits.” Annual Review of Neuroscience 14 (1): 219–45. https://doi.org/10.1146/annurev.ne.14.030191.001251.

Filippi, Massimo, Paola Valsasina, Paolo Misci, Andrea Falini, Giancarlo Comi, and Maria A Rocca. 2013. “The Organization of Intrinsic Brain Activity Differs between Genders: A Resting-State FMRI Study in a Large Cohort of Young Healthy Subjects.” Human Brain Mapping 34 (6): 1330–43. https://doi.org/10.1002/hbm.21514.

Fillingim, Roger B., Christopher D. King, Margarete C. Ribeiro-Dasilva, Bridgett Rahim-Williams, and Joseph L. Riley. 2009. “Sex, Gender, and Pain: A Review of Recent Clinical and Experimental Findings.” Journal of Pain 10 (5): 447–85. https://doi.org/10.1016/j.jpain.2008.12.001.

Firouzian, Shahrzad, Natalie R Osborne, Joshua C Cheng, Junseok A Kim, Rachael L Bosma, Kasey S Hemington, Anton Rogachov, and Karen D Davis. 2020. “Individual Variability and Sex Differences in Conditioned Pain Modulation and the Impact of Resilience, and Conditioning Stimulus Pain Unpleasantness and Salience.” PAIN Articles i. https://journals.lww.com/pain/Fulltext/9000/Individual_variability_and_sex_differences_in.984 54.aspx.

Fischl, Bruce. 2012. “FreeSurfer.” NeuroImage 62 (2): 774–81. https://doi.org/10.1016/j.neuroimage.2012.01.021.

Fischl, Bruce, André Van Der Kouwe, Christophe Destrieux, Eric Halgren, Florent Ségonne, David H. Salat, Evelina Busa, et al. 2004. “Automatically Parcellating the Human Cerebral Cortex.” Cerebral Cortex 14 (1): 11–22. https://doi.org/10.1093/cercor/bhg087.

Fischl, Bruce, David H. Salat, Evelina Busa, Marilyn Albert, Megan Dieterich, Christian Haselgrove, Andre Van Der Kouwe, et al. 2002. “Whole Brain Segmentation: Automated Labeling of Neuroanatomical Structures in the Human Brain.” Neuron 33 (3): 341–55. https://doi.org/10.1016/S0896-6273(02)00569-X.

REFERENCES 112

Fortin, Norbert J., Kara L. Agster, and Howard B. Eichenbaum. 2002. “Critical Role of the Hippocampus in Memory for Sequences of Events.” Nature Neuroscience 5 (5): 458–62. https://doi.org/10.1038/nn834.

Galea, L. A.M., B. S. McEwen, P. Tanapat, T. Deak, R. L. Spencer, and F. S. Dhabhar. 1997. “Sex Differences in Dendritic Atrophy of CA3 Pyramidal Neurons in Response to Chronic Restraint Stress.” Neuroscience 81 (3): 689–97. https://doi.org/10.1016/S0306-4522(97)00233-9.

Galea, L. A.M., S. R. Wainwright, M. M. Roes, P. Duarte-Guterman, C. Chow, and D. K. Hamson. 2013. “Sex, Hormones and Neurogenesis in the Hippocampus: Hormonal Modulation of Neurogenesis and Potential Functional Implications.” Journal of Neuroendocrinology 25 (11): 1039–61. https://doi.org/10.1111/jne.12070.

Garland, Eric L. 2012. “Pain Processing in the Human Nervous System. A Selective Review of Nociceptive and Biobehavioral Pathways.” Primary Care - Clinics in Office Practice 39 (3): 561–71. https://doi.org/10.1016/j.pop.2012.06.013.

Gerrits, Marloes M.J.G., Harm W.J. van Marwijk, Patricia van Oppen, Henriëtte van der Horst, and Brenda W.J.H. Penninx. 2015. “Longitudinal Association between Pain, and Depression and Anxiety over Four Years.” Journal of Psychosomatic Research 78 (1): 64–70. https://doi.org/10.1016/j.jpsychores.2014.10.011.

Gierthmühlen, Janne, and Ralf Baron. 2016. “Neuropathic Pain.” Seminars in Neurology 36 (05): 462–68. https://doi.org/10.1055/s-0036-1584950.

Gilbertson, Mark W., Martha E. Shenton, Aleksandra Ciszewski, Kiyoto Kasai, Natasha B. Lasko, Scott P. Orr, and Roger K. Pitman. 2002. “Smaller Hippocampal Volume Predicts Pathologic Vulnerability to Psychological Trauma.” Nature Neuroscience 5 (11): 1242–47. https://doi.org/10.1038/nn958.

Glare, Paul, Karin R. Aubrey, and Paul S. Myles. 2019. “Transition from Acute to Chronic Pain after Surgery.” The Lancet 393 (10180): 1537–46. https://doi.org/10.1016/S0140-6736(19)30352-6.

Golden, Lisa C., and Rhonda Voskuhl. 2017. “The Importance of Studying Sex Differences in Disease: The Example of Multiple Sclerosis.” Journal of Neuroscience Research 95 (1–2): 633– 43. https://doi.org/10.1002/jnr.23955.

Gould, E., A. Westlind-Danielsson, M. Frankfurt, and B. S. McEwen. 1990. “Sex Differences and Thyroid Hormone Sensitivity of Hippocampal Pyramidal Cells.” Journal of Neuroscience 10 (3): 996–1003. https://doi.org/10.1523/jneurosci.10-03-00996.1990.

Gould, E., Catherine S. Woolley, Maya Frankfurt, and Bruce S. McEwen. 1990. “Gonadal Steroids Regulate Dendritic Spine Density in Hippocampal Pyramidal Cells in Adulthood.” Journal of Neuroscience 10 (4): 1286–91. https://doi.org/10.1523/jneurosci.10-04-01286.1990.

REFERENCES 113

Graven-Nielsen, Thomas, and Lars Arendt-Nielsen. 2002. “Peripheral and Central Sensitization in Musculoskeletal Pain Disorders: An Experimental Approach.” Current Rheumatology Reports 4 (4): 313–21. https://doi.org/10.1007/s11926-002-0040-y.

Greenspan, Joel D., Rebecca M. Craft, Linda LeResche, Lars Arendt-Nielsen, Karen J. Berkley, Roger B. Fillingim, Michael S. Gold, et al. 2007. “Studying Sex and Gender Differences in Pain and Analgesia: A Consensus Report.” Pain 132 (SUPPL. 1): S26-45. https://doi.org/10.1016/j.pain.2007.10.014.

Grilli, Mariagrazia. 2017. “Chronic Pain and Adult Hippocampal Neurogenesis: Translational Implications from Preclinical Studies.” Journal of Pain Research 10 (September): 2281–86. https://doi.org/10.2147/JPR.S146399.

Grisart, Jacques, Martial Van Der Linden, and Etienne Masquelier. 2002. “Controlled Processes and Automaticity in Memory Functioning in Fibromyalgia Patients: Relation with Emotional Distress and Hypervigilance.” Journal of Clinical and Experimental Neuropsychology 24 (8): 994–1009. https://doi.org/10.1076/jcen.24.8.994.8380.

Grisart, Jacques M., and Martial Van der Linden. 2001. “Conscious and Automatic Uses of Memory in Chronic Pain Patients.” Pain 94 (3): 305–13. https://doi.org/10.1016/S0304-3959(01)00366- 9.

Gronseth, G., G. Cruccu, J. Alksne, C. Argoff, M. Brainin, K. Burchiel, T. Nurmikko, and J. M. Zakrzewska. 2008. “Practice Parameter: The Diagnostic Evaluation and Treatment of Trigeminal Neuralgia (an Evidence-Based Review): Report of the Quality Standards Subcommittee of the American Academy of Neurology and the European Federation of Neurological Societies.” Neurology 71 (15): 1183–90. https://doi.org/10.1212/01.wnl.0000326598.83183.04.

Grover, Vijay P.B., Joshua M. Tognarelli, Mary M.E. Crossey, I. Jane Cox, Simon D. Taylor- Robinson, and Mark J.W. McPhail. 2015. “Magnetic Resonance Imaging: Principles and Techniques: Lessons for Clinicians.” Journal of Clinical and Experimental Hepatology 5 (3): 246–55. https://doi.org/10.1016/j.jceh.2015.08.001.

Guadalupe, Tulio, Samuel R. Mathias, Theo G. M. vanErp, Christopher D. Whelan, Marcel P. Zwiers, Yoshinari Abe, Lucija Abramovic, et al. 2017. “Human Subcortical Brain Asymmetries in 15,847 People Worldwide Reveal Effects of Age and Sex.” Brain Imaging and Behavior 11 (5): 1497–1514. https://doi.org/10.1007/s11682-016-9629-z.

Gureje, Oye, Michael Von Korff, Lola Kola, Koen Demyttenaere, Yanling He, José Posada-Villa, Jean Pierre Lepine, et al. 2008. “The Relation between Multiple Pains and Mental Disorders: Results from the World Mental Health Surveys.” Pain 135 (1–2): 82–91. https://doi.org/10.1016/j.pain.2007.05.005.

Gutiérrez-Lobos, Karin, Michael Scherer, Peter Anderer, and Heinz Katschnig. 2002. “The Influence of Age on the Female/Male Ratio of Treated Incidence Rates in Depression.” BMC Psychiatry 2

REFERENCES 114

(January): 3. https://doi.org/10.1186/1471-244X-2-3.

Gwilym, Stephen E., Nicola Filippini, Gwenaelle Douaud, Andrew J. Carr, and Irene Tracey. 2010. “Thalamic Atrophy Associated with Painful Osteoarthritis of the Hip Is Reversible after Arthroplasty: A Longitudinal Voxel-Based Morphometric Study.” Arthritis and Rheumatism 62 (10): 2930–40. https://doi.org/10.1002/art.27585.

Haines, S. J., P. J. Jannetta, and D. S. Zorub. 1980. “Microvascular Relations of the Trigeminal Nerve. An Anatomical Study with Clinical Correlation.” Journal of Neurosurgery 52 (3): 381– 86. https://doi.org/10.3171/jns.1980.52.3.0381.

Haneef, Zulfi, Harvey S. Levin, and Sharon Chiang. 2015. “Brain Graph Topology Changes Associated with Anti-Epileptic Drug Use.” Brain Connectivity 5 (5): 284–91. https://doi.org/10.1089/brain.2014.0304.

Hannula, Deborah E., and Melissa C. Duff. 2017. The Hippocampus from Cells to Systems: Structure, Connectivity, and Functional Contributions to Memory and Flexible Cognition. Edited by Deborah E Hannula and Melissa C. Duff. Springer. Springer International Publishing. https://doi.org/10.1007/978-3-319-50406-3.

Harifi, Ghita, Mohamed Amine, Mariam Ait Ouazar, Asmae Boujemaoui, Imane Ouilki, Imane Rekkab, Ahlam Belkhou, Imane El Bouchti, Redouane Niamane, and Selma El Hassani. 2013. “Prevalence of Chronic Pain with Neuropathic Characteristics in the Moroccan General Population: A National Survey.” Pain Medicine (United States) 14 (2): 287–92. https://doi.org/10.1111/pme.12009.

Harry, G. Jean, and Christian Lefebvre D’Hellencourt. 2003. “Dentate Gyrus: Alterations That Occur with Hippocampal Injury.” NeuroToxicology 24 (3): 343–56. https://doi.org/10.1016/S0161- 813X(03)00039-1.

Harte-Hargrove, Lauren C., Ada Varga-Wesson, Aine M. Duffy, Teresa A. Milner, and Helen E. Scharfman. 2015. “Opioid Receptor-Dependent Sex Differences in Synaptic Plasticity in the Hippocampal Mossy Fiber Pathway of the Adult Rat.” Journal of Neuroscience 35 (4): 1723– 38. https://doi.org/10.1523/JNEUROSCI.0820-14.2015.

Hashmi, Javeria A., and Karen D. Davis. 2009. “Women Experience Greater Heat Pain Adaptation and Habituation than Men.” Pain 145 (3): 350–57. https://doi.org/10.1016/j.pain.2009.07.002.

———. 2010a. “Noxious Heat Evokes Stronger Sharp and Annoying Sensations in Women than Men in Hairy Skin but Not in Glabrous Skin.” Pain 151 (2): 323–29. https://doi.org/10.1016/j.pain.2010.06.026.

———. 2010b. “Effects of Temperature on Heat Pain Adaptation and Habituation in Men and Women.” Pain 151 (3): 737–43. https://doi.org/10.1016/j.pain.2010.08.046.

REFERENCES 115

———. 2014. “Deconstructing Sex Differences in Pain Sensitivity.” Pain 155 (1): 10–13. https://doi.org/10.1016/j.pain.2013.07.039.

Haughey, Norman J., Avi Nath, Sic L. Chan, A. C. Borchard, Mahendra S. Rao, and Mark P. Mattson. 2002. “Disruption of Neurogenesis by Amyloid β-Peptide, and Perturbed Neural Progenitor Cell Homeostasis, in Models of Alzheimer’s Disease.” Journal of Neurochemistry 83 (6): 1509–24. https://doi.org/10.1046/j.1471-4159.2002.01267.x.

Hayes, Dave J., David Q. Chen, Jidan Zhong, Ariel Lin, Brendan Behan, Matthew Walker, and Mojgan Hodaie. 2017. “Affective Circuitry Alterations in Patients with Trigeminal Neuralgia.” Frontiers in Neuroanatomy 11 (September). https://doi.org/10.3389/fnana.2017.00073.

“Headache Classification Committee of the International Headache Society (IHS) The International Classification of Headache Disorders, 3rd Edition.” 2018. Cephalalgia : An International Journal of Headache 38 (1): 1–211. https://doi.org/10.1177/0333102417738202.

Heer, Eric W. De, Marloes M.J.G. Gerrits, Aartjan T.F. Beekman, Jack Dekker, Harm W.J. Van Marwijk, Margot W.M. De Waal, Philip Spinhoven, Brenda W.J.H. Penninx, and Christina M. Van Der Feltz-Cornelis. 2014. “The Association of Depression and Anxiety with Pain: A Study from NESDA.” PLoS ONE 9 (10). https://doi.org/10.1371/journal.pone.0106907.

Henke, Peter G. 1982. “The Telencephalic Limbic System and Experimental Gastric Pathology: A Review.” Neuroscience and Biobehavioral Reviews 6 (3): 381–90. https://doi.org/10.1016/0149- 7634(82)90047-1.

Henry, Douglas E., Anthony E. Chiodo, and Weibin Yang. 2011. “Central Nervous System Reorganization in a Variety of Chronic Pain States: A Review.” PM and R 3 (12): 1116–25. https://doi.org/10.1016/j.pmrj.2011.05.018.

Henze, D. A., N. N. Urban, and G. Barrionuevo. 2000. “The Multifarious Hippocampal Mossy Fiber Pathway: A Review.” Neuroscience 98 (3): 407–27. https://doi.org/10.1016/S0306- 4522(00)00146-9.

Hillerer, Katharina M., Inga D. Neumann, Sebastien Couillard-Despres, Ludwig Aigner, and David A. Slattery. 2013a. “Sex-Dependent Regulation of Hippocampal Neurogenesis under Basal and Chronic Stress Conditions in Rats.” Hippocampus 23 (6): 476–87. https://doi.org/10.1002/hipo.22107.

———. 2013b. “Sex-Dependent Regulation of Hippocampal Neurogenesis under Basal and Chronic Stress Conditions in Rats.” Hippocampus 23 (6): 476–87. https://doi.org/10.1002/hipo.22107.

Hilton, David A., Seth Love, Terry Gradidge, and Hugh B. Coakham. 1994. “Pathological Findings Associated with Trigeminal Neuralgia Caused by Vascular Compression.” Neurosurgery 35 (2): 299–303. https://doi.org/10.1227/00006123-199408000-00017.

REFERENCES 116

Hockfield, Susan, and Stephen Gobel. 1982. “An Anatomical Demonstration of Projections to the Medullary Dorsal Horn (Trigeminal Nucleus Caudalis) from Rostral Trigeminal Nuclei and the Contralateral Caudal Medulla.” Brain Research 252 (2): 203–11. https://doi.org/10.1016/0006- 8993(82)90388-2.

Hodaie, M, and A F Coello. 2013. “Advances in the Management of Trigeminal Neuralgia.” Journal of Neurosurgical Sciences 57 (1): 13–21. http://www.ncbi.nlm.nih.gov/pubmed/23584217.

Hu, James W, and Alain Woda. 2013. “Trigeminal Brainstem Nuclear Complex, Physiology BT - Encyclopedia of Pain.” In , edited by Gerald F Gebhart and Robert F Schmidt, 4060–65. Berlin, Heidelberg: Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-28753-4_4604.

Hubbard, Catherine S., Shariq A. Khan, Michael L. Keaser, David A. Seminowicz, Vani A. Mathur, and Madhav Goyal. 2014. “Altered Brain Structure and Function Correlate with Disease Severity and Pain Catastrophizing in Migraine Patients.” ENeuro 1 (1). https://doi.org/10.1523/ENEURO.0006-14.2014.

Hucho, Tim, and Jon D. Levine. 2007. “Signaling Pathways in Sensitization: Toward a Nociceptor Cell Biology.” Neuron 55 (3): 365–76. https://doi.org/10.1016/j.neuron.2007.07.008.

Hung, Peter S.P., David Q. Chen, Karen D. Davis, Jidan Zhong, and Mojgan Hodaie. 2017. “Predicting Pain Relief: Use of Pre-Surgical Trigeminal Nerve Diffusion Metrics in Trigeminal Neuralgia.” NeuroImage: Clinical 15 (January): 710–18. https://doi.org/10.1016/j.nicl.2017.06.017.

Hung, Peter S.P., Sarasa Tohyama, Jia Y. Zhang, and Mojgan Hodaie. 2019. “Temporal Disconnection between Pain Relief and Trigeminal Nerve Microstructural Changes after Gamma Knife Radiosurgery for Trigeminal Neuralgia.” Journal of Neurosurgery, July, 1–9. https://doi.org/10.3171/2019.4.jns19380.

Hunsaker, Michael R., and Raymond P. Kesner. 2008. “Evaluating the Differential Roles of the Dorsal Dentate Gyrus, Dorsal CA3, and Dorsal CA1 during a Temporal Ordering for Spatial Locations Task.” Hippocampus 18 (9): 955–64. https://doi.org/10.1002/hipo.20455.

Hurley, Robert W., and Meredith C.B. Adams. 2008. “Sex, Gender, and Pain: An Overview of a Complex Field.” Anesthesia and Analgesia 107 (1): 309–17. https://doi.org/10.1213/01.ane.0b013e31816ba437.

Iglesias, Juan Eugenio, Jean C. Augustinack, Khoa Nguyen, Christopher M. Player, Allison Player, Michelle Wright, Nicole Roy, et al. 2015. “A Computational Atlas of the Hippocampal Formation Using Ex Vivo, Ultra-High Resolution MRI: Application to Adaptive Segmentation of in Vivo MRI.” NeuroImage 115 (July): 117–37. https://doi.org/10.1016/j.neuroimage.2015.04.042.

Iglesias, Juan Eugenio, Koen Van Leemput, Jean Augustinack, R. Insausti, Bruce Fischl, and Martin

REFERENCES 117

Reuter. 2016. “Bayesian Longitudinal Segmentation of Hippocampal Substructures in Brain MRI Using Subject-Specific Atlases.” NeuroImage 141 (November): 542–55. https://doi.org/10.1016/j.neuroimage.2016.07.020.

Ingalhalikar, Madhura, Alex Smith, Drew Parker, Theodore D. Satterthwaite, Mark A. Elliott, Kosha Ruparel, Hakon Hakonarson, Raquel E. Gur, Ruben C. Gur, and Ragini Verma. 2014. “Sex Differences in the Structural Connectome of the Human Brain.” Proceedings of the National Academy of Sciences of the United States of America 111 (2): 823–28. https://doi.org/10.1073/pnas.1316909110.

Inoue, Kazuhide, and Makoto Tsuda. 2018. “Microglia in Neuropathic Pain: Cellular and Molecular Mechanisms and Therapeutic Potential.” Nature Reviews Neuroscience 19 (3): 138–52. https://doi.org/10.1038/nrn.2018.2.

Insausti, R., and David G. Amaral. 2008. “Entorhinal Cortex of the Monkey: IV. Topographical and Laminar Organization of Cortical Afferents.” Journal of Comparative Neurology 509 (6): 608– 41. https://doi.org/10.1002/cne.21753.

———. 2012. “Hippocampal Formation.” In The Human Nervous System, edited by George Paxinos and Juergen Mai, 896–942. Elsevier Inc. https://doi.org/10.1016/B978-0-12-374236-0.10024-0.

Insausti, R., T. Tuñón, T. Sobreviela, A. M. Insausti, and L. M. Gonzalo. 1995. “The Human Entorhinal Cortex: A Cytoarchitectonic Analysis.” Journal of Comparative Neurology 355 (2): 171–98. https://doi.org/10.1002/cne.903550203.

Iosif, Robert E., Christine T. Ekdahl, Henrik Ahlenius, Cornelis J.H. Pronk, Sara Bonde, Zaal Kokaia, Sten Eirik W. Jacobsen, and Olle Lindvall. 2006. “Tumor Necrosis Factor Receptor 1 Is a Negative Regulator of Progenitor Proliferation in Adult Hippocampal Neurogenesis.” Journal of Neuroscience 26 (38): 9703–12. https://doi.org/10.1523/JNEUROSCI.2723-06.2006.

Jannetta, P. J. 1967. “Gross (Mesoscopic) Description of the Human Trigeminal Nerve and Ganglion.” Journal of Neurosurgery 26 (1). https://doi.org/10.3171/jns.1967.26.1part2.0109.

Jannetta, P J. 1985. “Microsurgical Management of Trigeminal Neuralgia.” Archives of Neurology 42 (8): 800. https://doi.org/10.1001/archneur.1985.04210090068018.

Jensen, Mark P., and Candace A. McFarland. 1993. “Increasing the Reliability and Validity of Pain Intensity Measurement in Chronic Pain Patients.” Pain 55 (2): 195–203. https://doi.org/10.1016/0304-3959(93)90148-I.

Ji, Guangchen, Hao Sun, Yu Fu, Zhen Li, Miguel Pais-Vieira, Vasco Galhardo, and Volker Neugebauer. 2010. “Cognitive Impairment in Pain through Amygdala-Driven Prefrontal Cortical Deactivation.” Journal of Neuroscience 30 (15): 5451–64. https://doi.org/10.1523/JNEUROSCI.0225-10.2010.

REFERENCES 118

Ji, Ru Rong, and Marc R. Suter. 2007. “P38 MAPK, Microglial Signaling, and Neuropathic Pain.” Molecular Pain 3 (November): 33. https://doi.org/10.1186/1744-8069-3-33.

Joel, Daphna, Zohar Berman, Ido Tavor, Nadav Wexler, Olga Gaber, Yaniv Stein, Nisan Shefi, et al. 2015. “Sex beyond the Genitalia: The Human Brain Mosaic.” Proceedings of the National Academy of Sciences of the United States of America 112 (50): 15468–73. https://doi.org/10.1073/pnas.1509654112.

Kälin, Andrea M., Min T.M. Park, M. Mallar Chakravarty, Jason P. Lerch, Lars Michels, Clemens Schroeder, Sarah D. Broicher, et al. 2017. “Subcortical Shape Changes, Hippocampal Atrophy and Cortical Thinning in Future Alzheimer’s Disease Patients.” Frontiers in Aging Neuroscience 9 (MAR). https://doi.org/10.3389/fnagi.2017.00038.

Kallarackal, Angy J., Mark D. Kvarta, Erin Cammarata, Leelah Jaberi, Xiang Cai, Aileen M. Bailey, and Scott M. Thompson. 2013. “Chronic Stress Induces a Selective Decrease in AMPA Receptor-Mediated Synaptic Excitation at Hippocampal Temporoammonic-CA1 Synapses.” Journal of Neuroscience 33 (40): 15669–74. https://doi.org/10.1523/JNEUROSCI.2588- 13.2013.

Kansaku, Kenji, Akira Yamaura, and Shigeru Kitazawa. 2000. “Sex Differences in Lateralization Revealed in the Posterior Language Areas.” Cerebral Cortex 10 (9): 866–72. https://doi.org/10.1093/cercor/10.9.866.

Karam, Sana D., Alexander Tai, Margaux Wooster, Abdul Rashid, Rosanna Chen, Nimrah Baig, Ann Jay, et al. 2014. “Trigeminal Neuralgia Treatment Outcomes Following Gamma Knife Radiosurgery with a Minimum 3-Year Follow-Up.” Journal of Radiation Oncology 3 (2): 125– 30. https://doi.org/10.1007/s13566-013-0134-3.

Katusic, S, D B Williams, C M Beard, E J Bergstralh, and L T Kurland. 1991. “Epidemiology and Clinical Features of Idiopathic Trigeminal Neuralgia and Glossopharyngeal Neuralgia: Similarities and Differences, Rochester, Minnesota, 1945-1984.” Neuroepidemiology 10 (5–6): 276–81. https://doi.org/10.1159/000110284.

Kendroud, Sarah, and Steve S. Bhimji. 2018. Physiology, Nociceptive Pathways. Edited by StatPearls [Internet]. StatPearls. StatPearls Publishing. http://www.ncbi.nlm.nih.gov/pubmed/29262164.

Kesner, Raymond P., and Michael R. Hunsaker. 2010. “The Temporal Attributes of Episodic Memory.” Behavioural Brain Research 215 (2): 299–309. https://doi.org/10.1016/j.bbr.2009.12.029.

Khan, Shariq A., Michael L. Keaser, Timothy F. Meiller, and David A. Seminowicz. 2014. “Altered Structure and Function in the Hippocampus and Medial Prefrontal Cortex in Patients with Burning Mouth Syndrome.” Pain 155 (8): 1472–80. https://doi.org/10.1016/j.pain.2014.04.022.

Khanna, S. 1997. “Dorsal Hippocampus Field CA1 Pyramidal Cell Responses to a Persistent versus

REFERENCES 119

an Acute Nociceptive Stimulus and Their Septal Modulation.” Neuroscience 77 (3): 713–21. https://doi.org/10.1016/S0306-4522(96)00456-3.

Khanna, S., and John G. Sinclair. 1989. “Noxious Stimuli Produce Prolonged Changes in the CA1 Region of the Rat Hippocampus.” Pain 39 (3): 337–43. https://doi.org/10.1016/0304- 3959(89)90047-X.

Kim, Eun Joo, Blake Pellman, and Jeansok J. Kim. 2015. “Stress Effects on the Hippocampus: A Critical Review.” Learning and Memory 22 (9): 411–16. https://doi.org/10.1101/lm.037291.114.

Kim, Jeansok J., and David M. Diamond. 2002. “The Stressed Hippocampus, Synaptic Plasticity and Lost Memories.” Nature Reviews Neuroscience 3 (6): 453–62. https://doi.org/10.1038/nrn849.

Kim, Jeansok J., Hongjoo J. Lee, Adam C. Welday, Eun Young Song, Jeiwon Cho, Patricia E. Sharp, Min W. Jung, and Hugh T. Blair. 2007. “Stress-Induced Alterations in Hippocampal Plasticity, Place Cells, and Spatial Memory.” Proceedings of the National Academy of Sciences of the United States of America 104 (46): 18297–302. https://doi.org/10.1073/pnas.0708644104.

Kim, Soyun, Adam J.O. Dede, Ramona O. Hopkins, and Larry R. Squire. 2015. “Memory, Scene Construction, and the Human Hippocampus.” Proceedings of the National Academy of Sciences of the United States of America 112 (15): 4767–72. https://doi.org/10.1073/pnas.1503863112.

Kitayama, Noriyuki, Viola Vaccarino, Michael Kutner, Paul Weiss, and J. Douglas Bremner. 2005. “Magnetic Resonance Imaging (MRI) Measurement of Hippocampal Volume in Posttraumatic Stress Disorder: A Meta-Analysis.” Journal of Affective Disorders 88 (1): 79–86. https://doi.org/10.1016/j.jad.2005.05.014.

Kjelstrup, Kirsten G., Frode A. Tuvnes, Hill Aina Steffenach, Robert Murison, Edvard I. Moser, and May Britt Moser. 2002. “Reduced Fear Expression after Lesions of the Ventral Hippocampus.” Proceedings of the National Academy of Sciences of the United States of America 99 (16): 10825–30. https://doi.org/10.1073/pnas.152112399.

Knierim, James J. 2015. “The Hippocampus.” Current Biology 25 (23): R1116–21. https://doi.org/10.1016/j.cub.2015.10.049.

Kodama, Daisuke, Hideki Ono, and Mitsuo Tanabe. 2007. “Altered Hippocampal Long-Term Potentiation after Peripheral Nerve Injury in Mice.” European Journal of Pharmacology 574 (2–3): 127–32. https://doi.org/10.1016/j.ejphar.2007.07.054.

———. 2011. “Increased Hippocampal Glycine Uptake and Cognitive Dysfunction after Peripheral Nerve Injury.” Pain 152 (4): 809–17. https://doi.org/10.1016/j.pain.2010.12.029.

Köhler, Christer. 1985. “A Projection from the Deep Layers of the Entorhinal Area to the Hippocampal Formation in the Rat Brain.” Neuroscience Letters 56 (1): 13–19. https://doi.org/10.1016/0304-3940(85)90433-1.

REFERENCES 120

Kondo, Hideki, Pierre Lavenex, and David G. Amaral. 2008. “Intrinsic Connections of the Macaque Monkey Hippocampal Formation: I. Dentate Gyrus.” Journal of Comparative Neurology 511 (4): 497–520. https://doi.org/10.1002/cne.21825.

Kondziolka, Douglas, Oscar Zorro, Javier Lobato-Polo, Hideyuki Kano, Thomas J. Flannery, John C. Flickinger, and L. Dade Lunsford. 2010. “Gamma Knife Stereotactic Radiosurgery for Idiopathic Trigeminal Neuralgia.” Journal of Neurosurgery 112 (4): 758–65. https://doi.org/10.3171/2009.7.JNS09694.

Korczeniewska, Olga, Junad Khan, Yuanxiang Tao, Eli Eliav, and Rafael Benoliel. 2017. “Effects of Sex and Stress on Trigeminal Neuropathic Pain-Like Behavior in Rats.” Journal of Oral & Facial Pain and Headache 31 (4): 381–97. https://doi.org/10.11607/ofph.1807.

Kröner-Herwig, Birgit, Jennifer Gaßmann, Marie Tromsdorf, and Elfi Zahrend. 2012. “Die Auswirkungen Des Biologischen Geschlechts Und Der Geschlechterrolle Auf Druckschmerz.” GMS Psycho-Social-Medicine 9: 1–10. https://doi.org/10.3205/psm000079.

Kruschke, John K. 2013. “Bayesian Estimation Supersedes the t Test.” Journal of Experimental Psychology: General 142 (2): 573–603. https://doi.org/10.1037/a0029146.

Kulaga-Yoskovitz, Jessie, Boris C. Bernhardt, Seok Jun Hong, Tommaso Mansi, Kevin E. Liang, Andre J.W. Van Der Kouwe, Jonathan Smallwood, Andrea Bernasconi, and Neda Bernasconi. 2015. “Multi-Contrast Submillimetric 3 Tesla Hippocampal Subfield Segmentation Protocol and Dataset.” Scientific Data 2 (November). https://doi.org/10.1038/sdata.2015.59.

Kumar, S, S Rastogi, P Mahendra, M Bansal, and L Chandra. 2013. “Pain in Trigeminal Neuralgia: Neurophysiology and Measurement: A Comprehensive Review.” Journal of Medicine and Life 6 (4): 383–88. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3973876&tool=pmcentrez&renderty pe=abstract.

Lange, E. E. De, G J Vielvoye, and H. J.C. Voormolen. 1986. “Arterial Compression of the Fifth Cranial Nerve Causing Trigemenal Neuralgia: Angiographic Findings.” Radiology 158 (3): 721–27. https://doi.org/10.1148/radiology.158.3.3945746.

Latremoliere, Alban, and Clifford J. Woolf. 2009. “Central Sensitization: A Generator of Pain Hypersensitivity by Central Neural Plasticity.” Journal of Pain 10 (9): 895–926. https://doi.org/10.1016/j.jpain.2009.06.012.

Laurberg, S., and K. E. Sørensen. 1981. “Associational and Commissural Collaterals of Neurons in the Hippocampal Formation (Hilus Fasciae Dentatae and Subfield CA3).” Brain Research 212 (2): 287–300. https://doi.org/10.1016/0006-8993(81)90463-7.

Leclercq, D., J. B. Thiebaut, and F. Héran. 2013. “Trigeminal Neuralgia.” Diagnostic and Interventional Imaging 94 (10): 993–1001. https://doi.org/10.1016/j.diii.2013.08.002.

REFERENCES 121

Li, Shi Ting, Qinggang Pan, Ningtao Liu, Feng Shen, Zhong Liu, Yuhang Guan, Marc Sindou, and Kim J. Burchiel. 2004. “Trigeminal Neuralgia: What Are the Important Factors for Good Operative Outcomes with Microvascular Decompression.” Surgical Neurology 62 (5): 400–404. https://doi.org/10.1016/j.surneu.2004.02.028.

Libby, Laura A., Arne D. Ekstrom, J. Daniel Ragland, and Charan Ranganath. 2012. “Differential Connectivity of Perirhinal and Parahippocampal Cortices within Human Hippocampal Subregions Revealed by High-Resolution Functional Imaging.” Journal of Neuroscience 32 (19): 6550–60. https://doi.org/10.1523/JNEUROSCI.3711-11.2012.

Ling, Jonathan, Carol Campbell, Thomas M. Heffernan, and Charles G. Greenough. 2007. “Short- Term Prospective Memory Deficits in Chronic Back Pain Patients.” Psychosomatic Medicine 69 (2): 144–48. https://doi.org/10.1097/PSY.0b013e31802e0f22.

Lisman, John E. 1999. “Relating Hippocampal Circuitry to Function: Recall of Memory Sequences by Reciprocal Dentate-CA3 Interactions.” Neuron 22 (2): 233–42. https://doi.org/10.1016/S0896-6273(00)81085-5.

Liu, Jixin, Lei Lan, Junya Mu, Ling Zhao, Kai Yuan, Yi Zhang, Liyu Huang, Fanrong Liang, and Jie Tian. 2015. “Genetic Contribution of Catechol-O-Methyltransferase in Hippocampal Structural and Functional Changes of Female Migraine Sufferers.” Human Brain Mapping 36 (5): 1782– 95. https://doi.org/10.1002/hbm.22737.

Liu, Ming Gang, and Jun Chen. 2009. “Roles of the Hippocampal Formation in Pain Information Processing.” Neuroscience Bulletin 25 (5): 237–66. https://doi.org/10.1007/s12264-009-0905-4.

Liu, Yong, Li Jun Zhou, Jun Wang, Dai Li, Wen Jie Ren, Jiyun Peng, Xiao Wei, et al. 2017. “TNF-α Differentially Regulates Synaptic Plasticity in the Hippocampus and Spinal Cord by Microglia- Dependent Mechanisms after Peripheral Nerve Injury.” Journal of Neuroscience 37 (4): 871–81. https://doi.org/10.1523/JNEUROSCI.2235-16.2016.

Lledo, Pierre Marie, Mariana Alonso, and Matthew S. Grubb. 2006. “Adult Neurogenesis and Functional Plasticity in Neuronal Circuits.” Nature Reviews Neuroscience 7 (3): 179–93. https://doi.org/10.1038/nrn1867.

Lloyd, Amy F., and Veronique E. Miron. 2019. “The Pro-Remyelination Properties of Microglia in the Central Nervous System.” Nature Reviews Neurology 15 (8): 447–58. https://doi.org/10.1038/s41582-019-0184-2.

Loeser, John D, and Ronald Melzack. 1999. “Pain: An Overview.” Lancet 353 (9164): 1607–9. https://doi.org/10.1016/S0140-6736(99)01311-2.

Love, Seth, and Hugh B. Coakham. 2001. “Trigeminal Neuralgia: Pathology and Pathogenesis.” Brain 124 (12): 2347–60. https://doi.org/10.1093/brain/124.12.2347.

REFERENCES 122

Lucia, Chiara De, Adeline Rinchon, Adrian Olmos-Alonso, Kristoffer Riecken, Boris Fehse, Delphine Boche, V. Hugh Perry, and Diego Gomez-Nicola. 2016. “Microglia Regulate Hippocampal Neurogenesis during Chronic Neurodegeneration.” Brain, Behavior, and Immunity 55 (July): 179–90. https://doi.org/10.1016/j.bbi.2015.11.001.

Lynch, M. A. 2004. “Long-Term Potentiation and Memory.” Physiological Reviews 84 (1): 87–136. https://doi.org/10.1152/physrev.00014.2003.

M Heir, Gary, and Eli Eliav. 2008. “Neuropathic Orofacial Pain.” In Orofacial Pain and Headache, edited by Yavir Sharav and Rafael Benoliel, 255–94. Elsevier Ltd. https://doi.org/10.1016/B978-0-7234-3412-2.10011-2.

Maarbjerg, Stine, Aydin Gozalov, Jes Olesen, and Lars Bendtsen. 2014. “Trigeminal Neuralgia--a Prospective Systematic Study of Clinical Characteristics in 158 Patients.” Headache 54 (10): 1574–82. https://doi.org/10.1111/head.12441.

MacDonald, B. K. 2000. “The Incidence and Lifetime Prevalence of Neurological Disorders in a Prospective Community-Based Study in the UK.” Brain 123 (4): 665–76. https://doi.org/10.1093/brain/123.4.665.

Maggi, Sergio P., James B. Lowe, and Susan E. Mackinnon. 2003. “Pathophysiology of Nerve Injury.” Clinics in Plastic Surgery 30 (2): 109–26. https://doi.org/10.1016/S0094- 1298(02)00101-3.

Maleki, Nasim, Lino Becerra, Jennifer Brawn, Bruce McEwen, Rami Burstein, and David Borsook. 2013. “Common Hippocampal Structural and Functional Changes in Migraine.” Brain Structure and Function 218 (4): 903–12. https://doi.org/10.1007/s00429-012-0437-y.

Maletic, Vladimir, and Charles L. Raison. 2009. “Neurobiology of Depression, Fibromyalgia and Neuropathic Pain.” Frontiers in Bioscience 14 (14): 5291–5338. https://doi.org/10.2741/3598.

Malinowski, Mark N. 2019. “Mediators of Pain and Pain Processing.” In Deer’s Treatment of Pain, edited by T. Deer, J. Pope, T. Lamer, and D. Provenzano, 61–73. Springer, Cham. https://doi.org/10.1007/978-3-030-12281-2_8.

Mansour, A. R., M. A. Farmer, M. N. Baliki, and A. Vania Apkarian. 2014. “Chronic Pain: The Role of Learning and Brain Plasticity.” Restorative Neurology and Neuroscience 32 (1): 129–39. https://doi.org/10.3233/RNN-139003.

Maren, Stephen, Beatrice De Oca, and Michael S. Fanselow. 1994. “Sex Differences in Hippocampal Long-Term Potentiation (LTP) and Pavlovian Fear Conditioning in Rats: Positive Correlation between LTP and Contextual Learning.” Brain Research 661 (1–2): 25–34. https://doi.org/10.1016/0006-8993(94)91176-2.

Martin, John. 2012. Neuroanatomy Text and Atlas. Edited by Eric R. Kandel, James H. Schwartz,

REFERENCES 123

Jessel Jessell, Steven A. Siegelbaum, and A. James Hudspeth. 4th ed. McGraw-Hill.

Martínez Moreno, Nuria E., Jorge Gutiérrez-Sárraga, Germán Rey-Portolés, Adolfo Jiménez-Huete, and Roberto Martínez Álvarez. 2016. “Long-Term Outcomes in the Treatment of Classical Trigeminal Neuralgia by Gamma Knife Radiosurgery.” Neurosurgery 79 (6): 879–88. https://doi.org/10.1227/NEU.0000000000001404.

Martuscello, Regina T., Robert N. Spengler, Adela C. Bonoiu, Bruce A. Davidson, Jadwiga Helinski, Hong Ding, Supriya Mahajan, et al. 2012. “Increasing TNF Levels Solely in the Rat Hippocampus Produces Persistent Pain-like Symptoms.” Pain 153 (9): 1871–82. https://doi.org/10.1016/j.pain.2012.05.028.

Mazza, Stéphanie, Maud Frot, and Amandine E. Rey. 2018. “A Comprehensive Literature Review of Chronic Pain and Memory.” Progress in Neuro-Psychopharmacology and Biological Psychiatry 87 (December): 183–92. https://doi.org/10.1016/J.PNPBP.2017.08.006.

McCarberg, Bill, and John Peppin. 2019. “Pain Pathways and Nervous System Plasticity: Learning and Memory in Pain.” Pain Medicine 20 (12): 2421–37. https://doi.org/10.1093/pm/pnz017.

McEwen, Bruce S., and Madhu Kalia. 2010a. “The Role of Corticosteroids and Stress in Chronic Pain Conditions.” Metabolism: Clinical and Experimental. https://doi.org/10.1016/j.metabol.2010.07.012.

———. 2010b. “The Role of Corticosteroids and Stress in Chronic Pain Conditions.” Metabolism: Clinical and Experimental 59 (SUPPL. 1). https://doi.org/10.1016/j.metabol.2010.07.012.

McEwen, Bruce S., and Robert M. Sapolsky. 1995. “Stress and Cognitive Function.” Current Opinion in Neurobiology 5 (2): 205–16. https://doi.org/10.1016/0959-4388(95)80028-X.

McKnight, Patrick E., and Julius Najab. 2010. “Mann-Whitney U Test.” In The Corsini Encyclopedia of Psychology, edited by I.B. Weiner and W.E. Craighead, 1–1. Hoboken, NJ, USA: John Wiley & Sons, Inc. https://doi.org/10.1002/9780470479216.corpsy0524.

McLaughlin, Mark R., Peter J. Jannetta, Brent L. Clyde, Brian R. Subach, Christopher H. Comey, and Daniel K. Resnick. 1999. “Microvascular Decompression of Cranial Nerves: Lessons Learned after 4400 Operations.” Journal of Neurosurgery 90 (1): 1–8. https://doi.org/10.3171/jns.1999.90.1.0001.

McPherson, Susan, Carla Back, J. Galen Buckwalter, and Jeffrey L. Cummings. 1999. “Gender- Related Cognitive Deficits in Alzheimer’s Disease.” International Psychogeriatrics 11 (2): 117– 22. https://doi.org/10.1017/S1041610299005670.

McWilliams, Lachlan A., Brian J. Cox, and Murray W. Enns. 2003. “Mood and Anxiety Disorders Associated with Chronic Pain: An Examination in a Nationally Representative Sample.” Pain 106 (1–2): 127–33. https://doi.org/10.1016/S0304-3959(03)00301-4.

REFERENCES 124

Meibach, Richard C., and Allan Siegel. 1977. “Efferent Connections of the Hippocampal Formation in the Rat.” Brain Research 124 (2): 197–224. https://doi.org/10.1016/0006-8993(77)90880-0.

Melzake, R., and K. L. Casey. 1968. “Sensory, Motivational, and Central Control Determinants of Pain.” In The Skin Senses: Proceedings of the First International Symposium on the Skin Senses., edited by Dan R. Kenshalo, 423–39. Charles C Thomas. https://www.researchgate.net/publication/233801589_Sensory_Motivational_and_Central_Cont rol_Determinants_of_Pain.

Mendell, Ari L., Sarah Atwi, Craig D.C. Bailey, Dan McCloskey, Helen E. Scharfman, and Neil J. MacLusky. 2017. “Expansion of Mossy Fibers and CA3 Apical Dendritic Length Accompanies the Fall in Dendritic Spine Density after Gonadectomy in Male, but Not Female, Rats.” Brain Structure and Function 222 (1): 587–601. https://doi.org/10.1007/s00429-016-1237-6.

Merskey, H., and N. Bogduk, eds. 1994. “Part III: Pain Terms, A Current List with Definitions and Notes on Usage.” In Classification of Chronic Pain, 2nd ed., 209–14. IASP Press. https://www.iasp-pain.org/terminology.

Mifflin, Katherine, Jill Chorney, and Bruce Dick. 2016. “Attention and Working Memory in Female Adolescents with Chronic Pain and Pain-Free Female Adolescents.” Clinical Journal of Pain 32 (7): 609–16. https://doi.org/10.1097/AJP.0000000000000239.

Mikova, O., R. Yakimova, E. Bosmans, G. Kenis, and M. Maes. 2001. “Increased Serum Tumor Necrosis Factor Alpha Concentrations in Major Depression and Multiple Sclerosis.” European Neuropsychopharmacology 11 (3): 203–8. https://doi.org/10.1016/S0924-977X(01)00081-5.

Millan, Mark J. 2002. “Descending Control of Pain.” Progress in Neurobiology 66 (6): 355–474. https://doi.org/10.1016/S0301-0082(02)00009-6.

Mirescu, Christian, and E. Gould. 2006. “Stress and Adult Neurogenesis.” Hippocampus. https://doi.org/10.1002/hipo.20155.

Moayedi, Massieh, Irit Weissman-Fogel, Adrian P. Crawley, Michael B. Goldberg, Bruce V. Freeman, Howard C. Tenenbaum, and Karen D. Davis. 2011. “Contribution of Chronic Pain and Neuroticism to Abnormal Forebrain Gray Matter in Patients with Temporomandibular Disorder.” NeuroImage 55 (1): 277–86. https://doi.org/10.1016/j.neuroimage.2010.12.013.

Mogil, Jeffrey S. 2012. “Sex Differences in Pain and Pain Inhibition: Multiple Explanations of a Controversial Phenomenon.” Nature Reviews Neuroscience 13 (12): 859–66. https://doi.org/10.1038/nrn3360.

Mogil, Jeffrey S., and Andrea L. Bailey. 2010. “Sex and Gender Differences in Pain and Analgesia.” Progress in Brain Research 186 (C): 140–57. https://doi.org/10.1016/B978-0-444-53630- 3.00009-9.

REFERENCES 125

Moriarty, Orla, Brian E. McGuire, and David P. Finn. 2011. “The Effect of Pain on Cognitive Function: A Review of Clinical and Preclinical Research.” Progress in Neurobiology 93 (3): 385–404. https://doi.org/10.1016/j.pneurobio.2011.01.002.

Moriarty, Orla, Nancy Ruane, David O’Gorman, Chris H. Maharaj, Caroline Mitchell, Kiran M. Sarma, David P. Finn, and Brian E. McGuire. 2017. “Cognitive Impairment in Patients with Chronic Neuropathic or Radicular Pain: An Interaction of Pain and Age.” Frontiers in Behavioral Neuroscience 11 (June). https://doi.org/10.3389/fnbeh.2017.00100.

Moser, May Britt, David C. Rowland, and Edvard I. Moser. 2015. “Place Cells, Grid Cells, and Memory.” Cold Spring Harbor Perspectives in Biology 7 (2). https://doi.org/10.1101/cshperspect.a021808.

Mueller, Susanne G., Norbert Schuff, Kristine Yaffe, Catherine Madison, Bruce Miller, and Michael W. Weiner. 2010. “Hippocampal Atrophy Patterns in Mild Cognitive Impairment and Alzheimer’s Disease.” Human Brain Mapping 31 (9): 1339–47. https://doi.org/10.1002/hbm.20934.

Mutso, Amelia A., B. Petre, L. Huang, M. N. Baliki, S. Torbey, K. M. Herrmann, T. J. Schnitzer, and A. V. Apkarian. 2014. “Reorganization of Hippocampal Functional Connectivity with Transition to Chronic Back Pain.” Journal of Neurophysiology 111 (5): 1065–76. https://doi.org/10.1152/jn.00611.2013.

Mutso, Amelia A., Daniel Radzicki, Marwan N. Baliki, Lejian Huang, Ghazal Banisadr, Maria V. Centeno, Jelena Radulovic, et al. 2012. “Abnormalities in Hippocampal Functioning with Persistent Pain.” The Journal of Neuroscience 32 (17): 5747–56. https://doi.org/10.1523/JNEUROSCI.0587-12.2012.

Naegel, Steffen, Dagny Holle, Nathalie Desmarattes, Nina Theysohn, Hans Christoph Diener, Zaza Katsarava, and Mark Obermann. 2014. “Cortical Plasticity in Episodic and Chronic Cluster Headache.” NeuroImage: Clinical 6: 415–23. https://doi.org/10.1016/j.nicl.2014.10.003.

Naninck, Eva F.G., Lianne Hoeijmakers, Nefeli Kakava-Georgiadou, Astrid Meesters, Stanley E. Lazic, Paul J. Lucassen, and Aniko Korosi. 2015. “Chronic Early Life Stress Alters Developmental and Adult Neurogenesis and Impairs Cognitive Function in Mice.” Hippocampus 25 (3): 309–28. https://doi.org/10.1002/hipo.22374.

Nestler, Eric J., Michel Barrot, Ralph J. DiLeone, Amelia J. Eisch, Stephen J. Gold, and Lisa M. Monteggia. 2002. “Neurobiology of Depression.” Neuron 34 (1): 13–25. https://doi.org/10.1016/S0896-6273(02)00653-0.

Nicholson, Bruce. 2006. “Differential Diagnosis: Nociceptive and Neuropathic Pain.” American Journal of Managed Care 12 (SUPPL. 9).

Nicoll, Roger A., and Dietmar Schmitz. 2005. “Synaptic Plasticity at Hippocampal Mossy Fibre

REFERENCES 126

Synapses.” Nature Reviews Neuroscience 6 (11): 863–76. https://doi.org/10.1038/nrn1786.

Nurmikko, T.J., and P.R. Eldridge. 2001. “Trigeminal Neuralgia—Pathophysiology, Diagnosis and Current Treatment.” British Journal of Anaesthesia 87 (1): 117–32. https://doi.org/10.1093/bja/87.1.117.

O’Keefe, J., and J. Dostrovsky. 1971. “The Hippocampus as a Spatial Map. Preliminary Evidence from Unit Activity in the Freely-Moving Rat.” Brain Research 34 (1): 171–75. https://doi.org/10.1016/0006-8993(71)90358-1.

O’Mara, Shane M. 2005. “The Subiculum: What It Does, What It Might Do, and What Neuroanatomy Has yet to Tell Us.” Journal of Anatomy 207 (3): 271–82. https://doi.org/10.1111/j.1469-7580.2005.00446.x.

O’Mara, Shane M., Sean Commins, Michael Anderson, and John Gigg. 2001. “The Subiculum: A Review of Form, Physiology and Function.” Progress in Neurobiology 64 (2): 129–55. https://doi.org/10.1016/S0301-0082(00)00054-X.

Oberlander, Joseph G., and Catherine S. Woolley. 2016. “17β-Estradiol Acutely Potentiates Glutamatergic Synaptic Transmission in the Hippocampus through Distinct Mechanisms in Males and Females.” Journal of Neuroscience 36 (9): 2677–90. https://doi.org/10.1523/JNEUROSCI.4437-15.2016.

Olaibi, Olayemi K., Opeyemi S. Osuntokun, and Omamuyovwi M. Lijomone. 2014. “Effects of Chronic Administration of Gabapentin and Carbamazepine on the Histomorphology of the Hippocampus and Striatum.” Annals of Neurosciences 21 (2): 57–61. https://doi.org/10.5214/ans.0972.7531.210206.

Oosterman, Joukje M., Laura C. Derksen, Albert J.M. van Wijck, Dieuwke S. Veldhuijzen, and Roy P.C. Kessels. 2011. “Memory Functions in Chronic Pain: Examining Contributions of Attention and Age to Test Performance.” The Clinical Journal of Pain 27 (1): 70–75. https://doi.org/10.1097/AJP.0b013e3181f15cf5.

Paller, Channing J., Claudia M. Campbell, Robert R. Edwards, and Adrian S. Dobs. 2009. “Sex- Based Differences in Pain Perception and Treatment.” Pain Medicine 10 (2): 289–99. https://doi.org/10.1111/j.1526-4637.2008.00558.x.

Pan, P. L., J. G. Zhong, H. F. Shang, Y. L. Zhu, P. R. Xiao, Z. Y. Dai, and H. C. Shi. 2015. “Quantitative Meta-Analysis of Grey Matter Anomalies in Neuropathic Pain.” European Journal of Pain (United Kingdom) 19 (9): 1224–31. https://doi.org/10.1002/ejp.670.

Papez, James W. 1937. “A Proposed Mechanism of Emotion.” Archives of Neurology And Psychiatry 38 (4): 725–43. https://doi.org/10.1001/archneurpsyc.1937.02260220069003.

Park, Denise C, Jennifer M Glass, Meredith Minear, and Leslie J Crofford. 2001. “Cognitive Function

REFERENCES 127

in Fibromyalgia Patients.” Arthritis and Rheumatism 44 (9): 2125–33. https://doi.org/10.1002/1529-0131(200109)44:9<2125::AID-ART365>3.0.CO;2-1.

Persson, Jonas, R. Nathan Spreng, Gary Turner, Agneta Herlitz, Arvid Morell, Eva Stening, Lars Olof Wahlund, Johan Wikström, and Hedvig Söderlund. 2014. “Sex Differences in Volume and Structural Covariance of the Anterior and Posterior Hippocampus.” NeuroImage 99 (October): 215–25. https://doi.org/10.1016/j.neuroimage.2014.05.038.

Pieretti, Stefano, Amalia Di Giannuario, Rita Di Giovannandrea, Francesca Marzoli, Giovanni Piccaro, Paola Minosi, and Anna Maria Aloisi. 2016. “Gender Differences in Pain and Its Relief.” Annali Dell’Istituto Superiore Di Sanita 52 (2): 184–89. https://doi.org/10.4415/ANN_16_02_09.

Ploghaus, Alexander, Charvy Narain, Christian F. Beckmann, Stuart Clare, Susanna Bantick, Richard Wise, Paul M. Matthews, J. Nicholas P Rawlins, and Irene Tracey. 2001. “Exacerbation of Pain by Anxiety Is Associated with Activity in a Hippocampal Network.” Journal of Neuroscience 21 (24): 9896–9903. https://doi.org/10.1523/jneurosci.21-24-09896.2001.

Poppenk, Jordan, Hallvard R. Evensmoen, Morris Moscovitch, and Lynn Nadel. 2013. “Long-Axis Specialization of the Human Hippocampus.” Trends in Cognitive Sciences 17 (5): 230–40. https://doi.org/10.1016/j.tics.2013.03.005.

Prasad, Sashank, and Steven Galetta. 2009. “Trigeminal Neuralgia Historical Notes and Current Concepts.” Neurologist 15 (2): 87–94. https://doi.org/10.1097/NRL.0b013e3181775ac3.

R Core Team. 2018. “R: A Language and Environment for Statistical Computing.” http://www.r- project.org/.

Racine, Mélanie, Yannick Tousignant-Laflamme, Lorie A. Kloda, Dominique Dion, Gilles Dupuis, and Manon Choinire. 2012a. “A Systematic Literature Review of 10 Years of Research on Sex/Gender and Experimental Pain Perception - Part 1: Are There Really Differences between Women and Men?” Pain 153 (3): 602–18. https://doi.org/10.1016/j.pain.2011.11.025.

———. 2012b. “A Systematic Literature Review of 10 Years of Research on Sex/Gender and Pain Perception - Part 2: Do Biopsychosocial Factors Alter Pain Sensitivity Differently in Women and Men?” Pain 153 (3): 619–35. https://doi.org/10.1016/j.pain.2011.11.026.

Reddi, Danielle, Natasha Curran, and Robert Stephens. 2013. “An Introduction to Pain Pathways and Mechanisms.” British Journal of Hospital Medicine 74 (SUPPL. 12). https://doi.org/10.12968/hmed.2013.74.Sup12.C188.

Regis, Jean, Constantin Tuleasca, Noemie Resseguier, Romain Carron, Anne Donnet, Jean Gaudart, and Marc Levivier. 2016. “Long-Term Safety and Effiacy of Gamma Knife Surgery in Classical Trigeminal Neuralgia: A 497-Patient Historical Cohort Study.” Journal of Neurosurgery. https://doi.org/10.3171/2015.2.JNS142144.

REFERENCES 128

Remodes, Miguel, and Erin M. Schuman. 2004. “Role for a Cortical Input to Hippocampal Area CA1 in the Consolidation of a Long-Tem Memory.” Nature 431 (7009): 699–703. https://doi.org/10.1038/nature02965.

Ren, Wen Jie, Yong Liu, Li Jun Zhou, Wei Li, Yi Zhong, Rui Ping Pang, Wen Jun Xin, et al. 2011. “Peripheral Nerve Injury Leads to Working Memory Deficits and Dysfunction of the Hippocampus by Upregulation of TNF-α in Rodents.” Neuropsychopharmacology 36 (5): 979– 92. https://doi.org/10.1038/npp.2010.236.

Riederer, Franz, Gunther Landmann, Andreas R. Gantenbein, Lenka Stockinger, Niklaus Egloff, Haiko Sprott, Wolfgang Schleinzer, et al. 2017. “Nondermatomal Somatosensory Deficits in Chronic Pain Are Associated with Cerebral Grey Matter Changes.” World Journal of Biological Psychiatry 18 (3): 227–38. https://doi.org/10.3109/15622975.2015.1073356.

Rodriguez-Raecke, Rea, Andreas Niemeier, Kristin Ihle, Wolfgang Ruether, and Arne May. 2013. “Structural Brain Changes in Chronic Pain Reflect Probably Neither Damage Nor Atrophy.” PLoS ONE 8 (2). https://doi.org/10.1371/journal.pone.0054475.

Rodriguez, Carmen S. 2001. “Pain Measurement in the Elderly: A Review.” Pain Management Nursing 2 (2): 38–46. https://doi.org/10.1053/jpmn.2001.23746.

Rogers, C. Leland, Andrew G. Shetter, Jeffrey A. Fiedler, Kris A. Smith, Patrick P. Han, and Burton L. Speiser. 2000. “Gamma Knife Radiosurgery for Trigeminal Neuralgia: The Initial Experience of the Barrow Neurological Institute.” International Journal of Radiation Oncology Biology Physics 47 (4): 1013–19. https://doi.org/10.1016/S0360-3016(00)00513-7.

Rolls, Edmund T., and Raymond P. Kesner. 2006. “A Computational Theory of Hippocampal Function, and Empirical Tests of the Theory.” Progress in Neurobiology 79 (1): 1–48. https://doi.org/10.1016/j.pneurobio.2006.04.005.

Romero-Grimaldi, Carmen, Esther Berrocoso, Cristina Alba-Delgado, Jose Luis M. Madrigal, Beatriz G. Perez-Nievas, Juan Carlos Leza, and Juan Antonio Mico. 2015. “Stress Increases the Negative Effects of Chronic Pain on Hippocampal Neurogenesis.” Anesthesia & Analgesia 121 (4): 1078–88. https://doi.org/10.1213/ANE.0000000000000838.

Rosen, Sarah, Boram Ham, and Jeffrey S. Mogil. 2017. “Sex Differences in Neuroimmunity and Pain.” Journal of Neuroscience Research 95 (1–2): 500–508. https://doi.org/10.1002/jnr.23831.

Ruau, David, Linda Y. Liu, J. David Clark, Martin S. Angst, and Atul J. Butte. 2012. “Sex Differences in Reported Pain across 11,000 Patients Captured in Electronic Medical Records.” Journal of Pain 13 (3): 228–34. https://doi.org/10.1016/j.jpain.2011.11.002.

Sanfilipo, Michael P., Ralph H.B. Benedict, Robert Zivadinov, and Rohit Bakshi. 2004. “Correction for Intracranial Volume in Analysis of Whole Brain Atrophy in Multiple Sclerosis: The Proportion vs. Residual Method.” NeuroImage 22 (4): 1732–43.

REFERENCES 129

https://doi.org/10.1016/j.neuroimage.2004.03.037.

Sapolsky, R M. 1985. “A Mechanism for Glucocorticoid Toxicity in the Hippocampus: Increased Neuronal Vulnerability to Metabolic Insults.” The Journal of Neuroscience : The Official Journal of the Society for Neuroscience 5 (5): 1228–32. http://www.ncbi.nlm.nih.gov/pubmed/3998819.

Saygin, Z. M., D. Kliemann, J. E. Iglesias, A. J.W. van der Kouwe, E. Boyd, M. Reuter, A. Stevens, et al. 2017. “High-Resolution Magnetic Resonance Imaging Reveals Nuclei of the Human Amygdala: Manual Segmentation to Automatic Atlas.” NeuroImage 155 (July): 370–82. https://doi.org/10.1016/j.neuroimage.2017.04.046.

Scheinost, Dustin, Emily S. Finn, Fuyuze Tokoglu, Xilin Shen, Xenophon Papademetris, Michelle Hampson, and R. Todd Constable. 2015. “Sex Differences in Normal Age Trajectories of Functional Brain Networks.” Human Brain Mapping 36 (4): 1524–35. https://doi.org/10.1002/hbm.22720.

Schnurr, Robert F, and Michael R MacDonald. 1995. “Memory Complaints in Chronic Pain.” The Clinical Journal of Pain 11 (2). https://journals.lww.com/clinicalpain/Fulltext/1995/06000/Memory_Complaints_in_Chronic_Pa in.4.aspx.

Schoene-Bake, Jan Christoph, Simon S. Keller, Pitt Niehusmann, Elisa Volmering, Christian Elger, Michael Deppe, and Bernd Weber. 2014. “In Vivo Mapping of Hippocampal Subfields in Mesial Temporal Lobe Epilepsy: Relation to Histopathology.” Human Brain Mapping 35 (9): 4718–28. https://doi.org/10.1002/hbm.22506.

Schoenfeld, Timothy J., Hayley C. McCausland, H. Douglas Morris, Varun Padmanaban, and Heather A. Cameron. 2017. “Stress and Loss of Adult Neurogenesis Differentially Reduce Hippocampal Volume.” Biological Psychiatry 82 (12): 914–23. https://doi.org/10.1016/j.biopsych.2017.05.013.

Schultz, Christian, and Maren Engelhardt. 2014. “Anatomy of the Hippocampal Formation.” In The Hippocampus in Clinical Neuroscience, edited by K. Szabo and M.G. Hennerici, 34:6–17. S. Karger AG. https://doi.org/10.1159/000360925.

Scimemi, Annalisa, Stephanie Schorge, Dimitri M. Kullmann, and Matthew C. Walker. 2006. “Epileptogenesis Is Associated With Enhanced Glutamatergic Transmission in the Perforant Path.” Journal of Neurophysiology 95 (2): 1213–20. https://doi.org/10.1152/jn.00680.2005.

Seminowicz, David A., Jennifer S. Labus, Joshua A. Bueller, Kirsten Tillisch, Bruce D. Naliboff, M. Catherine Bushnell, and Emeran A. Mayer. 2010. “Regional Gray Matter Density Changes in Brains of Patients With Irritable Bowel Syndrome.” Gastroenterology 139 (1). https://doi.org/10.1053/j.gastro.2010.03.049.

REFERENCES 130

Seminowicz, David A., Timothy H. Wideman, Lina Naso, Zeinab Hatami-Khoroushahi, Summaya Fallatah, Mark A. Ware, Peter Jarzem, et al. 2011. “Effective Treatment of Chronic Low Back Pain in Humans Reverses Abnormal Brain Anatomy and Function.” Journal of Neuroscience 31 (20): 7540–50. https://doi.org/10.1523/JNEUROSCI.5280-10.2011.

Sessle, B. J. 2000. “Acute and Chronic Craniofacial Pain: Brainstem Mechanisms of Nociceptive Transmission and Neuroplasticity, and Their Clinical Correlates.” Critical Reviews in Oral Biology and Medicine. Intern. and American Associations for Dental Research. https://doi.org/10.1177/10454411000110010401.

———. 2006. “Mechanisms of Oral Somatosensory and Motor Functions and Their Clinical Correlates.” Journal of Oral Rehabilitation 33 (4): 243–61. https://doi.org/10.1111/j.1365- 2842.2006.01623.x.

Shafto, Meredith A, Lorraine K Tyler, Marie Dixon, Jason R Taylor, James B Rowe, Rhodri Cusack, Andrew J Calder, et al. 2014. “The Cambridge Centre for Ageing and Neuroscience (Cam- CAN) Study Protocol: A Cross-Sectional, Lifespan, Multidisciplinary Examination of Healthy Cognitive Ageing.” BMC Neurology 14 (1): 204. https://doi.org/10.1186/s12883-014-0204-1.

Shankland, Wesley E. 2000. “The Trigeminal Nerve. Part I: An Over-View.” Cranio 18 (4): 238–48. https://doi.org/10.1080/08869634.2000.11746137.

———. 2001a. “The Trigeminal Nerve. Part II: The Ophthalmic Division.” Cranio 19 (1): 8–12. https://doi.org/10.1080/08869634.2001.11746145.

———. 2001b. “The Trigeminal Nerve. Part III: The Maxillary Division.” Cranio 19 (2): 78–83. https://doi.org/10.1080/08869634.2001.11746155.

———. 2001c. “The Trigeminal Nerve. Part IV: The Mandibular Division.” Cranio 19 (3): 153–61. https://doi.org/10.1080/08869634.2001.11746164.

Sheehan, Jason, Hung Chuan Pan, Matei Stroila, and Ladislau Steiner. 2005. “Gamma Knife Surgery for Trigeminal Neuralgia: Outcomes and Prognostic Factors.” Journal of Neurosurgery 102 (3): 434–41. https://doi.org/10.3171/jns.2005.102.3.0434.

Sheline, Yvette I., Mokhtar H. Gado, and Helena C. Kraemer. 2003. “Untreated Depression and Hippocampal Volume Loss.” American Journal of Psychiatry 160 (8): 1516–18. https://doi.org/10.1176/appi.ajp.160.8.1516.

Shors, Tracey J. 2006. “Stressful Experience and Learning Across the Lifespan.” Annual Review of Psychology 57 (1): 55–85. https://doi.org/10.1146/annurev.psych.57.102904.190205.

Shors, Tracey J., Chadrick Chua, and Jacqueline Falduto. 2001. “Sex Differences and Opposite Effects of Stress on Dendritic Spine Density in the Male versus Female Hippocampus.” Journal of Neuroscience 21 (16): 6292–97. https://doi.org/10.1523/jneurosci.21-16-06292.2001.

REFERENCES 131

Shors, Tracey J., Thomas B. Seib, Seymour Levine, and Richard F. Thompson. 1989. “Inescapable versus Escapable Shock Modulates Long-Term Potentiation in the Rat Hippocampus.” Science 244 (4901): 224–26. https://doi.org/10.1126/science.2704997.

Šimić, Goran, Ivica Kostović, Bengt Winblad, and Nenad Bogdanović. 1997. “Volume and Number of Neurons of the Human Hippocampal Formation in Normal Aging and Alzheimer’s Disease.” Journal of Comparative Neurology 379 (4): 482–94. https://doi.org/10.1002/(SICI)1096- 9861(19970324)379:4<482::AID-CNE2>3.0.CO;2-Z.

Simons, Laura E., Igor Elman, and David Borsook. 2014. “Psychological Processing in Chronic Pain: A Neural Systems Approach.” Neuroscience and Biobehavioral Reviews 39 (February): 61–78. https://doi.org/10.1016/j.neubiorev.2013.12.006.

Singh, Gyaninder Pal. 2019. “Anatomy of Trigeminal Nerve.” In Handbook of Trigeminal Neuralgia, edited by Girija Prasad Rath, 11–22. Springer Singapore. https://doi.org/10.1007/978-981-13- 2333-1_2.

Sjogren, Per, Lona L. Christrup, Morten Aa Petersen, and Jette Hojsted. 2005. “Neuropsychological Assessment of Chronic Non-Malignant Pain Patients Treated in a Multidisciplinary Pain Centre.” European Journal of Pain 9 (4): 453. https://doi.org/10.1016/j.ejpain.2004.10.005.

Smallwood, Rachel F., Angela R. Laird, Amy E. Ramage, Amy L. Parkinson, Jeffrey Lewis, Daniel J. Clauw, David A. Williams, et al. 2013. “Structural Brain Anomalies and Chronic Pain: A Quantitative Meta-Analysis of Gray Matter Volume.” Journal of Pain 14 (7): 663–75. https://doi.org/10.1016/j.jpain.2013.03.001.

Solodkin, A., G.W. Van Hoesen, and R. Insausti. 2014. “Entorhinal Cortex.” In Reference Module in Biomedical Sciences. Elsevier. https://doi.org/10.1016/b978-0-12-801238-3.04585-2.

Sommer, Claudia, Martin Marziniak, and Robert R. Myers. 1998. “The Effect of Thalidomide Treatment on Vascular Pathology and Hyperalgesia Caused by Chronic Constriction Injury of Rat Nerve.” Pain 74 (1): 83–91. https://doi.org/10.1016/S0304-3959(97)00154-1.

Sommer, Claudia, Christine Schmidt, Annette George, and Klaus V. Toyka. 1997. “A Metalloprotease-Inhibitor Reduces Pain Associated Behavior in Mice with Experimental Neuropathy.” Neuroscience Letters 237 (1): 45–48. https://doi.org/10.1016/S0304- 3940(97)00813-6.

Sorge, Robert E., and Larissa J. Strath. 2018. “Sex Differences in Pain Responses.” Current Opinion in Physiology. Elsevier Ltd. https://doi.org/10.1016/j.cophys.2018.05.006.

Sorge, Robert E., and Stacie K. Totsch. 2017. “Sex Differences in Pain.” Journal of Neuroscience Research 95 (6): 1271–81. https://doi.org/10.1002/jnr.23841.

Steward, Oswald. 1976. “Topographic Organization of the Projections from the Entorhinal Area to

REFERENCES 132

the Hippocampal Formation of the Rat.” Journal of Comparative Neurology 167 (3): 285–314. https://doi.org/10.1002/cne.901670303.

Strange, Bryan A., Menno P. Witter, Ed S. Lein, and Edvard I. Moser. 2014. “Functional Organization of the Hippocampal Longitudinal Axis.” Nature Reviews Neuroscience 15 (10): 655–69. https://doi.org/10.1038/nrn3785.

Swanson, L. W., and W. M. Cowan. 1977. “An Autoradiographic Study of the Organization of the Efferet Connections of the Hippocampal Formation in the Rat.” Journal of Comparative Neurology 172 (1): 49–84. https://doi.org/10.1002/cne.901720104.

Tajerian, Maral, Victor Hung, Huy Nguyen, Gail Lee, Lydia Marie Joubert, Andrey Victorovich Malkovskiy, Bende Zou, Simon Xie, Ting Ting Huang, and J. David Clark. 2018. “The Hippocampal Extracellular Matrix Regulates Pain and Memory after Injury.” Molecular Psychiatry 23 (12): 2302–13. https://doi.org/10.1038/s41380-018-0209-z.

Tan, Anh, Wenli Ma, Amit Vira, Dhruv Marwha, and Lise Eliot. 2016. “The Human Hippocampus Is Not Sexually-Dimorphic: Meta-Analysis of Structural MRI Volumes.” NeuroImage 124 (January): 350–66. https://doi.org/10.1016/j.neuroimage.2015.08.050.

Terada, Mioko, Naoko Kuzumaki, Nana Hareyama, Satoshi Imai, Keiich Niikura, Michiko Narita, Mitsuaki Yamazaki, Tsutomu Suzuki, and Minoru Narita. 2008. “Suppression of Enriched Environment-Induced Neurogenesis in a Rodent Model of Neuropathic Pain.” Neuroscience Letters 440 (3): 314–18. https://doi.org/10.1016/j.neulet.2008.05.078.

Teutsch, S., W. Herken, U. Bingel, E. Schoell, and A. May. 2008. “Changes in Brain Gray Matter Due to Repetitive Painful Stimulation.” NeuroImage 42 (2): 845–49. https://doi.org/10.1016/j.neuroimage.2008.05.044.

Thompson, Jeremy M., and Volker Neugebauer. 2019. “Cortico-Limbic Pain Mechanisms.” Neuroscience Letters 702 (May): 15–23. https://doi.org/10.1016/j.neulet.2018.11.037.

Toda, Tomohisa, Sarah L. Parylak, Sara B. Linker, and Fred H. Gage. 2019. “The Role of Adult Hippocampal Neurogenesis in Brain Health and Disease.” Molecular Psychiatry 24 (1): 67–87. https://doi.org/10.1038/s41380-018-0036-2.

Tohyama, Sarasa, Peter S.P. Hung, Joshua C. Cheng, Jia Y. Zhang, Aisha Halawani, David J. Mikulis, Jiwon Oh, and Mojgan Hodaie. 2020. “Trigeminal Neuralgia Associated with Solitary Pontine Lesion.” PAIN, December, 1. https://doi.org/10.1097/j.pain.0000000000001777.

Tohyama, Sarasa, Peter S.P. Hung, Jidan Zhong, and Mojgan Hodaie. 2018. “Early Postsurgical Diffusivity Metrics for Prognostication of Long-Term Pain Relief after Gamma Knife Radiosurgery for Trigeminal Neuralgia.” Journal of Neurosurgery 131 (2): 539–48. https://doi.org/10.3171/2018.3.JNS172936.

REFERENCES 133

Torrance, Nicola, Blair H. Smith, Michael I. Bennett, and Amanda J. Lee. 2006. “The Epidemiology of Chronic Pain of Predominantly Neuropathic Origin. Results From a General Population Survey.” Journal of Pain 7 (4): 281–89. https://doi.org/10.1016/j.jpain.2005.11.008.

Tracey, Irene, and Siri Graff Leknes. 2013. “Hippocampus and Entorhinal Complex: Functional Imaging.” In Encyclopedia of Pain, edited by Gerald F. Gebhart and Robert F. Schmidt, 1476– 81. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-28753-4_1763.

Treede, Rolf-Detlef, Winfried Rief, Antonia Barke, Qasim Aziz, Michael I. Bennett, Rafael Benoliel, Milton Cohen, et al. 2015. “A Classification of Chronic Pain for ICD-11.” Pain 156 (6): 1003– 7. https://doi.org/10.1097/j.pain.0000000000000160.

———. 2019. “Chronic Pain as a Symptom or a Disease: The IASP Classification of Chronic Pain for the International Classification of Diseases (ICD-11).” PAIN 160 (1): 19–27. https://doi.org/10.1097/j.pain.0000000000001384.

Treit, Sarah, Trevor Steve, Donald W. Gross, and Christian Beaulieu. 2018. “High Resolution In- Vivo Diffusion Imaging of the Human Hippocampus.” NeuroImage 182 (November): 479–87. https://doi.org/10.1016/J.NEUROIMAGE.2018.01.034.

Tyrtyshnaia, Anna, Igor Manzhulo, Yulia Kipryushina, and Ekaterina Ermolenko. 2019. “Neuroinflammation and Adult Hippocampal Neurogenesis in Neuropathic Pain and Alkyl Glycerol Ethers Treatment in Aged Mice.” International Journal of Molecular Medicine 43 (5): 2153–63. https://doi.org/10.3892/ijmm.2019.4142.

Vacca, Valentina, Sara Marinelli, Luisa Pieroni, Andrea Urbani, Siro Luvisetto, and Flaminia Pavone. 2014. “Higher Pain Perception and Lack of Recovery from Neuropathic Pain in Females: A Behavioural, Immunohistochemical, and Proteomic Investigation on Sex-Related Differences in Mice.” Pain 155 (2): 388–402. https://doi.org/10.1016/j.pain.2013.10.027.

Vachon-Presseau, Etienne, Mathieu Roy, Marc Olivier Martel, Etienne Caron, Marie France Marin, Jeni Chen, Geneviève Albouy, et al. 2013. “The Stress Model of Chronic Pain: Evidence from Basal Cortisol and Hippocampal Structure and Function in Humans.” Brain 136 (3): 815–27. https://doi.org/10.1093/brain/aws371.

Vaculik, Michael Frantisek, Alborz Noorani, Peter S.P. Hung, and Mojgan Hodaie. 2019. “Selective Hippocampal Subfield Volume Reductions in Classic Trigeminal Neuralgia.” NeuroImage: Clinical 23 (January): 101911. https://doi.org/10.1016/J.NICL.2019.101911.

Vago, David R., and Raymond P. Kesner. 2008. “Disruption of the Direct Perforant Path Input to the CA1 Subregion of the Dorsal Hippocampus Interferes with Spatial Working Memory and Novelty Detection.” Behavioural Brain Research 189 (2): 273–83. https://doi.org/10.1016/j.bbr.2008.01.002.

Vaher, Paul R., Victoria N. Luine, E. Gould, and Bruce S. McEwen. 1994. “Effects of Adrenalectomy

REFERENCES 134

on Spatial Memory Performance and Dentate Gyrus Morphology.” Brain Research 656 (1): 71– 78. https://doi.org/10.1016/0006-8993(94)91367-6.

Vasic, Verica, and Mirko H.H. Schmidt. 2017. “Resilience and Vulnerability to Pain and Inflammation in the Hippocampus.” International Journal of Molecular Sciences 18 (4). https://doi.org/10.3390/ijms18040739.

Vilensky, Joel A., Wendy M. Robertson, and Carlos A. Suárez-Quian. 2015. “The Trigeminal Nerve.” In The Clinical Anatomy of the Cranial Nerves, edited by Justin Jeffryes and Stephanie Dollan, 75–109. Hoboken, NJ: Wiley. https://doi.org/10.1002/9781118491959.ch5.

Villarreal, Gerardo, Derek A. Hamilton, Helen Petropoulos, Ira Driscoll, Laura M. Rowland, Jaqueline A. Griego, Piyadasa W. Kodituwakku, Blaine L. Hart, Rodrigo Escalona, and William M. Brooks. 2002. “Reduced Hippocampal Volume and Total White Matter Volume in Posttraumatic Stress Disorder.” Biological Psychiatry 52 (2): 119–25. https://doi.org/10.1016/S0006-3223(02)01359-8.

Vogt, Brent A. 2005. “Pain and Emotion Interactions in Subregions of the Cingulate Gyrus.” Nature Reviews Neuroscience 6 (7): 533–44. https://doi.org/10.1038/nrn1704.

Voscopoulos, C., and M. Lema. 2010. “When Does Acute Pain Become Chronic?” British Journal of Anaesthesia 105 (December): i69–85. https://doi.org/10.1093/bja/aeq323.

Walker, H. Kenneth. 1990. “Cranial Nerve V: The Trigeminal Nerve.” In Clinical Methods: The History, Physical, and Laboratory Examinations, edited by HK Walker, WD Hall, and JW Hurst. Butterworths. http://www.ncbi.nlm.nih.gov/pubmed/21250225.

Wang, Feng, Erik Bélanger, Marie Eve Paquet, Daniel C. Côté, and Yves De Koninck. 2016. “Probing Pain Pathways with Light.” Neuroscience 338 (December): 248–71. https://doi.org/10.1016/j.neuroscience.2016.09.035.

Wang, Gang, Nathalie Erpelding, and Karen D. Davis. 2014. “Sex Differences in Connectivity of the Subgenual Anterior Cingulate Cortex.” Pain 155 (4): 755–63. https://doi.org/10.1016/j.pain.2014.01.005.

Wang, Yuan, Qian Yang, Dongyuan Cao, David Seminowicz, Bethany Remeniuk, Lin Gao, and Ming Zhang. 2019. “Correlation between Nerve Atrophy, Brain Grey Matter Volume and Pain Severity in Patients with Primary Trigeminal Neuralgia.” Cephalalgia 39 (4): 515–25. https://doi.org/10.1177/0333102418793643.

Watanabe, Yoshifumi, E. Gould, and Bruce S. McEwen. 1992. “Stress Induces Atrophy of Apical Dendrites of Hippocampal CA3 Pyramidal Neurons.” Brain Research 588 (2): 341–45. https://doi.org/10.1016/0006-8993(92)91597-8.

West, M. J., P. D. Coleman, D. G. Flood, and J. C. Troncoso. 1994. “Differences in the Pattern of

REFERENCES 135

Hippocampal Neuronal Loss in Normal Ageing and Alzheimer’s Disease.” The Lancet 344 (8925): 769–72. https://doi.org/10.1016/S0140-6736(94)92338-8.

Whitlock, Elizabeth L., L. Grisell Diaz-Ramirez, M. Maria Glymour, W. John Boscardin, Kenneth E. Covinsky, and Alexander K. Smith. 2017. “Association between Persistent Pain and Memory Decline and Dementia in a Longitudinal Cohort of Elders.” JAMA Internal Medicine 177 (8). https://doi.org/10.1001/jamainternmed.2017.1622.

Wiesenfeld-Hallin, Zsuzsanna. 2005. “Sex Differences in Pain Perception.” Gender Medicine 2 (3): 137–45. https://doi.org/10.1016/S1550-8579(05)80042-7.

Wiffen, Philip J, Sheena Derry, R Andrew Moore, and Eija A Kalso. 2014. “Carbamazepine for Chronic Neuropathic Pain and Fibromyalgia in Adults.” Cochrane Database of Systematic Reviews. https://doi.org/10.1002/14651858.CD005451.pub3.

Wilson-Pauwels, Linda, P.A. Stewart, E.J. Akesson, and S.D. Spacey. 2013. Cranial Nerves: Function & Dysfunction. Edited by Susan Cooper. 2nd ed. Pmph usa.

Wilson, Michael G., John N. Lavis, and Moriah E. Ellen. 2015. “Supporting Chronic Pain Management across Provincial and Territorial Health Systems in Canada: Findings from Two Stakeholder Dialogues.” Pain Research and Management 20 (5): 269–79. https://doi.org/10.1155/2015/918976.

Wingenfeld, Katja, and Oliver T. Wolf. 2014. “Stress, Memory, and the Hippocampus.” In The Hippocampus in Clinical Neuroscience, edited by K. Szabo and M.G. Hennerici, 34:109–20. S. Karger AG. https://doi.org/10.1159/000356423.

Winner, Beate, Martin Regensburger, Sebastian Schreglmann, Leah Boyer, Iryna Prots, Edward Rockenstein, Michael Mante, et al. 2012. “Role of α-Synuclein in Adult Neurogenesis and Neuronal Maturation in the Dentate Gyrus.” Journal of Neuroscience 32 (47): 16906–16. https://doi.org/10.1523/JNEUROSCI.2723-12.2012.

Witter, Menno P. 2007. “The Perforant Path: Projections from the Entorhinal Cortex to the Dentate Gyrus.” Progress in Brain Research 163: 43–61. https://doi.org/10.1016/S0079-6123(07)63003- 9.

———. 2010. “Connectivity of the Hippocampus.” In Hippocampal Microcircuits, edited by Vassilis Cutsuridis, Bruce Graham, Stuart Cobb, and Imre Vida, 5–26. Springer New York. https://doi.org/10.1007/978-1-4419-0996-1_1.

Witter, Menno P., and David G. Amaral. 1991. “Entorhinal Cortex of the Monkey: V. Projections to the Dentate Gyrus, Hippocampus, and Subicular Complex.” Journal of Comparative Neurology 307 (3): 437–59. https://doi.org/10.1002/cne.903070308.

Witter, Menno P., Arjan W. Griffioen, Barbara Jorritsma-Byham, and Jose L.M. Krijnen. 1988.

REFERENCES 136

“Entorhinal Projections to the Hippocampal CA1 Region in the Rat: An Underestimated Pathway.” Neuroscience Letters 85 (2): 193–98. https://doi.org/10.1016/0304-3940(88)90350-3.

Woller, Sarah A., Kelly A. Eddinger, Maripat Corr, and Tony L. Yaksh. 2017. “An Overview of Pathways Encoding Nociception.” Clinical and Experimental Rheumatology 35 (5): S40–46.

Woolf, Clifford J., and Qiufu Ma. 2007. “Nociceptors-Noxious Stimulus Detectors.” Neuron. Elsevier. https://doi.org/10.1016/j.neuron.2007.07.016.

Woolf, Clifford J., and Richard J. Mannion. 1999. “Neuropathic Pain: Aetiology, Symptoms, Mechanisms, and Management.” Lancet 353 (9168): 1959–64. https://doi.org/10.1016/S0140- 6736(99)01307-0.

Woolley, Catherine S., E. Gould, Maya Frankfurt, and Bruce S. McEwen. 1990. “Naturally Occurring Fluctuation in Dendritic Spine Density on Adult Hippocampal Pyramidal Neurons.” Journal of Neuroscience 10 (12): 4035–39. https://doi.org/10.1523/jneurosci.10-12-04035.1990.

Woolley, Catherine S., E. Gould, and Bruce S. McEwen. 1990. “Exposure to Excess Glucocorticoids Alters Dendritic Morphology of Adult Hippocampal Pyramidal Neurons.” Brain Research 531 (1–2): 225–31. https://doi.org/10.1016/0006-8993(90)90778-A.

Xu, Ji Tian, Wen Jun Xin, Ying Zang, Chang You Wu, and Xian Guo Liu. 2006. “The Role of Tumor Necrosis Factor-Alpha in the Neuropathic Pain Induced by Lumbar 5 Ventral Root Transection in Rat.” Pain 123 (3): 306–21. https://doi.org/10.1016/j.pain.2006.03.011.

Yagi, Shunya, and Liisa A.M. Galea. 2019. “Sex Differences in Hippocampal Cognition and Neurogenesis.” Neuropsychopharmacology 44 (1): 200–213. https://doi.org/10.1038/s41386- 018-0208-4.

Yam, Mun Fei, Yean Chun Loh, Chu Shan Tan, Siti Khadijah Adam, Nizar Abdul Manan, and Rusliza Basir. 2018. “General Pathways of Pain Sensation and the Major Neurotransmitters Involved in Pain Regulation.” International Journal of Molecular Sciences 19 (8). https://doi.org/10.3390/ijms19082164.

Yang, Seoyon, and Min Cheol Chang. 2019. “Chronic Pain: Structural and Functional Changes in Brain Structures and Associated Negative Affective States.” International Journal of Molecular Sciences 20 (13). https://doi.org/10.3390/ijms20133130.

Yoshino, Norio, Hideaki Akimoto, Ichiro Yamada, Tsukasa Nagaoka, Akemi Tetsumura, Tohru Kurabayashi, Eiichi Honda, Shin Nakamura, and Takehito Sasaki. 2003. “Trigeminal Neuralgia: Evaluation of Neuralgic Manifestation and Site of Neurovascular Compression with 3D CISS MR Imaging and MR Angiography.” Radiology 228 (2): 539–45. https://doi.org/10.1148/radiol.2282020439.

Zakrzewska, J. M., and M. E. Linskey. 2014. “Trigeminal Neuralgia.” Bmj 348 (feb17 9): g474–g474.

REFERENCES 137

https://doi.org/10.1136/bmj.g474.

Zatorre, Robert J., R. Douglas Fields, and Heidi Johansen-Berg. 2012. “Plasticity in Gray and White: Neuroimaging Changes in Brain Structure during Learning.” Nature Neuroscience 15 (4): 528– 36. https://doi.org/10.1038/nn.3045.

Zelenka, Marek, Maria Schäfers, and Claudia Sommer. 2005. “Intraneural Injection of Interleukin-1β and Tumor Necrosis Factor-Alpha into Rat Sciatic Nerve at Physiological Doses Induces Signs of Neuropathic Pain.” Pain 116 (3): 257–63. https://doi.org/10.1016/j.pain.2005.04.018.

Zhang, Chao, Nathan D. Cahill, Mohammad R. Arbabshirani, Tonya White, Stefi A. Baum, and Andrew M. Michael. 2016. “Sex and Age Effects of Functional Connectivity in Early Adulthood.” Brain Connectivity 6 (9): 700–713. https://doi.org/10.1089/brain.2016.0429.

Zhao, H, A Alam, Q Chen, M A Eusman, A Pal, S Eguchi, L Wu, and D Ma. 2017. “The Role of Microglia in the Pathobiology of Neuropathic Pain Development: What Do We Know?” British Journal of Anaesthesia 118 (4): 504–16. https://doi.org/10.1093/bja/aex006.

Zheng, Jie, Ming Yi, and You Wan. 2016. “Hippocampal Neurogenesis: Does It Relieve or Worsen Chronic Pain?” Pain 157 (2): 506–7. https://doi.org/10.1097/j.pain.0000000000000418.

Zhong, Jidan, David Qixiang Chen, Peter S.P. Hung, Dave J. Hayes, Kevin E. Liang, Karen D. Davis, and Mojgan Hodaie. 2018. “Multivariate Pattern Classification of Brain White Matter Connectivity Predicts Classic Trigeminal Neuralgia.” Pain 159 (10): 2076–87. https://doi.org/10.1097/j.pain.0000000000001312.

Zhuo, Min. 2008. “Cortical Excitation and Chronic Pain.” Trends in Neurosciences 31 (4): 199–207. https://doi.org/10.1016/j.tins.2008.01.003.