Following peripheral nerve transection and microsurgical repair (PNIr) most patients retain significant sensorimotor impairments, a proportion of which also develop chronic neuropathic pain. Individual psychological factors may contribute to the development, intensity and duration of chronic pain. Furthermore, a large body of evidence has indentified beneficial and maladaptive cortical plasticity following disease or injury. The general aim of this thesis was to determine the extent of sensory and motor recovery, functional and structural brain changes, and the impact of chronic neuropathic pain on sensorimotor outcomes following upper limb PNIr. Towards this main aim a sensorimotor psychophysical assessment (that included psychological assessments), nerve conduction testing, and an MRI session that examined brain function and structure was performed in patients with peripipheral nerve injury induced neuropathic pain (PNI-P) and those with no neuropathic pain (PNI-NP). Nerve conduction testing demonstrated that all patients had incomplete peripheral nerve regeneration, and that PNI-P patients had worse sensory nerve regeneration. Psychophysical assessment confirmed that all PNIr patients had significant sensorimotor deficits. Additionally, deficits on tests of vibration detection, sensorimotor integration, and fine dexterity were significantly greater in PNI-P patients. Psychological measures clearly distinguished PNI-P from PNI-NP and healthy controls (HC). Vibrotactile stimulation of the deafferented territory in PNI-NP patients results in reduced BOLD activation within the primary and secondary somatosensory cortices. Interestingly, the regions of reduced BOLD corresponded with gray matter thinning which was negatively correlated with behavioural measures of sensory recovery. Structural abnormalities were also identified in the right insula. PNI-P patients had thinning within the right middle insula and a corresponding decrease in white matter pathways projecting into/out of that region. PNI-P patients also had white matter abnormalities in pathways feeding into/out of the contralesional primary somatosensory cortex and thalamus. In conclusion, PNIr is clearly associated with sensorimotor impairments and brain plasticity. Furthermore, neuropathic pain is associated with worse peripheral nerve regeneration, sensorimotor deficits, different psychological profiles, and structural alterations in brain regions involved in pain perception and somatosensation. These results provide insight into peripheral regeneration, the development of chronic pain, brain plasticity and structure-function-behavioural relationships following nerve injury and have important therapeutic implications.

Background: Adolescence and young adulthood are particularly vulnerable periods for the development of mental health disorders, including bipolar disorder (BD). Mental health screening at universities could aid in the early identification of particularly at- risk individuals, with the long-term aim of providing early treatment interventions to improve clinical outcomes. However, further research into the identification of appropriate behavioral and biological markers for vulnerability to psychiatric disorders – as well as into the acceptability and efficacy of mental health screening - is warranted. Methods: Young adults were recruited via an already existing Internet-based mental health screening survey of undergraduate students at the University of Oxford. In Study 1, qualitative interviews of young adults with and without previous mental health problems were conducted to assess the acceptability and efficacy of mental health screening within a university setting. In Studies 2-5 we explored the hypotheses of altered emotional decision-making, reward processing and neurostructural integrity as behavioral and neurobiological markers for vulnerability to bipolar disorder via the study of young adults with a common bipolar phenotype (BPP) - some of whom meet diagnostic criteria for bipolar II or not-otherwise-specified disorder (BD II/NOS). To that end, we employed a diverse range of methodologies: alcohol challenge (Study 2); neuropsychological task performance (Study 3); functional magnetic resonance imaging (fMRI; Study 4); diffusion tensor imaging (DTI) and voxel-based morphometry (VBM; Study 5). Results: Findings from Study 1 suggest that young adults are willing to participate in mental health screening within a university setting, and that such screening may be used to offer subsequent treatment interventions. Taken together, findings from Studies 2 and 4 suggest a general blunted reward response among unmedicated young adults at increased risk for BD during euthymia, and additionally suggest pathophysiological similarities between BD and alcohol use disorders (AUDs) that may provide a causal link between the elevated co-occurrence rates of the two disorders. Finally, findings from Study 5 suggest widespread white matter microstructural alterations – which are likely to be neurodevelopmental in origin – among antipsychotic- and mood-stabilizer naïve young adults with BD II/NOS. Conclusions: These data support the hypothesis of neurodevelopmental alterations identifiable prior to significant clinical impairment among young adults at increased risk of – or already meeting DSM-IV criteria for – bipolar disorder. They also suggest that young adults in higher education are willing to participate in mental health screening. Future studies should aim to identify more specific markers for individual disorders such as BD.

Le travail de cette thèse est méthodologique centré autour de l'imagerie du tenseur de diffusion par résonance magnétique (DTI) avec des développements incluant des simula- tion Monte Carlo des signaux RMN de diffusion dans des modèles géométriques du tissu cérébral et des acquisitions de séquence DTI haute résolution 3D pour aboutir à l'imagerie "fibre tracking" dans le cerveau de souris. Différents modèles géométriques de la substance blanche, grise ou encore incluant les deux structures sont proposés. Le principe de leur génération est décrit ainsi que la gestion des contraintes liées à la compartimentation. Il est montré aussi le principe de l'élaboration d'un nouveau “modèle composite” qui per- met de modéliser des géométries complexes comme le mélange de différentes structures ou encore des différentes orientations des axes des fibres de la substance blanche. Un avantage au modèle composite est sa simplicité et le gain en temps de calcul. Les résul- tats des simulations ont été confrontés à des données in vivo et ont permis d'interpréter l'origine des signaux et d'évaluer l'impact de certains paramètres géométriques sur ces signaux. Ils ont permis aussi d'optimiser les conditions d'acquisition. Une application majeure des développements de l'imagerie 3D haute résolution est son application dans un modèle apparenté à la schizophrénie chez la souris. Par comparaison à des souris nor- males, il est montré, pour la première fois en utilisant DTI et l'imagerie fibre tracking, une baisse du volume de la matière blanche et une réduction, voire une absence de la partie post-commissurale du fornix, un tract qui relaie l'hippocampe vers le corps mamillaire. / Le travail de cette thèse est méthodologique centré autour de l'imagerie du tenseur de diffusion par résonance magnétique (DTI) avec des développements incluant des simula- tion Monte Carlo des signaux RMN de diffusion dans des modèles géométriques du tissu cérébral et des acquisitions de séquence DTI haute résolution 3D pour aboutir à l'imagerie "fibre tracking" dans le cerveau de souris. Différents modèles géométriques de la substance blanche, grise ou encore incluant les deux structures sont proposés. Le principe de leur génération est décrit ainsi que la gestion des contraintes liées à la compartimentation. Il est montré aussi le principe de l'élaboration d'un nouveau “modèle composite” qui per- met de modéliser des géométries complexes comme le mélange de différentes structures ou encore des différentes orientations des axes des fibres de la substance blanche. Un avantage au modèle composite est sa simplicité et le gain en temps de calcul. Les résul- tats des simulations ont été confrontés à des données in vivo et ont permis d'interpréter l'origine des signaux et d'évaluer l'impact de certains paramètres géométriques sur ces signaux. Ils ont permis aussi d'optimiser les conditions d'acquisition. Une application majeure des développements de l'imagerie 3D haute résolution est son application dans un modèle apparenté à la schizophrénie chez la souris. Par comparaison à des souris nor- males, il est montré, pour la première fois en utilisant DTI et l'imagerie fibre tracking, une baisse du volume de la matière blanche et une réduction, voire une absence de la partie post-commissurale du fornix, un tract qui relaie l'hippocampe vers le corps mamillaire.

Introdução: Os transtornos depressivos constituem um problema de saúde pública na terceira idade, e estima-se que a depressão será uma das três principais causas de sobrecarga de doença no mundo nas próximas decadas. Métodos de neuroimagem têm sido amplamente utilizados em estudos de depressão em idosos, pois são técnicas não invasivas que permitem a detecção de alterações cerebrais estruturais e funcionais. Fração de Anisotropia (FA) e Difusividade Média (MD) são índices indiretos da integridade micro-estrutural da substância branca, mensurados através de imagens de tensor de difusão (DTI). A maioria dos estudos a respeito de depressão e neuroimagem tem focado apenas em possíveis diferenças em regiões de interesse (ROI) previamente determinadas. Pesquisas sobre depressão em idosos e as alterações estruturais por tensor de difusão em todo o cérebro são escassos. O objetivo deste estudo foi investigar a existência de alterações nos parâmetros de FA ou MD em todo o cérebro, sem uma região de interesse previamente definida, comparando idosos deprimidos a idosos sem depressão. Métodos: Exames de imagem cerebral por ressonância magnética foram obtidos de 47 idosos deprimidos (idade média=70,94 ± 6,98), segundo critérios diagnósticos do DSM-IV, e 36 idosos sem depressão (idade média=69,39 ± 7,21) (p=0,32). O exame de neuroimagem dos sujeitos foi realizado em aparelho de ressonância magnética (RM) de 1,5 T, (TE mínimo, TR=10000ms, FOV=26, matriz=128x128, espessura=5mm). Os parâmetros de difusão das imagens de RM foram obtidos a partir de 25 direções não colineares com um b-valor de 1000s/mm2 juntamente com imagem sem gradientes de difusão b=0. Antes da aquisição dos exames de imagem, um psiquiatra administrou os seguintes testes: Mini-Exame do Estado Mental (MEEM), Teste Cognitivo Cambridge (CAMCOG), Escala Montgomery-Aberg de Depressão (MADRS) e Escala de Depressão de Hamilton (HAM-D). Não foram encontradas diferenças significativas nos dados demográficos entre os grupos. A análise estatística baseada no voxel dos dados de FA foi realizada com uso da ferramenta TBSS, parte do programa FSL, que projeta a FA de cada indivíduo em um esqueleto de FA média antes de aplicar a análise estatística baseada no voxel entre os sujeitos da amostra. Diferenças entre os grupos foram controladas para idade. Resultados: Os escores médios da avaliação cognitiva para o grupo de idosos deprimidos foram: CAMCOG=82,94 ± 13,95 e MEEM=25,21 ± 3,74; e para o grupo controle: CAMCOG=90,83 ± 8,88 (p=0,017) e MEEM=27,86 ± 1,99 (p=0,004). Quanto às escalas de sintomatologia depressiva, tem-se no grupo de idosos deprimidos: MADRS=23,23 ± 8,60 HAM-D=18,64 ± 6,17; e no grupo de idosos sem depressão: MADRS=1,39 ± 1,20, HAM-D=2,67 ± 1,57. Após o ajuste por idade, o grupo de idosos deprimidos não apresentou diferenças significativas nos parâmetros de FA e de MD. Os escores da avaliação cognitiva (CAMCOG e MEEM) não se correlacionaram significativamente aos parâmetros de FA nem de MD. Resultados semelhantes foram obtidos após a correlação com escores das escalas de sintomatologia depressiva (MADRS e HAM-D). Conclusão: Não houve diferença significativa, na amostra estudada, dos parâmetros de FA ou MD entre os idosos deprimidos e idosos sem depressão quando o cérebro é analisado sem a utilização de ROI. Não houve correlação, na presente amostra, entre avaliação cognitiva e FA ou MD nem entre gravidade da depressão e estes parâmetros de avaliação de alteração de substância branca / Introduction: Depressive disorders constitute a public health problem in old age, and depression is projected to be one of the three leading causes of burden of disease worldwide in the next decades. Neuroimaging methods have been widely used in studies of depression in the elderly, because they are noninvasive techniques that allow the detection of structural and functional brain changes. Fractional Anisotropy (FA) and Mean Diffusivity (MD) are neuroimaging index of micro-structural white matter integrity, measured using diffusion tensor imaging. Most studies investigating depression and neuroimaging have focused only in possible differences in regions of interesting (ROI) previously selected. Studies investigating correlation between elderly depression and structural alterations measured by diffusion tensor in the whole brain are scarce. The aim of this study was to investigate the existence of FA or MD differences in the whole brain, without a region of interest previously determined, between elderly depressed and elderly without depression. Methods: Brain magnetic resonance imaging scans were obtained on 47 elderly depressed subjects (mean age=70.9 ± 6.9), according to DSM-IV criteria, and 36 healthy elderly controls (mean age=69.4 ± 7.2) (p=0.32). Scanning of subjects was performed on a 1,5T MRI scanner (TE minimum, TR=10000ms, FOV=26, matrix=128x128, section thickness=5mm). Diffusion MR images were obtained from 25 non-colinear directions with a b-value of 1000 s/mm2 along with a b=0 image with no diffusion gradients. Before MRI acquisition, a psychiatrist administered the following psychiatric tests: Cambridge Cognitve Test Examination (CAMCOG), Mini-Mental State Examination (MMSE), Montgomery-Aberg Depression Rating Scale (MADRS), and Hamilton Rating Scale of Depression (HAM-D). No significant differences were found on demographic data between groups. Voxelwise statistical analysis of FA data was carried out using Tract-Based Spatial Statistics (TBSS), part of FSL program. TBSS projects all subjects\' FA data onto a mean FA tract skeleton, before applying voxelwise cross-subject statistics. Differences between groups were assessed controlling for age. Results: The mean score from cognitive assessment for the whole depression group was: CAMCOG=82,94 ± 13,95 and MMSE=25,21 ± 3,74; and for controls: CAMCOG=90,83 ± 8,88 (p=0,017) and MMSE=27,86 ± 1,99 (p=0,004). Results of depressive symptom assessment for the patient group were MADRS=23.23 ± 8.60 HAM-D=18.64 ± 6.17 and MADRS=1.39 ± 1.20, HAM-D=2.67 ± 1.57 for control group. After controlling for age, geriatric depressed subjects had no significant differences on FA and on MD parameters. No significant correlations were found between scores from cognitive tests (CAMCOG and MMSE), and FA or MD parameters. Similar results were obtained after correlating scores from scales measuring depressive symptoms (MADRS and HAM-D) and FA or MD parameters. Conclusions: There was no significant difference in FA or MD values between elderly depressed and elderly without depression when the brain is analyzed without a ROI previously determined. There was no correlation, in the present sample, between cognitive assessment and FA or MD, neither between severity of depression and these brain white matter parameters

This thesis examines the advantages to nonlinear least-squares (NLS) fitting of diffusion-weighted MRI data over the commonly used linear least-squares (LLS) approach. A modified fitting algorithm is proposed which accounts for the positive bias experienced in magnitude images at low SNR. For b-values in the clinical range (~1000 s/mm2), the increase in precision of FA and fibre orientation estimates is almost negligible, except at very high anisotropy. The optimal b-value for estimating tensor parameters was slightly higher for NLS. The primary advantage to NLS was improved performance at high b-values, for which complex fibre architectures were more easily resolved. This was demonstrated using a model-selection classifier based on higher-order diffusion models. Using a b-value of 3000 s/mm2 and magnitude-corrected NLS fitting, at least 10% of voxels in the brain exhibited diffusion profiles which could not be represented by the tensor model.

This thesis examines the advantages to nonlinear least-squares (NLS) fitting of diffusion-weighted MRI data over the commonly used linear least-squares (LLS) approach. A modified fitting algorithm is proposed which accounts for the positive bias experienced in magnitude images at low SNR. For b-values in the clinical range (~1000 s/mm2), the increase in precision of FA and fibre orientation estimates is almost negligible, except at very high anisotropy. The optimal b-value for estimating tensor parameters was slightly higher for NLS. The primary advantage to NLS was improved performance at high b-values, for which complex fibre architectures were more easily resolved. This was demonstrated using a model-selection classifier based on higher-order diffusion models. Using a b-value of 3000 s/mm2 and magnitude-corrected NLS fitting, at least 10% of voxels in the brain exhibited diffusion profiles which could not be represented by the tensor model.

Attention deficit/hyperactivity disorder (ADHD) is a common disease with a worldwide prevalence of 5% on preschool children. It has been reported that ADHD patients have volume variant in partial brain regions. Futhermore, functional magnetic resonance imaging have also been used to detect function variant possibility in particular brain regions. In the last decade, some researchers used diffusion MR imaging to investigate the abnormality of neural fibers in disease involved with central nervous system. In general, the diffusion anisotropy of white matter in both ADHD patients and healthy subjects can be estimated seperately to undergo inter-subject comparison. While previous studies often used the popular ICBM brain template (MNI152), this study applied a self-made template of Taiwan adolescents as the common space of image normailization. In this work, group comparison of diffusion fractional anisotropy was performing by using two methods, TBSS and VBM. Both manners found a decreased FA in white matter of ADHD subjects compared with normal control group. However, regions detected by different methods showed low reproducibility. The areas of significant difference include inferior longitudinal fasciculus¡Binternal capsule¡Bexternal capsule¡Bsuperior longitudinal fasciculus¡Boptic radiation¡Bsuperior frontal¡Bsuperior region of corona radiata¡Bcorticospinal tract¡Bposterior region of corona radiata / superior longitudinal fasciculus¡Bsuperior fronto-occipital fasciculus¡Banterior region of corona radiata¡Bgenu of corpus callosum nerve fibers.

Attention deficit hyperactivity disorder (ADHD) is a neurobehavior developmental disorder that affects around 7.5% of Taiwan children. With the use of magnetic resonance imaging , many results have been reported that ADHD patients have volume atrophy in gray matter and dysfunction in couples of cortical regions. In recent years, diffusion MR imaging with diffusion-sensitizing gradients has been used to investigate the abnormality of neural fibers in disease involved with central nervous system. In this study, the anisotropy of white matter in both ADHD patients and age-matched healthy subjects was estimated using diffusion tensor imaging to undergo inter-subject comparison. In this work, a significant decrease (FWE-corrected p-value <0.05) of FA values has been found in white matter of adolescents diagnosed as ADHD patients, compared with normal controls group. The areas that confirmed by two different algorithms of inter-subject comparison are mainly diffused on white matter region, including middle cerebellar peduncle, left inferior longitudinal fasciculus, internal capsule, left optic radiation, external capsule, splenium of the corpus callosum, superior longitudinal fasciculus, superior frontal and parietal-occipital nerve fibers.

Diffusion tensor imaging (DTI) is a noninvasive MRI technique used to assess white matter (WM) integrity, fiber orientation, and structural connectivity (SC) using water diffusion properties. DTI techniques are rapidly evolving and are now having a dramatic effect on depression research. Major depressive disorder (MDD) is highly prevalent and a leading cause of worldwide disability. Despite decades of research, the neurobiology of MDD remains poorly understood. MDD is increasingly viewed as a disorder of neural circuitry in which a network of brain regions involved in mood regulation is dysfunctional. In an effort to better understand the neurobiology of MDD and develop more effective treatments, much research has focused on delineating the structure of this mood regulation network. Although many studies have focused on the structural connectivity of the mood regulation network, findings using DTI are highly variable, likely due to many technical and analytical limitations. Further, structural connectivity pattern analyses have not been adequately utilized in specific clinical contexts where they would likely have high relevance, e.g., the use of white matter deep brain stimulation (DBS) as an investigational treatment for depression. In this dissertation, we performed a comprehensive analysis of structural WM integrity in a large sample of depressed patients and demonstrated that disruption of WM does not play a major role in the neurobiology of MDD. Using graph theory analysis to assess organization of neural network, we elucidated the importance of the WM network in MDD. As an extension of this WM network analysis, we identified the necessary and sufficient WM tracts (circuit) that mediate the response of subcallosal cingulate cortex DBS treatment for depression; this work showed that such analyses may be useful in prospective target selection. Collectively, these findings contribute to better understanding of depression as a neural network disorder and possibly will improve efficacy of SCC DBS.

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