Introdução: Déficits de memória episódica constituem o marcador cognitivo mais frequente em pacientes com Comprometimento Cognitivo Leve (CCL).Estudos prévios mostram que déficits de memória episódica podem ser minimizados nestes pacientes por intervenções comportamentais. Entretanto, os mecanismos cerebrais envolvidos nos efeitos do treino cognitivo ainda são pouco explorados. O objetivo deste estudo foi avaliar o correlato neural por ressonância magnética funcional de um treino breve de memória em pacientes com CCL e compará-los com os achados em idosos saudáveis. Foram avaliados 18 pacientes com CCL e 19 idosos controles com a utilização de ressonância magnética funcional (RMf) em uma tarefa de codificação de listas de palavras com diferentes graus de relação semântica antes e após uma sessão de treino de estratégias de memória. Na sessão pré-treino, os participantes foram instruídos a memorizar as palavras durante a sessão de RMf sem qualquer orientação sobre o uso de estratégias de codificação. Após um treino breve no qual estratégias específicas de organização e agrupamento semântico foram exercitadas, os sujeitos foram reconduzidos ao aparelho de ressonância magnética e realizaram a sessão pós-treino, na qual foram instruídos a utilizar a estratégia treinada durante o paradigma de codificação de palavras. Os resultados dos exames de ressonância magnética funcional foram processados e analisados com o programa FSL versão 4.1. Ambos os grupos apresentaram aumento no número de palavras evocadas associado ao uso da estratégia treinada. Em ambos os grupos foi observado um aumento do sinal BOLD após o treino em regiões do córtex pré-frontal dorsolateral esquerdo e do córtex parietal bilateral. No grupo de idosos controles, entretanto, foi observada também uma redução da ativação em regiões do córtex parietal posterior esquerdo e cíngulo posterior bilateral, do córtex pré-frontal medial e cíngulo anterior direitos, do lóbulo parietal inferior e do córtex temporal superior direitos, do córtex pré-frontal dorsolateral direiro e do córtex óribito-frontal bilateral. A interação grupo x tempo foi significativa em áreas do córtex pré-frontal dorsolateral e ventromedial direitos. Estes resultado indicam que existem diferenças no recrutamento de regiões pré-frontais em resposta ao uso de estratégias de codificação em paradigmas de codificação de palavras entre pacientes com CCL e idosos cognitivamente saudáveis / The present studyinvestigated the effects of different applicationsof verbal learning strategies duringepisodicmemory encoding in patients with Mild Cognitive Impairment (MCI) (n=18) and normal controls (n=17) using functional magnetic resonance imaging (fMRI).The main goal of this study was to verify whether externally guided increases in verbal learning strategy application during episodic memory encoding modulate brain activity in memory-related networks in the same level in MCI as in controls. Participantswerescanned twice, using a word-list encoding fMRI paradigm.In the first session, self-initiated encoding strategies were used to intentionally memorize words during encoding. In the second session, participants received an explicit instruction to apply a semantic organization strategy (i.e. semantic clustering)to perform the task. The fMRI word list learning paradigm consisted of alternating blocks of encoding and resting baseline conditions. To perform the spontaneous fMRI session, participants were not instructed about the semantic organization of the words in the lists beforehand or given any practice with related lists. Therefore, any grouping by category observed in the subsequent free recall at the end of this fMRI acquisition was presumed to be self-initiated by the subject. At the end of the spontaneous session, each subject received a brief period of guidance or instructions to apply semantic strategies and organize words in terms of semantic categories during encoding, using a new set of word lists. Immediately after practicing the application of the strategy, participants were scanned again using the same type of paradigm as in the first session, except for the use of new set of word lists and the explicit instruction to apply semantic clustering.Free recall and strategic index scores were assessedafter each session. fMRI brain activation and deactivation during encoding of word lists in memory-related networks were examined across sessions. Results from the fMRI analysis revealed that after the explicit orientation to apply the verbal learning strategy, greater recruitment of frontoparietal network regions were observed in both MCI and control groups in relation to the unconstrained encoding condition. Group-differences in functional deactivations, however, were observed in the medial prefrontal (mPFC) cortex and in the right superior frontal gyrus, two critical nodes of the default mode network, related to the absence of modulation in the activity of the mPFC, along with a lack of suppression of the right superior frontal gyrus in MCI, in response to the increased use of the encoding strategy. A different association between improvement in strategy use and session-related changes in activation of the medial orbitalfrontal cortex between groups was also confirmed. That is, improvements in strategy use in controls contribute to a great extent in the amount of deactivation in OFC, whereas in patients, only a small portion of the increase in activation in this region was predicted by increases in strategy application

Body dissatisfaction (BD) is a condition derived from negative thoughts and feelings about one's body and is a core symptom of the eating disorder anorexia nervosa (AN). Beingdissatisfied with one’s body is highly present in women and to some extent men. This might be a result of a skewed ideal in combination with social influences. In recent year, research on neurobiological risk factors as well as neuroscientific and cognitive mappings of AN and BD have gained traction, particularly when it comes to studies using neuroimaging- techniques and cognitive tests. Studies have identified brain regions (insular cortex, anterior cingulate cortex, parietal cortex, amygdala, dorsolateral and orbitofrontal areas of the prefrontal cortex) associated with the processing of body shape as well as dysfunctional processing of self-image and body satisfaction. Structural imaging studies of AN patients using CT and MRI have, in many cases, found reduced cerebral volume, increased spinal fluid (CSF) and enlarged ventricles. Usually, food and water restriction has been seen as the cause, and structural deficits in AN patients have shown to improve with weight gain after long-term recovery.

Submitted by Caroline Xavier (caroline.xavier@pucrs.br) on 2017-06-30T17:22:52Z No. of bitstreams: 1 DIS_ANIBAL_SOLON_HEINSFELD_COMPLETO.pdf: 12807619 bytes, checksum: d11b60094a8bde0d839a6f7a23bbb56c (MD5) / Made available in DSpace on 2017-06-30T17:22:52Z (GMT). No. of bitstreams: 1 DIS_ANIBAL_SOLON_HEINSFELD_COMPLETO.pdf: 12807619 bytes, checksum: d11b60094a8bde0d839a6f7a23bbb56c (MD5) Previous issue date: 2016-03-28 / O Espectro Autista (EA) compreende uma s?rie de desordens no desenvolvimento neurol?gico, caracterizado por defici?ncias sociais e dificuldades de comunica??o, comportamentos repetitivos e atrasos cognitivos. Atualmente, o diagn?stico do EA ? amplamente baseado em medi??es comportamentais, que pode ser demorado, e depende da coopera??o do paciente e da experi?ncia do examinador. Para mitigar esta limita??o, investigamos padr?es neurais que ajudem no diagn?stico de desordens do EA. Nesta disserta??o, usamos t?cnicas de deep learning, a fim de extrair caracter?sticas robustas de neuroimagens de pacientes com autismo. Neuroimagens cont?m cerca de 300.000 pontos espaciais, com aproximadamente 200 medi??es cada. As t?cnicas de deep learning s?o ?teis para extrair caracter?sticas relevantes que diferenciam autistas de n?o-autistas. Ao utilizar denoising autoencoders, uma t?cnica de deep learning espec?fica que visa reduzir a dimensionalidade dos dados, n?s superamos o estado da arte, atingindo 69% de acur?cia, comparado com o melhor resultado encontrado na literatura, com 60% de acur?cia. / Autism Spectrum Disorders (ASD) comprise a range of neurodevelopmental disorders, characterized by social deficits and communication difficulties, repetitive behaviors, and cognitive delays. The diagnosis of ASD is largely based on behavioral measurements, which can be timeconsuming and relies on the patient cooperation and examiner expertise. In order to address this limitation, we aim to investigate neural patterns to help in the diagnosis of ASD. In this dissertation, we use deep learning techniques to extract robust characteristics from neuroimages of autistic subject brain function. Since neuroimage contains about 300,000 spatial points, with approximately 200 temporal measurements each, deep learning techniques are useful in order to extract important features to discriminate ASD subjects from non-ASD. By using denoising autoencoders, a specific deep learning technique that aims to reduce data dimensionality, we surpass the state-of-the-art by achieving 69% of accuracy, compared to 60% using the same dataset.

Human structural and functional brain architecture is increasingly studied by applying the mathematical framework of complex networks to data from magnetic resonance imaging. Connections (edges) in such brain networks are commonly constructed using correlations of features between pairs of brain regions, such as regional morphology (across participants) or neurophysiological time series (within participants). Subsequent analyses frequently focus on summary network statistics calculated using the strongest correlations, but often neglect potential underlying shifts within the correlation distribution. This thesis presents methods for the construction and analysis of correlation-derived structural and functional brain networks, focusing on the implications of changes within the correlation distribution. First, schizophrenia is considered as an example disease which is known to present a reduction in mean correlation between regional neurophysiological time series. Previous studies reported increased network randomisation in schizophrenia, but these results may have been driven by inclusion of a greater number of noisy edges in patients’ networks, based on retention of a fixed proportion of the strongest edges during network thresholding. Here, a novel probabilistic thresholding procedure is applied, based on the realisation that the strongest edges are not necessarily most likely to be true following adjustment of edge probabilities for effects of participant in-scanner motion. Probabilistically thresholded functional networks show decreased randomness, and increased consistency across participants. Further, applying probabilistic thresholding eliminates increased network randomisation in schizophrenia, supporting the hypothesis that previously reported group differences originated in the application of standard thresholding approaches to patient networks with decreased functional correlations. Subsequently, healthy adolescent development is studied, to help understand the frequent emergence of psychiatric disorders in this period. Importantly, both structural and functional brain networks undergo maturational shifts in correlation distribution over adolescence. Due to reliance of structural correlation networks on a group of subjects, previous studies of adolescent structural network development divided groups into discrete age-bins. Here, a novel sliding-window method is used to describe adolescent development of structural correlation networks in a continuous manner. Moreover, networks are probabilistically thresholded by retaining edges that are most consistent across bootstrapped samples of participants, leading to clearer maturational trajectories. These structural networks show non-linear trajectories of adolescent development driven by changes in association cortical areas, compatible with a developmental process of pruning combined with consolidation of surviving connections. Robustness of the results is demonstrated using extensive sensitivity analyses. Finally, adolescent developmental changes in functional network architecture are described, focusing on the characterisation of unthresholded (fully weighted) networks. The distribution of functional correlations presents a non-uniform shift over adolescence. Initially strong cortical connections to primary sensorimotor areas further strengthen into adulthood, whereas association cortical and subcortical edges undergo a subtler reorganisation of functional connectivity. Furthermore, individual subcortical regions show distinct maturational profiles. Patterning of maturation according to known functional systems is affirmed by partitioning regions developing at similar rates into maturational modules. Taken together, this thesis comprises novel methods for the characterisation of disease-related and normative developmental changes in structural and functional correlation brain networks. These methods are generalizable to a wide range of scenarios, beyond the specific disease and developmental age-ranges presented herein.

INTRODUÇÃO: O Doppler Transcraniano funcional pode avaliar mudanças na velocidade do fluxo sanguíneo encefálico associadas a tarefas cognitivas e/ou sensitivo-motoras. Mede de maneira indireta a atividade metabólica de regiões cerebrais, segundo o princípio do acoplamento neurovascular. Os objetivos deste estudo foram: desenvolver um novo método de análise de Doppler transcraniano funcional para análise da lateralização hemisférica e verificar a capacidade deste novo método em diferenciar a lateralização hemisférica durante a execução de uma tarefa motora unimanual por indivíduos saudáveis. Adicionalmente, a lateralização hemisférica foi correlacionada com a preferência manual nestes indivíduos. MÉTODOS: Treze indivíduos saudáveis foram submetidos a um exame de Doppler transcraniano funcional durante uma prova de ativação motora manual (oposição de dedos). As sessões de Doppler transcraniano funcional foram realizadas com aparelho Doppler-Box Transcranial Doppler Unit. A prova manual compreendeu uma sequência de movimentos de oposição do primeiro e segundo dedos (thumb-tofinger opposition movement) realizado por uma mão e depois pela outra, em uma frequência de 1 movimento por segundo (1Hz) fornecida por um metrônomo digital. Durante a execução dos movimentos, foram insonadas simultaneamente as artérias cerebrais médias direita e esquerda. Para interpretação dos dados de Doppler transcraniano funcional desenvolvemos um novo programa de análise denominado FDAT, que tem vantagens de sofrer mínima influência de artefatos de ruído no sinal e de não assumir um formato pré-determinado da resposta hemodinâmica cerebral. Foi calculado um índice de lateralização (IL) como a diferença entre a velocidade relativa média da época de ativação e a velocidade relativa média da época de repouso para cada prova motora. Foi calculada a diferença dos valores de IL (ILe - ILd) provenientes da análise com cada método, obtendo-se um índice de ativação, próprio de cada sujeito. A comparação do índice de ativação durante a movimentação da mão direita, e durante a movimentação da mão esquerda, foi feita com o teste de Wilcoxon. A correlação entre o índice de ativação e a preferência manual avaliada pelo Inventário de Edimburgo foi avaliada pelo coeficiente rho de Spearman. RESULTADOS: Houve uma diferença estatisticamente significante entre o IA obtido durante a movimentação da mão direita ou da mão esquerda (p=0,02). Houve correlação estatisticamente significante entre a preferência manual e a assimetria na lateralização hemisférica identificada pelo Doppler Transcraniano funcional (rho = 0.85, p < 0.001). CONCLUSÕES: A análise do Doppler Transcraniano funcional mostrou-se viável pelo método proposto, capaz de avaliar o grau de lateralização hemisférica em uma prova de ativação motora, com boa correlação com a preferência manual. Trata-se de uma ferramenta prática, não invasiva e de baixo custo para a avaliação da lateralização hemisférica em determinadas provas funcionais / INTRODUCTION: Functional transcranial Doppler is a method for the assessment of changes in blood flow velocity of the middle cerebral artery. An asymmetric increase in blood flow velocity is a marker of hemispheric lateralization during unimanual motor task performance. The aims of this study were to propose a novel and efficient method for functional transcranial Doppler analysis based on cubic smoothing splines, and to verify the ability of this method to identify hemispheric lateralization during unimanual motor task performance in healthy subjects. In addition, hemispheric lateralization was correlated with handedness in these subjects. METHODS: Thirteen healthy subjects participated in the study. Blood flow velocities in the right and left middle cerebral arteries were recorded using functional transcranial Doppler during a finger-tapping task with either the right or left hand. Data were analyzed with a multi-step new method that included: baseline determination, raw data normalization, smoothing, lateralization Index calculation, definition of rest and motor task epochs and activation Index calculation. A positive activation Index reflects right-hemisphere lateralization and a negative activation index, left hemisphere lateralization. RESULTS: There was a statistically significant difference between the activation index obtained during right or left hand movements (p=0.02). Hand dominance was significantly correlated with asymmetry in hemispheric lateralization assessed with functional transcranial Doppler (rho = 0.85, p<0.001). CONCLUSIONS: This novel method for functional transcranial Doppler analysis was capable to assess the hemispheric lateralization during motor task performance, and correlated well with handedness. It is a practical, non-invasive and unexpensive tool for the assessment of hemispheric lateralization.

Despite extensive evidence documenting abnormal hypothalamic-pituitary-adrenal (HPA) axis functioning as a risk factor for the development of depression and other psychiatric disorders, and experimental evidence from acute stress manipulations, the effects of sustained cortisol alterations on clinically relevant cognitive-behavioural and neural processing remain poorly understood. The aim of this thesis was to characterise how non-acute changes in cortisol levels modify behavioural and neural biases implicated in stress-related disorders by following two complementary lines of evidence: firstly, by increasing cortisol via a direct pharmacological intervention; and secondly, by testing the ability of gut microbiota manipulations to alter cortisol reactivity. The first study found that sustained increases in cortisol following 10-day administration of hydrocortisone were associated with altered memory and emotional processing in healthy volunteers. Specifically, participants receiving hydrocortisone showed enhanced recognition of emotional words, while their neutral memory performance was unaffected despite lower parahippocampal and occipital activation during viewing and encoding of neutral pictures. Furthermore, we found that resting-state functional connectivity between limbic-temporal regions of interest (amygdala and hippocampus) and the striatum (head of the caudate), as well as frontal and prelimbic cortices was decreased. In contrast, hippocampal and visual processing during negative facial expressions, and functional connectivity between the amygdala and the brainstem at rest, were increased in the hydrocortisone versus placebo groups. Overall, these findings suggest that non-acute increases in glucocorticoids enhance processing of emotionally salient information in limbic-temporal regions, which may modulate further neural mechanisms of sensory and homeostatic relevance. Enhancements in declarative emotional memory following hydrocortisone also implicate the modulation of amygdalar-hippocampal interactions by cortisol. Conversely, neutral stimulus processing was found to be either reduced or unaffected across a number of cognitive and memory domains. A specific increase for negative processing was further supported by poorer self-reported well-being at the mid-point of the study in participants receiving hydrocortisone. In a separate study exploring the ability of prebiotic supplements to affect cortisol reactivity and emotional processing, a Bimuno-galactooligosaccharide prebiotic was found to reduce the waking cortisol response and increase positive versus negative attentional processing in healthy volunteers. While these effects were not found to be associated, they provide initial promising evidence of the ability to target the HPA axis and emotional processing via the gut microbiota in humans. Overall, this thesis supports the idea that stress-induced physiological changes after prolonged or repeated cortisol exposure are associated with neural and behavioural alterations, which in turn have been crucial in understanding neuropsychological mechanisms underlying psychiatric disease. A better stratification of the effects of sustained HPA axis alterations on psychiatrically relevant cognitive-emotional domains and neural mechanisms thus remains of high priority.

This study aims to shed light on how and when mechanisms of the human brain evolved to support complex cognition and language. The field of evolutionary cognitive archaeology asserts that prehistoric technologies, as products of past cognition in action, are informative of the minimum cognitive and linguistic abilities that hominins needed to possess for their production. Previous researchers attempted to reconstruct the neural correlates of two Early Stone Age (ESA) tool industries, the 2.6 million-year-old Oldowan industry and the 0.7 million-year-old late Acheulian industry, by using positron emission tomography (PET) to observe the functional activation occurring in the brains of trained and expert stone knappers after making these different tool types. Because of evidence for overlap between the knapping and language circuits of the brain and increased anterior frontal activity during Acheulian tool production, these researchers argued that their results 1) indicate increased cognitive demands for late Acheulian tool production relative to Oldowan tool production and 2) support a technological origin for language, meaning that certain language functions co-opted the neural substrate and functions that were already established for toolmaking and tool use. Because of the motion limiting aspects of PET, however, these studies were unable to record the hemodynamic response of naturalistic stone knapping in real-time. They also were unable to observe the functional activation associated with the earliest stage of learning, which is likely to differ from late stage learning or expertise. Furthermore, any conclusion regarding a technological origin for language is problematic if it relies on data obtained from participants who learned to knap with verbal instruction. To test these two claims, this dissertation utilized a neuroimaging technique called functional near-infrared spectroscopy (fNIRS) to explore the neural correlates of real-time, naturalistic Oldowan and Acheulian stone knapping at three different points in learning. Participants in the study were separated into two groups to learn ESA knapping skills. Both groups watched the same video tutorials that depicted an expert’s hands as he made stone tools, but those in the verbal group heard spoken instructions, while those in the nonverbal group watched a version with the sound turned off. Functional brain images were reconstructed from the digitized landmarks of each participant’s head and from the optical data. An analysis of variance (ANOVA) revealed a clearer distinction between the neural processes of Oldowan and Acheulian tool manufacturing tasks than has previously been demonstrated. Only the Acheulian task recruited a frontotemporal working memory network. Selection for individuals with increased working memory capacities, which would have allowed them to make increasingly complex tools to gain access to novel dietary items, may have spurred the evolution of larger brain size in the genus Homo during the early Pleistocene. The results also demonstrated that the presence or absence of language during training dictated which higher-order cognitive areas of the brain become engaged and at what point in training. Thus, the results of previous neuroarchaeological studies reflect a very specific condition of stone knapping skill acquisition that involves linguistic instruction, which may not be analogous to how skills were transmitted during the ESA. Finally, evidence of overlap between left hemisphere language and stone knapping circuits among the participants in the nonverbal group lends additional support for the technological origin for language hypothesis.

Chronic musculoskeletal pain is a leading cause of disability worldwide yet the mechanisms of chronification and neural responses to effective treatment remain elusive. Non-invasive imaging techniques are useful for investigating brain alterations associated with health and disease. Thus the overall goal of this dissertation was to investigate the white (WM) and grey matter (GM) structural differences in patients with musculoskeletal pain before and after psychotherapeutic intervention: cognitive behavioral therapy (CBT). To aid in the interpretation of clinical findings, we used a novel porcine model of low back pain-like pathophysiology and developed a post-mortem, in situ, neuroimaging approach to facilitate translational investigation. The first objective of this dissertation (Chapter 2) was to identify structural brain alterations in chronic pain patients compared to healthy controls. To achieve this, we examined GM volume and diffusivity as well as WM metrics of complexity, density, and connectivity. Consistent with the literature, we observed robust differences in GM volume across a number of brain regions in chronic pain patients, however, findings of increased GM volume in several regions are in contrast to previous reports. We also identified WM changes, with pain patients exhibiting reduced WM density in tracts that project to descending pain modulatory regions as well as increased connectivity to default mode network structures, and bidirectional alterations in complexity. These findings may reflect network level dysfunction in patients with chronic pain. The second aim (Chapter 3) was to investigate reversibility or neuroplasticity of structural alterations in the chronic pain brain following CBT compared to an active control group. Longitudinal evaluation was carried out at baseline, following 11-week intervention, and a four-month follow-up. Similarly, we conducted structural brain assessments including GM morphometry and WM complexity and connectivity. We did not observe GM volumetric or WM connectivity changes, but we did discover differences in WM complexity after therapy and at follow-up visits. To facilitate mechanistic investigation of pain related brain changes, we used a novel porcine model of low back pain-like pathophysiology (Chapter 6). This model replicates hallmarks of chronic pain, such as soft tissue injury and movement alteration. We also developed a novel protocol to perform translational post-mortem, in situ, neuroimaging in our porcine model to reproduce WM and GM findings observed in humans, followed by a unique perfusion and immersion fixation protocol to enable histological assessment (Chapter 4). In conclusion, our clinical data suggest robust structural brain alterations in patients with chronic pain as compared to healthy individuals and in response to therapeutic intervention. However, the mechanism of these brain changes remains unknown. Therefore, we propose to use a porcine model of musculoskeletal pain with a novel neuroimaging protocol to promote mechanistic investigation and expand our interpretation of clinical findings.

Cannabis use initiated during adolescence may precipitate lasting consequences on the brain and behavioral health of the individual. However, research on the risk factors for cannabis use during adolescence has been largely cross-sectional in design. Despite the few prospective studies, even less is known about the neurobiological predictors. This dissertation improves on the extant literature by leveraging a large longitudinal study to uncover the predictors of cannabis use in adolescent samples collected prior to exposure. All data were drawn from the IMAGEN study and contained a large sample of adolescents studied at age 14 (N=2,224), and followed up at age 16 and 19. Participants were richly characterized using psychosocial questionnaires, structural and functional MRI, and genetic measurements. Two hypothesis-driven studies focused on amygdala reactivity and two data-driven studies across the feature domains were completed to characterize cannabis use in adolescence. The first study was cross-sectional and identified bilateral amygdala hyperactivity to angry faces in a sample reporting cannabis use by age 14 (n=70). The second study determined this amygdala effect was predictive of cannabis use by studying a sample of cannabis-naïve participants at age 14 who then used cannabis by age 19 (n=525). A dose-response relationship was observed such that heavy cannabis users exhibited higher amygdala reactivity. Exploratory analyses suggested amygdala reactivity decreased from age 14 to 19 within the cannabis sample, although statistical significance was not found. In the third study, data-driven machine learning analyses predicted cannabis initiation by age 16 separately for males (n=207) and females (n=158) using data from all feature domains. These analyses identified a sparse set of shared psychosocial predictors, whereas the identified brain predictors exhibited sex- and drug-specificity. Additional analyses predicted initiation by age 19 and identified a sparse set of psychosocial predictors for females only (n=145). The final study improved on drug-specificity by performing differential prediction analyses between matched samples of participants who initiated cannabis+binge drinking vs. binge drinking only by age 16 (males n=178; females n=148). A sparse subset of psychosocial predictors identified in the third study was reproduced, and novel brain predictors were identified. Those analyses were unique as they compared two machine learning algorithms, namely regularized logistic regression and random forest analyses. These studies substantiated the use of both hypothesis- and data-driven prediction analyses applied to large longitudinal datasets. They also addressed common issues related to human addiction research by examining sex-differences and drug-specificity. Critically, these studies uncovered predictors of use in samples collected prior to cannabis-exposure. The identified predictors are therefore disentangled from consequences of use. Results from all studies inform etiological mechanisms influencing cannabis use in adolescence. These findings can also be used to stratify risk in vulnerable adolescents and inform targets for interventions designed to curb use.

Anxiety disorders (ADs) and stress-related disorders are some of the most common psychiatric disorders in the United States. Like other c0mplex psychiatric illness, genetics and neuroimaging research has focused on understanding their underlying neurobiology. Areas within the fear-network play important roles in threat perception, fear conditioning/learning, cognitive processing, and modulation of fear responses including contextual modulation and extinction and have been implicated in ADs as well as stress disorders such as posttraumatic stress disorder (PTSD). The primary gap in the current search for underlying biological mechanisms is in whether biomarkers associated with disorders share genetic influences with the disorders they index. Therefore, the aims of this dissertation are: 1) to examine the shared etiology of PTSD and threat-related brain regions while accounting for trauma using a large sample of male twins who served in the military during the Vietnam War; 2) to elucidate the shared and specific risk factors (genetic, familial environment and unique environment) and their roles amongst fear and anxiety domains in children; and 3) to examine whether brain regions previously implicated in fear processing and anxiety are significantly associated with a genetic factor score indexing fear and anxiety measures in a child sample. Using biometrical twin modeling this dissertation produced several novel findings regarding etiology of PTSD, threat-related domains and associated brain morphometry. Analyses investigating brain morphometric differences as potential endophenotypes for PTSD provided preliminary evidence that their phenotypic association is largely accounted for by environmental influences, specifically trauma exposure. However, sample size-induced model instability limits the ability to make definitive conclusions. Examining domains of fear and anxiety in children suggested a substantial genetic overlap between the two. Finally, the incorporation of a genetic factor score derived from the results of the biometrical modeling of fear and anxiety provided preliminary evidence for a genetic relationship between fear/anxiety and brain regions of interest. Although these results should be interpreted within the context of important limitations, they provide clear evidence that additional research into the genetic relationship between brain regions and disorders with larger sample sizes is justified.