Orientador: Gabriela Castellano / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Fisica Gleb Wataghin / Made available in DSpace on 2018-08-16T08:25:23Z (GMT). No. of bitstreams: 1 Silva_ElvisLirada_D.pdf: 63417799 bytes, checksum: f7f42b73809b23b9c1b761e184412c98 (MD5) Previous issue date: 2010 / Resumo: Nas últimas décadas, vêm crescendo muito o ramo da Neurociência que estuda a integração neuronal entre áreas cerebrais, onde tal integração é mediada pela chamada conectividade efetiva. A conectividade efetiva pode ser definida como a influência que um sistema neural exerce sobre o outro, tanto ao nível sináptico quanto ao nível cortical. Neste contexto, é cada vez maior a participação de físicos e matemáticos na elaboração de técnicas matemáticas que permitam investigar o comportamento desses sistemas neurais através de experimentos baseados na Ressonância Magnètica funcional (fMRI) e na Eletroencefalografia (EEG). Uma das técnicas que vem sendo amplamente utilizada para estimar a conectividade efetiva entre áreas cerebrais é a denominada Modelagem Causal Dinâmica (DCM), que é uma técnica que incorpora à sua teoria a não-linearidade e a dinâmica de sistemas biológicos. Este trabalho teve por objetivo estudar a conectividade entre áreas cerebrais através da DCM em experimentos de fMRI. Foram estudados dois sistemas neurais. O primeiro deles, o sistema motor, nos possibilitou verificar a plausibilidade da DCM, al'em de averiguarmos as diferenças na conectividade entre as áreas do sistema motor quando indivíduos destros movimentaram os dedos da mão direita e da mão esquerda. Encontramos que a conectividade efetiva é maior quando tais sujeitos movimentaram a mão esquerda, que supomos ser em decorrência da maior dificuldade (inerente às pessoas destras) em mover essa mão. O segundo sistema estudado foi o sistema de reconhecimento de faces emotivas (onde a emoção foi representada por níveis de tristeza) de indivíduos sadios, indivíduos com a doença de Parkinson e indivíduos com a doença de Parkinson e depressão. Neste estudo foi possível verificar através dos resultados da conectividade a falta de habilidade de sujeitos com Parkinson e sujeitos com Parkinson e depressão em reconhecer faces humanas emotivas. Sugerimos que esta falta de habilidade está relacionada principalmente com uma disfunção da atividade do córtex pré-frontal e consequentemente com um aumento da conectividade efetiva desta área com as outras áreas do sistema / Abstract: The branch of Neuroscience that studies functional integration between cerebral areas has recently shown a significant growth. Functional integration refers to the interactions among specialized neuronal populations, where the integration is mediated by the so called effective connectivity. Effective connectivity is defined as the influence that regions, which encompass given neuronal populations, exert on each other. In this process, physicists and mathematicians play an important role in the development of mathematical techniques that allow to investigate the behavior of these neuronal systems through experiments based on functional Magnetic Resonance Imaging (fMRI) and Electroencephalography (EEG). One technique that has been widely used to calculate the effective connectivity between brain areas is known as Dynamic Causal Modeling (DCM), which is a technique that embraces in its theory the nonlinearity and dynamics of biological systems. This work aimed to study the effective connectivity between brain areas through the DCM on fMRI experiments. Two neural systems were studied. The first one was the motor system, which allowed us to check the plausibility of DCM, and to investigate the differences in connectivity between areas of the motor system when right-handed subjects moved the fingers of their right and left hands. We found that the effective connectivity was larger when these individuals moved their left hands, due to a greater difficulty (inherent in right-handed people) in moving this hand. The second system studied was the system for recognition of emotional faces (with sadness as the emotion) of healthy subjects, subjects with Parkinson¿s disease and subjects with Parkinson¿s disease and depression. In this study we verified through the connectivity results the inability of subjects with Parkinson¿s disease and subjects with Parkinson¿s disease and depression to recognize human emotional faces. We suggest that this inability is mainly related to a dysfunction of the neuronal activity of the prefrontal cortex and a consequent increase in the effective connectivity of this area with other areas of the system / Doutorado / Física / Doutor em Ciências

Orientadores: Fernando Cendes, Benito Pereira Damasceno, Gabriela Castellano / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Ciências Médicas / Made available in DSpace on 2018-08-17T05:21:26Z (GMT). No. of bitstreams: 1 Pereira_FabricioRamosSilvestre_M.pdf: 49779303 bytes, checksum: 3c2d2949aa4cb1bb74eaec511dfeb084 (MD5) Previous issue date: 2010 / Resumo: Um número crescente de estudos sobre conectividade cerebral tem-se destacado na área da Neurociência. Esses estudos almejam entender como diferentes regiões no cérebro estão relacionadas. Para isso, diversas técnicas podem ser empregadas, dentre elas, a ressonância magnética funcional (fMRI). Baseada no sinal BOLD (Blood Oxigenation Level Dependence), a fMRI constitui-se de séries temporais que permitem estimar padrões conectividade efetiva (ecMRI) e funcional (fcMRI). Esta é definida como uma sincronização entre atividades neurais de regiões cerebrais remotas, aquela, como a influência que a atividade neural em uma região cerebral exerce sobre outra área. O presente trabalho consiste no estudo da conectividade funcional em estado de repouso (resting-state) dos hipocampos de três grupos de indivíduos: controles, pacientes com ELTM esquerda e pacientes com ELTM direita. Os resultados mostraram diferenças na conectividade funcional tanto entre controles versus pacientes (apenas os controles apresentaram correlação entre ambos os hipocampos) quanto entre pacientes com ELTM esquerda versus pacientes com ELTM direita (os valores de conectividade funcional dos pacientes com ELTM à direita foram significativamente superiores aos valores do grupo com ELTM à esquerda). Os resultados demonstram que o uso de técnicas para avaliam a conectividade funcional pode representar uma potente ferramenta no estudo da plasticidade cerebral em pacientes com epilepsia mesial temporal além de possibilitar a análise da rede cerebral padrão em sujeitos controles / Abstract: A growing number of studies on brain connectivity have been deployed in the area of Neuroscience. These studies aim to understand how different brain regions are related. Indeed, several techniques can be employed such as the functional magnetic resonance imaging (fMRI). Based on the BOLD signal (Blood Oxigenation Level Dependence), the fRMI consists of time series to estimate functional (fcMRI) and effective connectivity (ecMRI) patterns. The former is defined as synchronization between neural activities in remote brain regions and the later as the influence that one neural activity exerts on another area. The present work studies functional connectivity at rest (resting-state) of hippocampi from three groups: controls, patients with left MTLE and patients with right MTLE. The results showed differences in functional connectivity between both patients versus controls (only the controls showed correlation between both hippocampi) and between patients with left MTLE versus right MTLE (values of functional connectivity in patients with right MTLE were significantly higher than the group with left MTLE). The results demonstrated that the use of techniques that assess functional connectivity can be a powerful tool in the study of brain plasticity in patients with MTLE / Mestrado / Ciencias Biomedicas / Mestre em Ciências Médicas

O dito popular afirma que quando uma pessoa perde um dos sentidos há uma compensação por parte dos outros sentidos para suprir a perda. Através de três experimentos psicofísicos baseados no modelo de Posner (Inibição de Retorno) e técnicas de Ressonância Magnética Funcional, surdos congênitos foram comparados a pessoas ouvintes com o objetivo de verificar se os surdos possuem processos atencionais diferentes dos ouvintes, e se as mesmas áreas corticais como a área de Wernicke, Broca e Córtex auditivo - eram ativadas em ambos os grupos. A tarefa consistia em pressionar um botão todas as vezes que os sujeitos detectassem a presença de um quadrado maior (alvo) apresentado em uma tela, enquanto também eram apresentados quadrados menores (pista) ora do mesmo lado, ora do lado oposto ao alvo. Através do Experimento I se pôde verificar que ambos os grupos apresentaram os fenômenos clássicos do Paradigma de Posner: Facilitação ou Inibição de Retorno, o que denotou a possibilidade de mecanismos atencionais semelhantes para ambos os grupos. Foi observado, porém, que os ouvintes eram mais rápidos que os surdos para responder à tarefa quando o intervalo temporal entre pista e alvo era longo (800ms), comparado ao tempo que levavam para responder quando o intervalo entre pista e alvo era curto (100 ms). O Experimento I suscitou a hipótese de que os surdos possivelmente apresentassem uma diferença de processamento temporal. No Experimento I todas as condições eram apresentadas de forma randômica. O Experimento II foi elaborado com o objetivo de por em evidência a 22 diferença dos TRM para intervalos curtos e longos, portanto os intervalos entre pista e alvo passaram a ser apresentados de forma fixa. Ao comparar os resultados do Experimento I com os do Experimento II (Intervalos Temporais Fixos), se pode verificar que os ouvintes apresentaram Tempos de Reação Manual mais lentos, enquanto os surdos apresentaram as mesmas médias a despeito da vantagem temporal, o que levou a sugerir a hipótese de que os surdos apresentem um déficit no processamento temporal. O experimento III consistiu na utilização do Paradigma de Posner enquanto os sujeitos eram submetidos ao exame de Ressonância Magnética Funcional com o objetivo de investigar se as regiões corticais ativadas poderiam ser semelhantes nos dois grupos. As imagens por Ressonância Magnética Funcional (RMF) demonstraram ativações nas áreas de Wernickie, Broca, e córtex auditivo em ambos os grupos enquanto executavam a tarefa, que embora não possuísse nenhum contexto semântico explícito, possuía o tempo como o principal parâmetro físico no qual os sujeitos pudessem se basear para melhorar o desempenho na tarefa. O tempo é um dos parâmetros físicos primários da língua oral, diferente da língua de sinais que possui o parâmetro visual e espacial como primário. Os resultados sugerem que as ativações corticais nos centros de audição e fala podem indicar uma plasticidade cruzada no grupo de surdos. Ainda, a participação do córtex auditivo no processamento da elaboração de estratégias para responder a uma tarefa que não contenha um contexto semântico explicito possivelmente indica sua participação no processamento de linguagem. / It is popularly said that when a person loses one sense, there is a compensation by the other remaining senses to suppress the loss. Throughout three Phsycophysic Experiments based on Inhibition of Return Posners Paradigm and Functional Magnetic Resonance (fMRI) Techniques, congenital deaf people were compared to normal hearing people in order to check if deaf people possess different attentional pattern compared to normal hearing people, and if the same cortical areas Wernicke and Brocas area and Hearing Cortex were activated in both groups. Experiment I consisted on pressing a button every time the presence of a big square (target) was detected by subjects while non-predictive small squares (cue) were also presented at the same or opposite side of the target. At Experiment I it was observed that both groups presented Posners Paradigm classical phenomena: Facilitation or Inhibition of Return, what suggested the possibility that attentional pattern may be similar to both groups. Therefore, it was observed that normal hearing people were faster than deaf people to respond to the task when time interval between cue and target was long (800 ms) when compared to the time they spent to respond when time interval between cue and target as short (100 ms). 24 Experiment I raised the hypotheses that possibly deaf people may present a temporal processing difference. At Experiment I every condition was randomly presented. Experiment II was elaborated to highlight MRT differences between short and long time intervals, so every time interval was presented on a fixed order. Comparison of Experiment I and II (Fixed Time Intervals) showed that normal hearing people presented shorter Manual Reaction Times (MRT), while deaf people kept the same averages despite the temporal advantage, what suggested that deaf people may present a deficit on temporal processing. Experiment III used Posners Paradigm while subjects were submitted to fMRI scanning in order to check if activated cortical regions could be similar in both groups. fMRI images demonstrate Wernicke and Brocas area and hearing cortex activations in both groups while executing the task, which, although did not have any explicit semantic content, had time as the main physical parameter on which subjects could be based to increase performance to respond to the task. Time is one of the oral language primary physical parameter, different of signed language which has visual and spatial parameters as primaries. Results suggest that cortical audition center activations may indicate a cross-modal plasticity at the deaf group. Yet, participation of hearing cortex on strategy elaboration to respond to a task which does not have any explicit semantic content possibly indicates the participation of hearing cortex on language processing.

Le neurofeedback (NF) est une technique consistant à renvoyer à un individu des informations sur son activité cérébrale en temps réel, lui permettant ainsi d'apprendre à mieux en contrôler certains aspects pour la réorganiser de manière durable. Des effets spécifiques sur les fonctions émotionnelles, cognitives ou comportementales du sujet sont supposés accompagner l'entraînement par NF, ce qui fait du NF une technique prometteuse pour la rééducation du cerveau de patients souffrant de troubles neurologiques ou psychiatriques et pour l'optimisation de la performance chez les sujets sains. Le NF a été étudié comme outil de rééducation cérébrale dans un grand nombre de troubles neurologiques et psychiatriques. Pourtant, son déploiement au sein de l'arsenal thérapeutique est restreint par le manque de preuves concluantes sur sa réelle efficacité. Les limitations inhérentes aux modalités de mesures de l'activité cérébrale pourraient être une des raisons à l'origine de cette efficacité débattue. En effet, la plupart des approches de NF reposent sur l'exploitation d'un seul type de modalité, l'EEG et l'IRMf étant les plus répandues. Alors que l'EEG est peu coûteux et bénéficie d'une haute résolution temporelle (milliseconde), sa résolution spatiale (quelques centimètres) est limitée par la conduction volumique de la tête et le nombre d'électrodes employées. De plus, la localisation de sources à partir de l'EEG est imprécise du fait qu'elle constitue un problème inverse mal posé. De manière complémentaire, l'IRMf rend possible l'auto-régulation de régions cérébrales spécifiques avec une haute résolution spatiale (millimètres) mais pâtit d'une faible résolution temporelle (seconde). La combinaison de l'EEG et de l'IRMf s'est révélée fructueuse dans l'étude des fonctions cérébrales chez l'homme, pourtant elle a rarement été exploitée pour des applications de NF. Dans le cadre du NF, elle permet d'évaluer et de valider différents paradigmes de manière transmodale. Mais surtout, elle ouvre un champ de possibilités pour le développement de nouvelles approches de NF qui mélangeraient les deux modalités, soit à l'étape de calibration soit pour produire un signal de NF bimodal. La combinaison de l'EEG et de l'IRMf pose de nombreux défis relatifs à la physiologie, au design expérimental, à la qualité des données, ainsi qu'à leur analyse/intégration et leur interprétation. Ces défis sont d'autant plus grands si l'EEG et l'IRMf sont destinés à être utilisés simultanément pour le calcul du signal de NF, du fait de la contrainte de temps-réel et de la difficulté de définir des tâches expérimentales compatibles avec les natures divergentes de l'EEG et de l'IRMf. La partie théorique de cette thèse vise à identifier les aspects méthodologiques qui diffèrent entre le NF-EEG et le NF-IRMf ainsi qu'à examiner les motivations et les stratégies pour combiner l'EEG et l'IRMf dans le cadre du NF. Parmi ces différentes stratégies de combinaison, nous avons choisi de nous focaliser sur le NF-EEG-IRMf bimodal car il apparaît comme une approche prometteuse et n'a quasiment pas été étudié. La faisabilité de cette approche a récemment été démontrée, faisant ainsi place à un tout nouveau champ d'investigation. Cette thèse vise à répondre aux questions suivantes : quelle est la valeur ajoutée du NF bimodal par rapport au NF unimodal ; existe-t-il des mécanismes spécifiques engagés lorsqu'un individu apprend à contrôler deux signaux de NF ; comment intégrer l'EEG et l'IRMf pour produire un seul feedback ? La partie expérimentale de cette thèse se focalise donc sur le développement et l'évaluation de méthodes de NF-EEG-IRMf. Afin de conduire des expériences de NF bimodal, nous commençons par mettre en place une plateforme EEG-IRMf temps-réel. Ensuite, dans une première étude, nous comparons les effets du NF-EEG-IRMF, du NF-EEG et du NF-IRMf. Enfin, dans une seconde étude nous proposons et évaluons deux types de feedbacks intégrés pour le NF-EEG-IRMf. / NF is the process of feeding back real-time information to an individual about his/her ongoing brain activity, so that he/she can train to self-regulate neural substrates of specific behavioral functions. NF has been extensively studied for brain rehabilitation of patients with psychiatric and neurological disorders. However its effective deployment in the clinical armamentarium is being held back by the lack of evidence about its efficacy. One of the possible reason for the debated efficacy of current approaches could be the inherent limitations of single imaging modalities. Indeed, most NF approaches rely on the use of a single modality, EEG and fMRI being the two most widely used. While EEG is inexpensive and benefits from a high temporal resolution (millisecond), its spatial resolution (centimeters) is limited by volume conduction of the head and the number of electrodes. Also source localization from EEG is inaccurate because of the ill-posed inverse problem. In a complementary way, fMRI gives access to the self-regulation of specific brain regions at high spatial resolution (millimeter) but has low temporal resolution (second). Combined EEG-fMRI has proven much valuable for the study of human brain function, however it has rarely been exploited for NF purpose. In the context of NF, combining EEG and fMRI enables cross-modal paradigm evaluation and validation. But more interestingly it opens up avenues for the development of new NF approaches that would mix both modalities, either at the calibration phase or to provide a bimodal NF signal. Combined EEG-fMRI poses numerous challenges with regard to basic physiology, study design, data quality, analysis/integration and interpretation. These challenges are even greater if EEG and fMRI are both to be used simultaneously for online NF computation, because of the real-time constraint and the difficulty to find a task design compatible with EEG and fMRI' diverging natures. The theoretical part of this PhD dissertation aims at identifying methodological aspects that differ between EEG-NF and fMRI-NF and at examining the motivations and strategies for combining EEG and fMRI for NF purpose. Among these combination strategies, we choose to focus on bimodal EEG-fMRI-NF as it seems to be one of the most promising approach and is mostly unexplored. The feasibility of this approach was recently demonstrated and opened an entire new field of investigation. First and foremost, we would like to address the following questions: what is the added value of bimodal NF over unimodal NF; are there any specific mechanisms involved when learning to control two NF signals simultaneously; how to integrate EEG and fMRI to derive a single feedback ? The experimental part of this PhD dissertation therefore focuses on the development and evaluation of methods for bimodal EEG-fMRI-NF. In order to conduct bimodal NF experiments, we start by building up a real-time EEG-fMRI platform. Then in a first study, we compare for the first time bimodal EEG-fMRI-NF with unimodal EEG-NF and fMRI-NF. Eventually, in a second study, we introduce and evaluate two integrated feedback strategies for EEG-fMRI-NF.

The proposal of this work was to determine the contribution of functional MR imaging techniques, i.e. secretin-enhanced MRCP (S-MRCP) and dynamic contrast-enhanced magnetic resonance (DCE-MR) imaging in the quantitative assessment of exocrine pancreatic function and perfusion.<p><p>The pancreas is both an exocrine and endocrine organ, though the exocrine tissue accounts for more than 90%. The exocrine pancreas is specialized in the synthesis and storage of digestive enzymes and in bicarbonate and water secretion in response respectively to various secretagogues (CCK, ach, GRP, VIP,…) and to secretin. <p>The arterial supply of the pancreas derives from branches of the celiac trunk and of the superior mesenteric artery. The microvascularity of the exocrine and the endocrine parts of the gland are anatomically and functionally separated, with differentially regulated blood perfusion. <p>Based on the knowledge of a close relationship between the activity of the gland and its blood supply, in normal conditions pancreatic perfusion responds to the functional state of the exocrine parenchyma: increased demands for exocrine secretions are associated with increased pancreatic blood flow. <p>The pancreatic gland can be involved at different degrees of severity in acute and chronic inflammatory processes due to various causes. In both processes microcirculatory changes occur and the pancreatic exocrine function can be impaired. Moreover, an exiguous microvascular component characterizes pancreatic ductal adenocarcinoma (PDA) related to a prominent stroma.<p><p><p>In the first section of this thesis, quantitative assessment of the pancreatic exocrine secretions was performed with S-MRCP in physiologic and non-physiologic conditions. The stimulating effect of secretin as well as the inhibitory effect of somatostatin on normal pancreas, both administered at different dose-regimens, were tested. The results of these investigations showed that quantitative S-MRCP is able to detect changes in pancreatic exocrine secretions correlated to the degree of stimulation or inhibition. <p>In pathologic settings, pancreatic exocrine secretions were assessed in chronic pancreatitis patients showing different degrees of severity, before and after endoscopic pancreatic duct drainage procedures (PDDP). In the group of patients presenting a reduced pancreatic exocrine reserve before treatment, quantitative S-MRCP showed a short-term improvement after PDDP. <p><p>In the second section, the feasibility and the reproducibility of DCE-MR imaging to quantify regional pancreatic perfusion was firstly investigated. DCE-MR imaging was performed in normal volunteers. Reference values for regional pancreatic perfusion were achieved with an intra-individual variability of 21%.<p>DCE-MR investigations were repeated during secretin stimulation and disclosed a significant increase of regional pancreatic perfusion in all individuals. <p>Secondly, DCE-MR imaging investigated benign and malignant focal pancreatic solid lesions and non tumoral tissue in patients undergoing pancreatic surgical resection. The purpose was to correlate DCE-MR quantitative parameters, (reflecting perfusion and/or permeability and the distribution volume fraction) with histologic features such as the degree of fibrosis and the microvascular density (MVD) in the corresponding tissues. A significant correlation was found between DCE-MR and histologic parameters: Ktrans was negatively correlated with the degree of fibrosis (high fibrosis was correlated with low perfusion), while the distribution volume fraction was positively correlated with the degree of fibrosis and with MVD (larger EES was correlated with high fibrosis and higher MVD). <p> / Doctorat en Sciences médicales / info:eu-repo/semantics/nonPublished

Cette thèse porte sur les processus de perception visuelle impliqués dans la reconnaissance des lettres. L’Étude 1 vise à déterminer la fenêtre temporelle à partir de laquelle les lettres sont discriminées. Nos résultats démontrent, en établissant un lien entre potentiels évoqués (PEs) et indices comportementaux, des effets apparaissant vers 100 ms et 220 ms au niveau d’électrodes occipitales droites, que nous lions à des traitements visuels, et un effet apparaissant aux alentours de 170 ms au niveau d’électrodes fronto-centrales, que nous lions à la possible récupération du nom des lettres. L’Étude 2 vise à déterminer jusqu’à quand, lors du processus de reconnaissance des lettres, trouve-t-on des influences de traitements de nature visuelle? Nous comparons les PEs de lettres nominalement similaires, mais visuellement dissimilaires (variant selon la casse), et nos résultats indiquent des influences visuelles toujours à l’œuvre aux alentours de 300 ms. L’Étude 3 vise à mettre en évidence les aires cérébrales impliquées dans la récupération du nom des lettres, révélées en imagerie par résonance magnétique fonctionnelle (IRMf), mais également les effets induits par cette récupération sur les PEs. Nous utilisons un paradigme d’apprentissage de symboles inconnus, durant lequel nous induisons une gradation dans la capacité des participants à pouvoir récupérer le nom des symboles. Cette gradation est alors utilisée comme marqueur de récupération du nom des symboles au niveau des PEs et des images fonctionnelles. Nous démontrons une covariation avec la gradation induite aux alentours de 200 ms sur les PEs, et au niveau du gyrus fusiforme et d’aires temporales gauches en IRMf. / The aim of this thesis is to investigate visual perception processes involved in recognizing letters. Study 1 aims at determining the time window during which letters are discriminated. Our results linking event-related potentials (ERPs) and behavioral measures, indicate effects occurring around 100 ms and 220 ms on right occipital electrodes as reflecting visual processing, while we assume that an effect occurring around 170 ms on fronto-central electrodes might be functionally linked to the retrieval of letter names.Study 2 aims at determining until when, along the process of letter recognition, influences of visual processing are observed. We compare ERPs associated with nominally similar but visually dissimilar letters (by varying the case of presentation), and our results indicate that visual influences are still active until around 300 ms. Study 3 aims at highlighting both the brain areas involved in the retrieval of letter names, as revealed by functional magnetic resonance imaging (fMRI), and the effects induced by this retrieval on ERPs. We use a learning paradigm of unknown visual symbols, in which we induce a gradation in the ability of participants to retrieve the name of these symbols. The gradation is used as a marker of the retrieval of the symbols’ names, both on ERPs and fMRI. We demonstrate that the induced gradation co-varies with ERPs at around 200 ms, and with fMRI signals on left fusiform gyrus and left temporal areas.

O objetivo deste trabalho é apresentar os métodos originais em Bioinformática desenvolvidos para a análise estatística na interpretação dos dados de duas técnicas baseadas em imagens: a técnica de microarranjos de DNA e a técnica de ressonância magnética funcional. O interesse principal é abordar essas técnicas experimentais quando enfrenta-se uma situação clara de amostras escassas, isto é, quando existem relativamente poucas observações experimentais do fenômeno estudado, sendo a análise individual/personalizada o representante extremo desta situação, que tem que ser resolvida. Para tanto, opta-se pelo uso da Inferência Bayesiana no contexto da Teoria da Decisão sob Incerteza, implementada computacionalmente sob o arcabouço dos Sistemas de Suporte à Decisão. Ambas as tecnologias estudadas produzem dados complexos, baseados na interpretação das diferenças entre imagens obtidas da resposta do sistema a um estímulo e da resposta numa situação controle. O resultado deste trabalho é o desenvolvimento de dois sistemas de suporte à decisão, chamados HTself e Dotslashen, para a análise de dados de microarranjos e ressonância magnética funcional, respectivamente; e de seus métodos matemáticos/computacionais subjacentes. Os sistemas desenvolvidos extraem conhecimento racional de bancos-de-dados normativos, através de modelos matemáticos específicos, contornando então o problema de amostras escassas. Finalmente, neste trabalho são descritas aplicações a problemas reais, para destacar a utilidade dos sistemas de suporte à decisão desenvolvidos nas áreas de Biologia Molecular e Neuroimagem Funcional. / The goal of this work is to present the novel Bioinformatics methods that were developed aiming the statistical analysis of two image-based techniques: DNA microarrays and functional magnetic resonance imaging. The main interest is to approach these experimental techniques in small sample size situations, i.e., when there are relatively few experimental observations of the phenomena of interest, for which the case of single subject/datum analysis is its most extreme. In order to approach these problems we chose to use Bayesian Inference in the context of the Decision Theory under Uncertainty, computationally implemented under the Decision Support Systems framework. Both technologies produce complex data, based on the interpretation of differences between images from the response to a given stimulus and the control situation. The result of this work is the development of two decision support systems, called HTself and Dotslashen, to analyze microarray and functional magnetic resonance imaging data, respectively; and the underling mathematical and computational methods. These systems use the rational knowledge from normative databases implemented in specific mathematical models, overcoming the problem of small sample size. Finally, in this work it is described applications to real problems in order to stress the utility for Molecular Biology and Functional Neuroimaging of the developed decision support systems.

Esta dissertação desenvolve e aplica métodos para caracterizar regiões cerebrais durante o estado de repouso. Utilizam-se grafos para representar a inter-dependência temporal de sinais de ressonância magnética funcional provenientes de regiões cerebrais distintas. Vértices representam regiões cerebrais e arestas representam a conectividade funcional. Buscando superar os problemas de visualização e interpretação desta forma de representação, elaboram-se métodos quantitativos para caracterizar padrões de conectividade entre regiões cerebrais. Para cada sujeito analisado: 1) Faz-se a redução da dimensionalidade espacial das imagens de ressonância magnética funcional respeitando os limites anatômicos das regiões cerebrais. 2) Estima-se a rede de conectividade funcional pela coerência direcionada entre pares de regiões distintas. 3) Constrói-se um grafo direcionado e pesado pela medida de conectividade. 4) Quantificam-se os vértices por índices e faz-se o registro destes valores no espaço comum MNI. 5) Avalia-se a consistência de cada índice pelo teste não paramétrico de Friedman seguido de análises de múltiplas comparações. A análise de 198 imagens de sujeitos sadios produziu resultados consistentes e biologicamente plausíveis. Em sua maioria, revelou regiões associadas a conceitos anatômicos de conectividade e integração cerebral. Embora de implementação simples, o método proporciona informações de natureza dinâmica sobre as relações entre diferentes regiões cerebrais e pode ser utilizado futuramente para estudar e entender desordens psiquiátricas/neurológicas. / This dissertation develops and applies methods to characterize brain regions during resting state. Graphs are used to represent functional MRI connectivity from different brain regions. Vertices represent brain regions and edges represent connectivity. To overcome the visualization and interpretation problems of this form of representation, we developed quantitative methods to characterize its patterns. Methods: For each subject: 1) The reduction of spatial dimensionality of functional magnetic resonance imaging is carried out taking into account the anatomic limits of the brain regions. 2) The network is estimated by directed coherence between pairs of separate regions. 3) A directed graph with weights on its edges is constructed using the later connectivity measure. 4) The vertices are quantified by indexes that are registered in the MNI common space. 5) The consistency of each index is evaluated by the nonparametric Friedman followed by Post-Hoc analysis. Results: The analysis of 198 images of healthy subjects produced consistent and biologically plausible results. They revealed anatomical regions involved in brain integration. Conclusion: The method provides information about the dynamic nature of the relationships between different brain regions and can be used in future clinical studies to understand psychiatric and neurological disorders.

Infinite-Dimensional Systems (IDSs) which have been made possible by recent advances in mathematical and computational tools can be used to model complex real phenomena. However, due to physical, economic, or stringent non-invasive constraints on real systems, the underlying characteristics for mathematical models in general (and IDSs in particular) are often missing or subject to uncertainty. Therefore, developing efficient estimation techniques to extract missing pieces of information from available measurements is essential. The human brain is an example of IDSs with severe constraints on information collection from controlled experiments and invasive sensors. Investigating the intriguing modeling potential of the brain is, in fact, the main motivation for this work. Here, we will characterize the hemodynamic behavior of the brain using functional magnetic resonance imaging data. In this regard, we propose efficient estimation methods for two classes of IDSs, namely Partial Differential Equations (PDEs) and Fractional Differential Equations (FDEs). This work is divided into two parts. The first part addresses the joint estimation problem of the state, parameters, and input for a coupled second-order hyperbolic PDE and an infinite-dimensional ordinary differential equation using sampled-in-space measurements. Two estimation techniques are proposed: a Kalman-based algorithm that relies on a reduced finite-dimensional model of the IDS, and an infinite-dimensional adaptive estimator whose convergence proof is based on the Lyapunov approach. We study and discuss the identifiability of the unknown variables for both cases. The second part contributes to the development of estimation methods for FDEs where major challenges arise in estimating fractional differentiation orders and non-smooth pointwise inputs. First, we propose a fractional high-order sliding mode observer to jointly estimate the pseudo-state and input of commensurate FDEs. Second, we propose a modulating function-based algorithm for the joint estimation of the parameters and fractional differentiation orders of non-commensurate FDEs. Sufficient conditions ensuring the local convergence of the proposed algorithm are provided. Subsequently, we extend the latter technique to estimate smooth and non-smooth pointwise inputs. The performance of the proposed estimation techniques is illustrated on a neurovascular-hemodynamic response model. However, the formulations are efficiently generic to be applied to a wide set of additional applications.

Working memory (WM) for facial identity and WM for facial expressions of emotions is important in everyday functioning and seems to have different neurobiological correlates. We investigated the level of neural activation in three regions of interest (ROI): the fusiform face area (FFA), dorsolateral prefrontal cortex (dlPFC), and amygdala; and how they are related to behavioral performance during an n-back task involving face stimuli with a complex background figure within an fMRI-paradigm. Participants performed three different 2-back tasks, one for facial expressions of emotions (EMO), one for the facial identity (ID), and one for a background figure presented behind the face (FIG). We hypothesized that the FFA would activate more in ID, the amygdala would activate more during EMO, and that the dlPFC would activate in all n-back tasks. An ROI analysis was done to extract mean activation values from the participants (N = 32) in the fusiform gyrus area 2 (FG2), the laterobasal amygdala (amygdala lb), and dlPFC in the different tasks. A one way repeated measures ANOVA revealed a similar activation in FG2 and amygdala lb in both ID and EMO. During the FIG task higher activation in FG2 was shown in comparison with ID and EMO, and lower activation in amygdala lb was shown in comparison to ID. dlPFC was activated in all tasks. Furthermore, there was a negative correlation between amygdala lb activation and reaction time in the FIG task, where an abstract figure was kept in WM and facial information was to be ignored. These results indicate that the activation in FG2 and amygdala lb might not differ between WM for facial identity and WM for facial expressions of emotions, which is unexpected in comparison to perception studies where a difference in these nodes has been reported for processing these two different types of information. This might suggest that the role of these neural nodes differ depending on WM load and task irrelevant features.