Episodic memory is a key feature in learning. One must remember past events to act upon a present situation. Episodic memory has been reported to be impaired in individuals with schizophrenia. In order to have an intact episodic memory the contextual features (context) must be bound to the content of the event; this mechanism is referred to as contextual binding. It is proposed that binding errors during the encoding process are responsible for episodic memory impairments in schizophrenia. Since the hippocampal formation is considered to be the central element for contextual binding, it is hypothesized that the synaptic disorganization described in this condition results in such a deficit. Moreover, the hippocampus mediates and influences other cognitive processes such as learning and executive functioning. Hence, a contextual binding deficit can have important consequences on cognition, behaviour and emotions. The object of this dissertation was to investigate the neurofunctioning, neuroanatomy and neurofunctional connectivity of the hippocampus while performing a task that utilized contextual binding mechanisms. Since spatial relational processing is part of contextual binding and is rooted in the hippocampal regions, visuospatial navigation, more precisely a wayfinding task, was used as a probe to activate the hippocampus and its associated regions in a group of patients with schizophrenia and matched healthy controls. The following dissertation presents three original research papers contributing to our understanding of the contextual binding and hippocampal deficits in schizophrenia. The first paper investigates the neurofunctioning of the hippocampus with a wayfinding task. The second paper investigates the hippocampal structural abnormality in schizophrenia and how it relates to performance during the wayfinding task. The third paper explores effective connectivity of the hippocampus with other brain regions involved in navigation in schizophrenia with a particular interest in the prefrontal cortex. These three studies demonstrate significant neurofunctional, neuroanatomical, and neurofunctional connectivity deficits in the hippocampus of the patients with schizophrenia compared to a healthy control population. Results of all three papers are further discussed in terms of research and clinical implications.

Near infrared spectroscopy (NIRS) is an emerging non-invasive optical neuro imaging technique that monitors the hemodynamic response to brain activation with ms-scale temporal resolution and sub-cm spatial resolution. The overall goal of my dissertation was to develop and apply NIRS towards investigation of neurological response to language, joint attention and planning and execution of motor skills in healthy adults. Language studies were performed to investigate the hemodynamic response, synchrony and dominance feature of the frontal and fronto-temporal cortex of healthy adults in response to language reception and expression. The mathematical model developed based on granger causality explicated the directional flow of information during the processing of language stimuli by the fronto-temporal cortex. Joint attention and planning/ execution of motor skill studies were performed to investigate the hemodynamic response, synchrony and dominance feature of the frontal cortex of healthy adults and in children (5-8 years old) with autism (for joint attention studies) and individuals with cerebral palsy (for planning/execution of motor skills studies). The joint attention studies on healthy adults showed differences in activation as well as intensity and phase dependent connectivity in the frontal cortex during joint attention in comparison to rest. The joint attention studies on typically developing children showed differences in frontal cortical activation in comparison to that in children with autism. The planning and execution of motor skills studies on healthy adults and individuals with cerebral palsy (CP) showed difference in the frontal cortical dominance, that is, bilateral and ipsilateral dominance, respectively. The planning and execution of motor skills studies also demonstrated the plastic and learning behavior of brain wherein correlation was found between the relative change in total hemoglobin in the frontal cortex and the kinematics of the activity performed by the participants. Thus, during my dissertation the NIRS neuroimaging technique was successfully implemented to investigate the neurological response of language, joint attention and planning and execution of motor skills in healthy adults as well as preliminarily on children with autism and individuals with cerebral palsy. These NIRS studies have long-term potential for the design of early stage interventions in children with autism and customized rehabilitation in individuals with cerebral palsy.

Master’s thesis is aimed at familiarization with the principles of measurement and data processing functional magnetic resonance, focusing on the analysis of effective connectivity using dynamic causal modelling (DCM). The practical part includes three main thematic areas relating to the description of the processing and evaluation of measured or simulated data. First, there is on sample dataset described the neuroscientific SPM toolbox to analyze measured data. Then follows introduction of the proposed approach with which is investigated the behavior of the model estimation neural interactions with respect to the change of input parameters. This phenomenon is also simulated and on base of achieved results is recommended optimal approach to analyzing effective connectivity using dynamic causal modeling for the group of subjects. The last circuit in the practical part is assessment of shift the coordinates of brain areas on dynamic causal modelling results for the group of subjects from the data obtained from real measurements. Obtained results from simulated data and the results obtained from measured data are evaluated and discussed in the final part.

Muitas operações cognitivas requerem velocidade de processamento de informação (VPI) suficiente para serem executadas dentro do prazo permitido, sendo que VPI retardada geralmente está subjacente a déficits atencionais. A desaceleração no tempo de resposta é particularmente evidente em pacientes com traumatismo crânio-encefálico, doença de Parkinson, depressão, demência e esclerose múltipla (EM). A importância de compreender os déficits de VPI e o desenvolvimento de programas efetivos de reabilitação é, portanto, crítico. Devido à sua alta validade preditiva e à sua fácil administração, o Symbol Digit Modalities Test (SDMT) é um dos testes clínicos mais amplamente utilizados para a avaliação cognitiva de pacientes com menor VPI. No entanto, além de avaliar a presença e gravidade de seus déficits, é interessante determinar as regiões cerebrais responsáveis por essa função e sua integração. Devido à sua não invasividade e ao seu bom nível de confiabilidade, a técnica de Imagem de Ressonância Magnética Funcional Dependente do Nível de Oxigenação no Sangue (BOLD-fMRI) é a ferramenta mais apropriada para esse fim. Logo, o objetivo do presente estudo foi o mapeamento funcional cerebral de VPI durante o desempenho de uma tarefa (SDMT) adaptada para o ambiente da ressonância em um grupo de voluntários saudáveis jovens. 16 controles saudáveis destros foram recrutados e submetidos à avaliação cognitiva com a versão oral do SDMT antes da aquisição de imagens. IRM foi adquirida em um sistema de 3T (Philips Achieva). Imagens funcionais (BOLD) foram adquiridas com uma sequência EPI. O experimento consistiu de seis blocos de 30 s de controle intercalados com cinco blocos de 30 segundos de tarefa (SDMT). Durante os blocos de tarefa, um símbolo foi apresentado a cada 2 segundos e ao participante foi requerido que associasse o número correspondente ao símbolo apresentado baseando-se em uma chave de resposta. Durante os blocos de controle, um número foi apresentado a cada 2 segundos e ao participante foi requerido que lesse silenciosamente o número em questão. Mapas paramétricos estatísticos foram obtidos para estudo de localização funcional utilizando o Modelo Linear Geral com um regressor boxcar convoluído com uma função de resposta hemodinâmica canônica (p-FDR < 0,01). Foi realizada a correlação bivariada entre as séries temporais médias das regiões associadas à tarefa para estudo de integração funcional (p-FDR < 0.0001). As informações de localização e integração funcionais foram inseridas em analise de conectividade efetiva. Ativações foram observadas na rede frontoparietal e no córtex occipital para análises individual e em grupo. Análise de conectividade efetiva para a arquitetura do sistema revelou o declive em posição serial com o giro lingual, o cúneo e duas regiões paralelas (pré-cúneo e lóbulo parietal superior), a partir do qual a informação converge para o giro frontal inferior e se bifurca para os giros frontais médios esquerdo e direito. Um modelo de rede envolvendo áreas relacionadas à VPI foi obtido e pode servir como referência para investigações futuras deste processo cognitivo em grupos clínicos, combinadas com estudos de neuroplasticidade cerebral. / Many cognitive operations require sufficient information processing speed (IPS) to be executed within the allowed time frame, with delayed IPS often underlining attentional deficits. The deceleration in response time is particularly evident in patients with traumatic brain injury, Parkinson\'s disease, depression, dementia and multiple sclerosis (MS). The importance of understanding IPS deficits and developing effective rehabilitation programs is therefore critical. Because of its high predictive validity and easy administration, the Symbol Digit Modalities Test (SDMT) is one of the most widely used clinical tests for the cognitive assessment of patients with lower IPS. However, in addition to evaluating the presence and severity of its deficits, it is interesting to determine the brain regions responsible for this function and its integration. Because of its non-invasiveness and its good level of reliability, the BOLD-fMRI technique is the most appropriate tool for this purpose. Therefore, the aim of the present study was the functional brain function mapping of IPS during the performance of a task (SDMT) adapted to the resonance environment in a group of healthy young volunteers. 16 healthy right controls were recruited and submitted to cognitive assessment with the oral version of SDMT prior to image acquisition. MRI was acquired in a 3T system (Philips Achieva). Functional images (BOLD) were acquired with an EPI sequence. The experiment consisted of six blocks of 30 s of control intercalated with five blocks of 30 seconds of task (SDMT). During the task blocks, a symbol was displayed every 2 seconds and the participant was required to associate the number corresponding to the displayed symbol based on a response key. During the control blocks, a number was displayed every 2 seconds and the participant was required to silently read the number in question. Statistical parametric maps were obtained for functional localization study using the General Linear Model with a boxcar regressor convolved with a canonical hemodynamic response function (p-FDR <0.01). The bivariate correlation between the mean time series of the regions associated with the task for functional integration study (p-FDR <0.0001) was performed. The functional location and integration information was inserted into effective connectivity analysis. Activations were observed in the frontoparietal network and in the occipital cortex for individual and group analyzes. Effective connectivity analysis for the system architecture revealed the declive in serial position with the lingual gyrus, the cuneus and two parallel regions (precuneus and superior parietal lobule), from which the information converges to the inferior frontal gyrus and bifurcates to the left and right middle turns. A network model involving areas related to IPS has been obtained and may serve as a reference for future investigations of this cognitive process in clinical groups, combined with studies of cerebral neuroplasticity.

No description available.

Muitas operações cognitivas requerem velocidade de processamento de informação (VPI) suficiente para serem executadas dentro do prazo permitido, sendo que VPI retardada geralmente está subjacente a déficits atencionais. A desaceleração no tempo de resposta é particularmente evidente em pacientes com traumatismo crânio-encefálico, doença de Parkinson, depressão, demência e esclerose múltipla (EM). A importância de compreender os déficits de VPI e o desenvolvimento de programas efetivos de reabilitação é, portanto, crítico. Devido à sua alta validade preditiva e à sua fácil administração, o Symbol Digit Modalities Test (SDMT) é um dos testes clínicos mais amplamente utilizados para a avaliação cognitiva de pacientes com menor VPI. No entanto, além de avaliar a presença e gravidade de seus déficits, é interessante determinar as regiões cerebrais responsáveis por essa função e sua integração. Devido à sua não invasividade e ao seu bom nível de confiabilidade, a técnica de Imagem de Ressonância Magnética Funcional Dependente do Nível de Oxigenação no Sangue (BOLD-fMRI) é a ferramenta mais apropriada para esse fim. Logo, o objetivo do presente estudo foi o mapeamento funcional cerebral de VPI durante o desempenho de uma tarefa (SDMT) adaptada para o ambiente da ressonância em um grupo de voluntários saudáveis jovens. 16 controles saudáveis destros foram recrutados e submetidos à avaliação cognitiva com a versão oral do SDMT antes da aquisição de imagens. IRM foi adquirida em um sistema de 3T (Philips Achieva). Imagens funcionais (BOLD) foram adquiridas com uma sequência EPI. O experimento consistiu de seis blocos de 30 s de controle intercalados com cinco blocos de 30 segundos de tarefa (SDMT). Durante os blocos de tarefa, um símbolo foi apresentado a cada 2 segundos e ao participante foi requerido que associasse o número correspondente ao símbolo apresentado baseando-se em uma chave de resposta. Durante os blocos de controle, um número foi apresentado a cada 2 segundos e ao participante foi requerido que lesse silenciosamente o número em questão. Mapas paramétricos estatísticos foram obtidos para estudo de localização funcional utilizando o Modelo Linear Geral com um regressor boxcar convoluído com uma função de resposta hemodinâmica canônica (p-FDR < 0,01). Foi realizada a correlação bivariada entre as séries temporais médias das regiões associadas à tarefa para estudo de integração funcional (p-FDR < 0.0001). As informações de localização e integração funcionais foram inseridas em analise de conectividade efetiva. Ativações foram observadas na rede frontoparietal e no córtex occipital para análises individual e em grupo. Análise de conectividade efetiva para a arquitetura do sistema revelou o declive em posição serial com o giro lingual, o cúneo e duas regiões paralelas (pré-cúneo e lóbulo parietal superior), a partir do qual a informação converge para o giro frontal inferior e se bifurca para os giros frontais médios esquerdo e direito. Um modelo de rede envolvendo áreas relacionadas à VPI foi obtido e pode servir como referência para investigações futuras deste processo cognitivo em grupos clínicos, combinadas com estudos de neuroplasticidade cerebral. / Many cognitive operations require sufficient information processing speed (IPS) to be executed within the allowed time frame, with delayed IPS often underlining attentional deficits. The deceleration in response time is particularly evident in patients with traumatic brain injury, Parkinson\'s disease, depression, dementia and multiple sclerosis (MS). The importance of understanding IPS deficits and developing effective rehabilitation programs is therefore critical. Because of its high predictive validity and easy administration, the Symbol Digit Modalities Test (SDMT) is one of the most widely used clinical tests for the cognitive assessment of patients with lower IPS. However, in addition to evaluating the presence and severity of its deficits, it is interesting to determine the brain regions responsible for this function and its integration. Because of its non-invasiveness and its good level of reliability, the BOLD-fMRI technique is the most appropriate tool for this purpose. Therefore, the aim of the present study was the functional brain function mapping of IPS during the performance of a task (SDMT) adapted to the resonance environment in a group of healthy young volunteers. 16 healthy right controls were recruited and submitted to cognitive assessment with the oral version of SDMT prior to image acquisition. MRI was acquired in a 3T system (Philips Achieva). Functional images (BOLD) were acquired with an EPI sequence. The experiment consisted of six blocks of 30 s of control intercalated with five blocks of 30 seconds of task (SDMT). During the task blocks, a symbol was displayed every 2 seconds and the participant was required to associate the number corresponding to the displayed symbol based on a response key. During the control blocks, a number was displayed every 2 seconds and the participant was required to silently read the number in question. Statistical parametric maps were obtained for functional localization study using the General Linear Model with a boxcar regressor convolved with a canonical hemodynamic response function (p-FDR <0.01). The bivariate correlation between the mean time series of the regions associated with the task for functional integration study (p-FDR <0.0001) was performed. The functional location and integration information was inserted into effective connectivity analysis. Activations were observed in the frontoparietal network and in the occipital cortex for individual and group analyzes. Effective connectivity analysis for the system architecture revealed the declive in serial position with the lingual gyrus, the cuneus and two parallel regions (precuneus and superior parietal lobule), from which the information converges to the inferior frontal gyrus and bifurcates to the left and right middle turns. A network model involving areas related to IPS has been obtained and may serve as a reference for future investigations of this cognitive process in clinical groups, combined with studies of cerebral neuroplasticity.

Les travaux présentés dans cette thèse s'inscrivent dans la problématique de la connectivité cérébrale, connectivité tripartite puisqu'elle sous-tend les notions de connectivité structurelle, fonctionnelle et effective. Ces trois types de connectivité que l'on peut considérer à différentes échelles d'espace et de temps sont bien évidemment liés et leur analyse conjointe permet de mieux comprendre comment structures et fonctions cérébrales se contraignent mutuellement. Notre recherche relève plus particulièrement de la connectivité effective qui permet de définir des graphes de connectivité qui renseignent sur les liens causaux, directs ou indirects, unilatéraux ou bilatéraux via des chemins de propagation, représentés par des arcs, entre les nœuds, ces derniers correspondant aux régions cérébrales à l'échelle macroscopique. Identifier les interactions entre les aires cérébrales impliquées dans la génération et la propagation des crises épileptiques à partir d'enregistrements intracérébraux est un enjeu majeur dans la phase pré-chirurgicale et l'objectif principal de notre travail. L'exploration de la connectivité effective suit généralement deux approches, soit une approche basée sur les modèles, soit une approche conduite par les données comme nous l'envisageons dans le cadre de cette thèse où les outils développés relèvent de la théorie de l'information et plus spécifiquement de l'entropie de transfert, la question phare que nous adressons étant celle de la précision des estimateurs de cette grandeur dans le cas des méthodes développées basées sur les plus proches voisins. Les approches que nous proposons qui réduisent le biais au regard d'estimateurs issus de la littérature sont évaluées et comparées sur des signaux simulés de type bruits blancs, processus vectoriels autorégressifs linéaires et non linéaires, ainsi que sur des modèles physiologiques réalistes avant d'être appliquées sur des signaux électroencéphalographiques de profondeur enregistrés sur un patient épileptique et comparées à une approche assez classique basée sur la fonction de transfert dirigée. En simulation, dans les situations présentant des non-linéarités, les résultats obtenus permettent d'apprécier la réduction du biais d'estimation pour des variances comparables vis-à-vis des techniques connues. Si les informations recueillies sur les données réelles sont plus difficiles à analyser, elles montrent certaines cohérences entre les méthodes même si les résultats préliminaires obtenus s'avèrent davantage en accord avec les conclusions des experts cliniciens en appliquant la fonction de transfert dirigée. / The work presented in this thesis deals with brain connectivity, including structural connectivity, functional connectivity and effective connectivity. These three types of connectivities are obviously linked, and their joint analysis can give us a better understanding on how brain structures and functions constrain each other. Our research particularly focuses on effective connectivity that defines connectivity graphs with information on causal links that may be direct or indirect, unidirectional or bidirectional. The main purpose of our work is to identify interactions between different brain areas from intracerebral recordings during the generation and propagation of seizure onsets, a major issue in the pre-surgical phase of epilepsy surgery treatment. Exploring effective connectivity generally follows two kinds of approaches, model-based techniques and data-driven ones. In this work, we address the question of improving the estimation of information-theoretic quantities, mainly mutual information and transfer entropy, based on k-Nearest Neighbors techniques. The proposed approaches we developed are first evaluated and compared with existing estimators on simulated signals including white noise processes, linear and nonlinear vectorial autoregressive processes, as well as realistic physiology-based models. Some of them are then applied on intracerebral electroencephalographic signals recorded on an epileptic patient, and compared with the well-known directed transfer function. The experimental results show that the proposed techniques improve the estimation of information-theoretic quantities for simulated signals, while the analysis is more difficult in real situations. Globally, the different estimators appear coherent and in accordance with the ground truth given by the clinical experts, the directed transfer function leading to interesting performance.

Functional magnetic resonance imaging (fMRI) is recent important method, used in neuroimaging. The aim of this thesis is to develop software tool for comparison of two methods for functional and effective connectivity estimation. In this thesis are described the basics of magnetic resonance imaging, fMRI, basic terms of fMRI experiments and generally are described methods of functional and effective connectivity. Then are more detailed mentioned methods of dynamic causal modeling (DCM), Granger causal modeling (GCM) and independent component analysis (ICA). Practical implementation of DCM in toolbox SMP and ICA in toolbox GIFT is also mentioned. In purpose to describe behavior of DCM and GCM in dependence on several parameters are performed Monte Carlo simulations. Then the concept and realization of software tool for simulating connectivity and comparison of DCM and GCM are described. Finally results of DCM and GCM comparison and results of Monte Carlo simulations are discussed.

Zobrazení funkční magnetickou rezonancí (fMRI) využívající "blood-oxygen-level-dependent" efekt jako indikátor lokální aktivity je velmi užitečnou technikou k identifikaci oblastí mozku, které jsou aktivní během percepce, kognice, akce, ale také během klidového stavu. V poslední době také roste zájem o studium konektivity mezi těmito oblastmi, zejména v klidovém stavu. Tato práce předkládá nový a originální přístup k problému nepřímého vztahu mezi měřenou hemodynamickou odezvou a její příčinou, tj. neuronálním signálem. Zmíněný nepřímý vztah komplikuje odhad efektivní konektivity (kauzálního ovlivnění) mezi různými oblastmi mozku z dat fMRI. Novost prezentovaného přístupu spočívá v použití (zobecněné nelineární) techniky slepé dekonvoluce, což dovoluje odhad endogenních neuronálních signálů (tj. vstupů systému) z naměřených hemodynamických odezev (tj. výstupů systému). To znamená, že metoda umožňuje "data-driven" hodnocení efektivní konektivity na neuronální úrovni i v případě, že jsou měřeny pouze zašumělé hemodynamické odezvy. Řešení tohoto obtížného dekonvolučního (inverzního) problému je dosaženo za použití techniky nelineárního rekurzivního Bayesovského odhadu, který poskytuje společný odhad neznámých stavů a parametrů modelu. Práce je rozdělena do tří hlavních částí. První část navrhuje metodu k řešení výše uvedeného problému. Metoda využívá odmocninové formy nelineárního kubaturního Kalmanova filtru a kubaturního Rauch-Tung-Striebelova vyhlazovače, ovšem rozšířených pro účely řešení tzv. problému společného odhadu, který je definován jako simultánní odhad stavů a parametrů sekvenčním přístupem. Metoda je navržena především pro spojitě-diskrétní systémy a dosahuje přesného a stabilního řešení diskretizace modelu kombinací nelineárního (kubaturního) filtru s metodou lokální linearizace. Tato inverzní metoda je navíc doplněna adaptivním odhadem statistiky šumu měření a šumů procesu (tj. šumů neznámých stavů a parametrů). První část práce je zaměřena na inverzi modelu pouze jednoho časového průběhu; tj. na odhad neuronální aktivity z fMRI signálu. Druhá část generalizuje navrhovaný přístup a aplikuje jej na více časových průběhů za účelem umožnění odhadu parametrů propojení neuronálního modelu interakce; tj. odhadu efektivní konektivity. Tato metoda představuje inovační stochastické pojetí dynamického kauzálního modelování, což ji činí odlišnou od dříve představených přístupů. Druhá část se rovněž zabývá metodami Bayesovského výběru modelu a navrhuje techniku pro detekci irelevantních parametrů propojení za účelem dosažení zlepšeného odhadu parametrů. Konečně třetí část se věnuje ověření navrhovaného přístupu s využitím jak simulovaných tak empirických fMRI dat, a je významných důkazem o velmi uspokojivých výsledcích navrhovaného přístupu.