L’imagerie par résonance magnétique fonctionnelle (IRMf) est un outil de choix pour cartographier d’une manière non invasive l’activité du cortex, donnant ainsi un accès à l’organisation fonctionnelle cérébrale. Cette organisation des aires cérébrales en réseaux complexes reste encore un vaste sujet d’étude, autant dans le domaine de la recherche fondamentale, pour mieux comprendre le développement et le fonctionnement du cerveau, que dans le domaine clinique, à des fins diagnostiques par exemple. Les réseaux cérébraux dits de repos, chez un sujet donné, peuvent être observés lors d’études IRMf lorsqu’aucune tâche motrice ou cognitive n’est imposée au sujet imagé. La première partie de cette thèse a permis le développement d’une méthode automatique d’identification de ces réseaux. Réalisée à l’échelle du sujet, cette méthode permet de sélectionner tous les réseaux spécifiques au sujet ce qui s’avère nécessaire dans un cadre diagnostique où l’individu prime. Au delà de la détection et de l’identification de ces réseaux, l’étude de leurs modes d’interaction dans l’espace et dans le temps et plus généralement l’analyse de la dynamique de la connectivité fonctionnelle (DCF) fait l’objet d’un intérêt grandissant. Cette analyse nécessite le développement de méthodes innovantes de traitement du signal et de l’image qui, pour l’heure, sont encore de nature exploratoire. La deuxième partie de cette thèse présente donc de nouvelles approches pour caractériser la DCF en utilisant le cadre probabiliste de modèles de Markov cachés multidimensionnels. Les mécanismes conversationnels entre réseaux cérébraux peuvent ainsi être identifiés et caractérisés à l’échelle de la seconde. Deux applications, au niveau du sujet puis du groupe, ont permis de mettre en avant les modifications des propriétés dynamiques des interactions entre réseaux sous certaines conditions ou pathologies. / The functional magnetic resonance imaging (fMRI) is a perfect tool for mapping in a non- invasive manner the activity of the cortex, giving access to the functional organization of the brain. This organization of brain areas into complex networks remains a large topic of study, both from a fundamental research perspective, to better understand the development and function of the brain, and from a clinical perspective, for diagnostic purposes for instance. The resting-state networks in a given subject can be observed in fMRI studies where no motor or cognitive tasks are imposed to the subject. The first part of this thesis focused on the development of an automatic identification method of these networks. Performed at the subject level, this method selects all the resting-state networks proper to the subject. Beyond the detection and identification of these networks, the study of interactions between these networks in space and time, and more generally the analysis of the dynamic functional connectivity (DFC), is the subject of growing interest. This analysis requires the development of innovative methods of signal or image processing that, for now, are still exploratory. The second part of this thesis thus presents new approaches to characterize the DFC using the probabilistic framework of multidimensional hidden Markov models. Conversational mechanisms between brain networks can be identified and characterized at the resolution of the second. Two applications, first on a single subject then on a group, helped to highlight the changes of dynamic properties of interaction between networks under certain conditions or diseases.

Abstract The goal of this study was to explore preoperative evaluation of patients with intracranial tumours using magnetic resonance imaging (MRI) methods: oedema-attenuated inversion recovery (EDAIR) sequence in low-field MRI, and diffusion-weighted imaging (DWI) and resting-state functional MRI (fMRI) in high-field MRI. The aim was also to increase our knowledge about the effects of brain surgery on eloquent brain cortices using new MRI techniques. The total number of patients in these studies was 50 (24 women). Enhancement of the tumour in ten patients after intravenous administration of gadolinium-based contrast agent in low-field MRI was examined with a new sequence, EDAIR, and compared with more conventionally used partial saturation spin echo sequences. EDAIR may facilitate the perception of small enhancing lesions and is valuable in low-field imaging, where T1-based contrast is inferior to high-field imaging. DWI was performed on 25 patients in order to evaluate the potential of this imaging method to assist in differential diagnosis of intracranial tumours. It was shown that apparent diffusion coefficient values of the tumour and peritumoural oedema produced by DWI were different in benign and malignant tumours. Resting-state blood oxygen level-dependent (BOLD) fMRI was performed on eight patients and ten healthy volunteers to examine if functional sensorimotor areas in the brain could be determined without any task-related activations. It was shown that intracranial tumours do not appear to hamper visualization of the sensorimotor area in resting-state BOLD fMRI when independent component analysis is performed, and this method may be used in preoperative imaging when activation studies cannot be performed. Conventional BOLD fMRI with motor and auditory stimuli was used with seven patients as the effect of brain surgery was studied. The results suggest that resection of a tumour with preoperative oedema probably decreases pressure on the brain and makes the functional cortex transiently more easily detectable in BOLD fMRI. In conclusion, the MRI imaging methods used in this study can give valuable additional information about the tumour, specifically for preoperative imaging and planning for surgery.

Background: The aim of this thesis was to investigate the relationship of moral cognition and emotions to the pathophysiology of major depressive disorder (MDD). Patients with MDD may experience excessive guilt or self-blaming biases despite recovery from the depressed state. Since guilt is a moral emotion thought to motivate altruistic behaviours, it has been hypothesized that elevated self-blame in MDD may result in pathological increases to altruism in some patients. The relationship of self-blame to altruistic choices in individuals with remitted MDD (rMDD), however, has not been established. Guilt has been shown to activate the subgenual cingulate and adjacent septal region (SCSR) which is of known importance to the pathophysiology of MDD. Since MDD is thought to arise from network-level dysfunctions, and moral cognition and emotions are hypothesized to emerge from network-level binding, investigating resting-state SCSR functional connectivity in rMDD patients and healthy control (HC) participants could reveal networks of potential relevance both to MDD and to moral cognition and emotions. Chapter 2: We investigated whether melancholic rMDD patients could be distinguished from non-melancholic and HC groups on the basis of resting-state functional connectivity to an SCSR seed region. Lower SCSR-amygdala connectivity distinguished the melancholic rMDD group from non-melancholic and HC groups. Chapter 3: We investigated whether patients who remained resilient to recurring depressive episodes were distinguishable from recurring episode MDD and HC groups on the basis of resting-state connectivity to an SCSR seed region. Lower interhemispheric SCSR connectivity distinguished the resilient MDD patients from the recurring episode MDD and HC groups. Chapter 4: We measured explicit and implicit preferences for social options with and without altruistic motivations relative to selfish options in the rMDD and HC groups during emotion priming to modulate feelings of guilt. The rMDD patients explicitly preferred prosocial options (i.e., social options and altruism directed towards friends or colleagues) less than HC participants. Regardless of group, guilt priming increased explicit and implicit preferences for altruism towards strangers. Chapter 5: We investigated whether explicit and/or implicit preferences for prosocial options during guilt priming were correlated with resting-state connectivity to an SCSR seed region, and whether this relationship could distinguish the rMDD and HC groups. Across all participants, implicit prosocial choice preference negatively correlated with connectivity between the SCSR and right temporoparietal junction (TPJ). The relationship of SCSR-TPJ connectivity to implicit preferences for social options and for altruism towards friends and colleagues was weaker in the rMDD group compared to the HC group, particularly for implicit altruism. Conclusions: We identified resting-state SCSR networks associated with vulnerability to melancholia and with resilience to recurring depressive episodes. Patients with rMDD explicitly preferred options entailing social withdrawal, a symptom associated with MDD vulnerability. Irrespective of group, guilt motivated altruism towards strangers but not friends and colleagues. Implicit prosociality was negatively associated with connectivity in a social agency network, and the comparatively weak relationships between connectivity and implicit choice preferences in rMDD patients may reflect a vulnerability factor for MDD.

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.

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Human infants have been shown to have an innate capacity to acquire their mother tongue. In recent decades, the advent of the functional magnetic resonance imaging (fMRI) technique has made it feasible to explore the neural basis underlying language acquisition and processing in children, even in newborn infants (for reviews, see Kuhl & Rivera-Gaxiola, 2008; Kuhl, 2010) . Spontaneous low-frequency (< 0.1 Hz) fluctuations (LFFs) in the resting brain have been shown to be physiologically meaningful in the seminal study (Biswal et al., 1995) . Compared to task-based fMRI, resting-state fMRI (rs-fMRI) has some unique advantages in neuroimaging research, especially in obtaining data from pediatric and clinical populations. Moreover, it enables us to characterize the functional organization of the brain in a systematic manner in the absence of explicit tasks. Among brain systems, the language network has been well investigated by analyzing LFFs in the resting brain. This thesis attempts to investigate the functional connectivity within the language network in typically developing preschool children and the covariation of this connectivity with children’s language development by using the rs-fMRI technique. The first study (see Chapter 2.1; Xiao et al., 2016a) revealed connectivity differences in language-related regions between 5-year-olds and adults, and demonstrated distinct correlation patterns between functional connections within the language network and sentence comprehension performance in children. The results showed a left fronto-temporal connection for processing syntactically more complex sentences, suggesting that this connection is already in place at age 5 when it is needed for complex sentence comprehension, even though the whole functional network is still immature. In the second study (see Chapter 2.2; Xiao et al., 2016b), sentence comprehension performance and rs-fMRI data were obtained from a cohort of children at age 5 and a one-year follow-up. This study examined the changes in functional connectivity in the developing brain and their relation to the development of language abilities. The findings showed that the development of intrinsic functional connectivity in preschool children over the course of one year is clearly observable and individual differences in this development are related to the advancement in sentence comprehension ability with age. In summary, the present thesis provides new insights into the relationship between intrinsic functional connectivity in the brain and language processing, as well as between the changes in intrinsic functional connectivity and concurrent language development in preschool children. Moreover, it allows for a better understanding of the neural mechanisms underlying language processing and the advancement of language abilities in the developing brain.

Nous proposons un algorithme basé sur une approche orientée d'ensemble de système dynamique pour extraire une organisation grossière de l'espace d'état de cerveau sur la base des signaux de l'EEG. Nous l'utilisons pour comparer l'organisation de l'espace d'état des données simulées à grande échelle avec la dynamique cérébrale réelle au repos chez des sujets sains et pathologiques (SEP). / We propose an algorithme based on set oriented approach of dynamical system to extract a coarse grained organization of brain state space on the basis of EEG signals. We use it for comparing the organization of the state space of large scale simulation of brain dynamics with actual brain dynamics of resting activity in healthy and SEP subjects.

L'IRMf de repos qui repose sur l'étude des fluctuations du signal BOLD chez un sujet au repos, pourrait permettre d'explorer les mécanismes du handicap dans la Sclérose En Plaques (SEP). En utilisant l'IRMf de repos, ce travail a eu pour objectif de caractériser la réorganisation fonctionnelle des patients atteints de SEP et ses liens avec leur handicap.Nous avons d'abord réalisé une étude combinant IRMf de repos et d'activation au stade précoce de la SEP et montré l'existence d'une corrélation entre la plasticité fonctionnelle du système moteur des patients au repos et durant la tâche. Nous avons ensuite montré l'existence d'une augmentation diffuse du niveau de connectivité fonctionnelle des patients présentant une SEP débutante, corrélée à leurs performances. Dans la 3ème partie, nous avons objectivé l'existence d'un déclin dynamique de la topologie fonctionnelle corrélée à la progression du handicap grâce à une étude longitudinale utilisant la théorie des graphes. Enfin, nous avons démontré que le gain fonctionnel obtenu par la rééducation chez les patients SEP était corrélé à une augmentation de connectivité fonctionnelle du réseau cérébral par défaut et central exécutif et de densité de substance grise dans le cortex frontal.Nos travaux montrent l'existence d'une réorganisation cérébrale fonctionnelle complexe et dynamique dans la SEP qui pourrait correspondre à des phénomènes compensatoires, dont le déclin avec l'évolution de la maladie participe à la progression du handicap. Ils démontrent l'intérêt de l'IRMf de repos pour la compréhension des substrats anatomo-fonctionnels du handicap dans la SEP et comme potentiel instrument futur d'évaluation thérapeutique. / Resting-state fMRI (rs-fMRI) may provide important clue concerning disability in multiple sclerosis (MS) by exploring the spontaneous BOLD fluctuations at rest in the whole brain. The aim of this work is to depict the functional reorganization of resting-state networks in MS patients and to assess its potential relationships with disability.In the first part, we performed an fMRI protocol combining a rs-fMRI and task-associated fMRI during a motor task, in a group of early MS patients. This study evidenced a direct association between reorganization of connectivity at rest and during activation in the motor system of patients. In the second rs-fMRI study, we evidenced an increased of the global level of connectivity in most of the rs-networks, strongly associated with the level of disability of patients. In the third part, we evidenced in a 2-year longitudinal study using graph theoretical approach that MS patients exhibited a dynamical alteration of functional brain topology that significantly correlated with disability progression. In the last part, we evidenced that the transient clinical improvement following physical rehabilitation in MS patients is associated with reversible plasticity mechanisms located in the default mode network, the central executive network and in the left fronto-orbital cortex. These works evidence that MS patients exhibit a complex and dynamical functional reorganization of rs-networks, significantly associated with disability progression. This PhD thesis confirms that rs-fMRI is a relevant biomarker of pathophysiology leading to disability in MS and represents a promising tool for therapeutic assessment of MS patients in the future.

A presença de redes cerebrais funcionais ativadas durante o repouso é bem conhecida e verificada por diferentes técnicas de imagens, como as Imagens por Ressonância Magnética funcionais (IRMf) baseadas no contraste dependente do nível de oxigenação do sangue (BOLD, Blood Oxygenation Level Dependent). Entretanto, apesar de ser atualmente o método não invasivo convencional para tais estudos, o contraste BOLD é sensível a diferentes parâmetros hemodinâmicos (fluxo sanguíneo cerebral, CBF; volume sanguíneo cerebral e extração de oxigênio), cuja relação não é completamente conhecida em diversas patologias. Por outro lado, o método de Marcação dos Spins Arteriais (ASL) é uma técnica de IRM não invasiva que fornece mapas quantitativos de CBF e pode ser usada para avaliar as redes de repouso. Portanto, o objetivo do presente estudo foi investigar a viabilidade de usar sequências de ASL (pulsada e pseudocontínua), disponíveis para o uso na rotina clínica, para o estudo da conectividade funcional do cérebro em estado de repouso. Imagens de ASL e BOLD, de 23 indivíduos jovens e saudáveis, foram adquiridas em um equipamento de 3T. Após o pré-processamento usual das imagens e cálculos dos mapas de perfusão, CBF e pseudo-BOLD (pBOLD), a partir das imagens de ASL, as redes cerebrais de repouso foram obtidas pela Análise de Componentes Independentes (ICA) e pelo método baseado em semente. Utilizando ICA, a análise em grupo conjunta de pBOLD e BOLD identificou cinco redes: rede de modo padrão (DMN), visual, auditiva, saliência e motora. Quando analisados separadamente, os dados de pBOLD mostraram apenas as redes DMN e visual, enquanto os dados de BOLD mostraram também as redes auditiva, saliência, motora, atentiva e frontoparietais direita e esquerda. Para ambas as análises, comparações entre as redes de pBOLD e BOLD apresentaram similaridades de moderadas a altas. Entretanto, nenhuma rede foi observada utilizando os dados de perfusão e CBF. Já as análises baseadas em sementes mostraram correlações significativas, para as séries temporais de pBOLD e CBF, entre regiões que constituem algumas redes de repouso conhecidas (DMN, visual, sensorial-motora, atentiva e frontoparietal). Os valores obtidos para a força das conectividades nas redes de pBOLD e CBF se correlacionaram com aqueles obtidos nas redes de BOLD. As diferenças no desempenho de ASL e BOLD devem-se a uma combinação de fatores, como relação sinal ruído e resolução temporal. Além disso, a natureza dos sinais não é a mesma. O sinal BOLD é influenciado por diferentes parâmetros fisiológicos e é proveniente principalmente de grandes veias; enquanto o sinal de ASL é proveniente da rede de capilares, fornecendo especificidade espacial mais alta para a atividade neuronal, além de permitir a quantificação do CBF, que está relacionado mais diretamente ao metabolismo cerebral. Portanto, o presente estudo mostrou ser possível investigar a conectividade funcional do cérebro no estado de repouso com uma sequência comercial, apesar das limitações técnicas da ASL. Além disso, as séries temporais de CBF e BOLD refletem diferentes aspectos do cérebro em repouso, fornecendo informações complementares dos seus processos fisiológicos / The presence of functional brain networks activated during resting state is well known and has been verified by different imaging techniques, such as the functional Magnetic Resonance Imaging (fMRI) based on the Blood Oxygenation Level-Dependent (BOLD) contrast. Although BOLD-fMRI is currently the conventional non invasive method for such studies, BOLD contrast is sensitive to different hemodynamic parameters (Cerebral Blood Flow, CBF; cerebral blood volume and oxygen extraction fraction), whose relationship is not fully understood in several pathologies. In contrast, the Arterial Spin Labeling (ASL) MRI technique is a non invasive tool for CBF quantification and can be used to investigate resting-state networks. Therefore, the goal of the present study was to investigate the feasibility of using ASL sequences (pulsed and pseudocontinuous), available for clinical routine use, for the study of functional connectivity of the brain at rest. ASL and BOLD images of 23 healthy young subjects were acquired in a 3T machine. After the usual image pre-processing and quantification of perfusion, CBF and pseudo-BOLD (pBOLD) maps, from ASL images, resting-state brain networks were obtained by Independent Component Analysis (ICA) and a seed-based method. Five networks were identified in a joint analysis of pBOLD and BOLD: Default Mode Network (DMN), visual, auditory, salience, and motor. When analyzed separately, pBOLD showed only the DMN and visual networks, while BOLD also showed auditory, salience, motor, attentive, right and left frontoparietal networks. For both analyses, comparisons between pBOLD and BOLD networks showed from moderate to high similarities. However, no network was obtained from perfusion and CBF time series. Seed-based analysis showed significant correlations, for pBOLD e CBF time series, between regions that integrate some known networks (DMN, visual, sensorial-motor, attentive and frontoparietal). Functional connectivity strength obtained from pBOLD and CBF networks correlated with the ones from BOLD data. Differences in performance with ASL and BOLD are due to a combination of factors, such as SNR and temporal resolution. Moreover, the nature of the signals is not the same. BOLD signal is influenced by different physiologic parameters and comes mainly from large veins; while ASL signal comes from small capillaries, providing higher spatial specificity regarding neural activity, in addition to allow the quantification of CBF, which is closer related to the cerebral metabolism. In conclusion, the present study showed the feasibility of investigating functional connectivity of the brain at rest using a commercial ASL sequence, even with its technical limitations. Moreover, CBF and BOLD time series reflect different aspects of the resting-state brain and provide complementary information on its physiological processes