Resting state functional magnetic resonance imaging (fMRI) is currently at the forefront of research on cognition and the brain’s large-scale organization. Patterns of hemodynamic activity that it records have been strongly linked to certain behaviors and cognitive pathologies. These signals are widely assumed to reflect local neuronal activity but our understanding of the exact relationship between them remains incomplete. Researchers often address this using multimodal approaches, pairing fMRI signals with known measures of neuronal activity such as electroencephalography (EEG). It has long been thought that infraslow (< 0.1 Hz) fMRI signals, which have become so important to the study of brain function, might have a direct electrophysiological counterpart. If true, EEG could be positioned as a low-cost alternative to fMRI when fMRI is impractical and therefore could also become much more influential in the study of functional brain networks. Previous works have produced indirect support for the fMRI-EEG relationship, but until recently the hypothesized link between them had not been tested in resting humans. The objective of this study was to investigate and characterize their relationship by simultaneously recording infraslow fMRI and EEG signals in resting human adults. We present evidence strongly supporting their link by demonstrating significant stationary and dynamic correlations between the two signal types. Moreover, functional brain networks appear to be a fundamental unit of this coupling. We conclude that infraslow electrophysiology is likely playing an important role in the dynamic configuration of the resting state brain networks that are well-known to fMRI research. Our results provide new insights into the neuronal underpinnings of hemodynamic activity and a foundational point on which the use of infraslow EEG in functional connectivity studies can be based.

Le but de cette thèse est d'étudier les corrélats comportementaux et neuronaux du transfert inter-linguistique (TIL) dans l'apprentissage d’une langue seconde (L2). Compte tenu de nos connaissances sur l'influence de la distance linguistique sur le TIL (Paradis, 1987, 2004; Odlin, 1989, 2004, 2005; Gollan, 2005; Ringbom, 2007), nous avons examiné l'effet de facilitation de la similarité phonologique à l’aide de la résonance magnétique fonctionnelle entre des langues linguistiquement proches (espagnol-français) et des langues linguistiquement éloignées (persan-français). L'étude I rapporte les résultats obtenus pour des langues linguistiquement proches (espagnol-français), alors que l'étude II porte sur des langues linguistiquement éloignées (persan-français). Puis, les changements de connectivité fonctionnelle dans le réseau langagier (Price, 2010) et dans le réseau de contrôle supplémentaire impliqué dans le traitement d’une langue seconde (Abutalebi & Green, 2007) lors de l’apprentissage d’une langue linguistiquement éloignée (persan-français) sont rapportés dans l’étude III. Les résultats des analyses d’IRMF suivant le modèle linéaire général chez les bilingues de langues linguistiquement proches (français-espagnol) montrent que le traitement des mots phonologiquement similaires dans les deux langues (cognates et clangs) compte sur un réseau neuronal partagé par la langue maternelle (L1) et la L2, tandis que le traitement des mots phonologiquement éloignés (non-clang-non-cognates) active des structures impliquées dans le traitement de la mémoire de travail et d'attention. Toutefois, chez les personnes bilingues de L1-L2 linguistiquement éloignées (français-persan), même les mots phonologiquement similaires à travers les langues (cognates et clangs) activent des régions connues pour être impliquées dans l'attention et le contrôle cognitif. Par ailleurs, les mots phonologiquement éloignés (non-clang-non-cognates) activent des régions usuellement associées à la mémoire de travail et aux fonctions exécutives. Ainsi, le facteur de distance inter-linguistique entre L1 et L2 module la charge cognitive sur la base du degré de similarité phonologiques entres les items en L1 et L2. Des structures soutenant les processus impliqués dans le traitement exécutif sont recrutées afin de compenser pour des demandes cognitives. Lorsque la compétence linguistique en L2 augmente et que les tâches linguistiques exigent ainsi moins d’effort, la demande pour les ressources cognitives diminue. Tel que déjà rapporté (Majerus, et al, 2008; Prat, et al, 2007; Veroude, et al, 2010; Dodel, et al, 2005; Coynel, et al ., 2009), les résultats des analyses de connectivité fonctionnelle montrent qu’après l’entraînement la valeur d'intégration (connectivité fonctionnelle) diminue puisqu’il y a moins de circulation du flux d'information. Les résultats de cette recherche contribuent à une meilleure compréhension des aspects neurocognitifs et de plasticité cérébrale du TIL ainsi que l'impact de la distance linguistique dans l'apprentissage des langues. Ces résultats ont des implications dans les stratégies d'apprentissage d’une L2, les méthodes d’enseignement d’une L2 ainsi que le développement d'approches thérapeutiques chez des patients bilingues qui souffrent de troubles langagiers. / The purpose of this thesis was to study the behavioral and neural correlates of Cross-linguistic Transfer effects (CLT) at the word level, in second language learning. Moreover, given that language distance has an impact on CLT, (Paradis, 1987, 2004, Odlin, 1989, 2004, 2005, Gollan, 2005, Ringbom, 2007), two distinct language pairs were examined: Close language pairs (Spanish-French) and distant language pairs (Persian-French). This thesis comprises three studies. In study I, Spanish speakers and in study II Persian speakers were trained for lexical learning until consolidation level. Cognates (phonologically and semantically similar words), Clangs (phonologically similar words with different meanings), and Non-cognate-non-clangs (semantically similar words), were presented in a picture naming task. Accuracy rates and response times as well as event-related fMRI BOLD responses to each word category were measured. Simple and direct contrasts with phonologically similar and phonologically distant words were performed. Thus, Study I reports the results of close languages (Spanish-French) and Study II, reports the results of distant languages (Persian-French). The neurocognitive processing of language learning was further investigated in terms of networks using functional connectivity analysis in distant languages (Persian-French) and the results are reported in Study III. The Results with the General Linear Model analysis show that with close language pairs (French-Spanish), the processing of phonologically similar words (cognates and clangs) relies upon a shared L1-L2 language specific neural areas, whereas processing of phonologically distant words (non-clang-non-cognates), activates L1 language processing areas, but also relies upon working memory, attentional, and processing structures. However, with distant language pairs (French-Persian), even phonologically similar words (cognates and clangs) activate areas known to be involved in attentional processing and cognitive control. Moreover, phonologically distant words (non-clang-non-cognates) also activate areas involved in working memory and executive function processing structures. Thus, the factor of L1-L2 cross-linguistic distance appears to modulate the executive load imposed to the system, on the basis of the degree of phonological overlap between L1-L2 items; thus in order to compensate for more effortful processing demands, the system recruits executive function supporting structures. The results of the connectivity analysis show that, in line with literature (Majerus, et al., 2008; Prat, et al., 2007; Veroude, et al., 2010; Dodel, et al., 2005; Coynel, et al., 2009), when the language proficiency is low, there is enhanced functional connectivity between and within language specific and other cognitive processing (working memory, attentional and cognitive control) networks. However, as proficiency increases, integration values (functional connectivity) decrease. This reflects that language tasks become less effortful and demand less cognitive resources. The results of this dissertation contribute to a better understanding of CLT effects on L2 learning, both in regards to different word types and L1-L2 language distance. These results have implications with regards to L2 learning and teaching strategies and approaches as well as with regards to the development of data-driven therapy approaches in the case of language break down in bilingual population.

Women exhibit greater habituation to painful stimuli than men. The neural mechanism underlying this sex difference is unknown. However, pain habituation has been associated with pain-evoked activity of the subgenual anterior cingulate cortex (sgACC), implicating a connection between the sgACC and the descending pain antinociceptive system. Therefore, the thesis hypothesis was that women have stronger connectivity than men between the sgACC and the descending antinociceptive system. Healthy subjects provided informed consent. 3T MRI images included anatomical diffusion-weighted imaging for structural connectivity analyses (SC) with probabilistic tractography and resting-state functional images for functional connectivity (FC) analyses. Women had stronger sgACC FC with nodes of the descending pain modulation system (raphe, PAG) and the medial thalamus. In contrast, men had stronger sgACC FC with nodes of the salience/attention network (anterior insula, TPJ) and stronger sgACC SC with the hypothalamus. These findings implicate a mechanism for pain habituation and its associated sex differences.

La méditation par le ‘mindfulness’ favorise la stabilité émotionelle, mais les mécanismes neuroneux qui sous-tendent ces effets sont peu connus. Ce projet investiga l’effet du ‘mindfulness’ sur les réponses cérébrales et subjectives à des images négatives, positives et neutres chez des méditants expérimentés et des débutants au moyen de l’imagerie par résonance magnétique fonctionnelle (IRMf). Le ‘mindfulness’ atténua l’intensité émotionelle via différents mécanismes cérébraux pour chaque groupe. Comparés aux méditants, les débutants manifestèrent une déactivation de l’amygdale en réponse aux stimuli émotifs durant le ‘mindfulness’. Comparés aux débutants, les méditants exhibèrent une déactivation de régions du réseau du mode par défaut (RMD) pendant le ‘mindfulness’ pour tous stimuli (cortex médian préfrontal [CMP], cortex cingulaire postérieur [CCP]). Le RMD est constitué de régions fonctionnellement connectées, activées au repos et déactivées lors de tâches explicites. Cependant, nous ne connaissons pas les impacts de l’entraînement par la méditation sur la connectivité entre régions du RMD et si ces effets persistent au-delà d’un état méditatif. La connectivité fonctionnelle entre régions du RMD chez les méditants et débutants au repos fut investiguée au moyen de l’IRMf. Comparés aux débutants, les méditants montrèrent une connectivité affaiblie entre subdivisions du CMP, et une connectivité accrue entre le lobule pariétal inférieur et trois regions du RMD. Ces résultats reflètent que les bienfaits immédiats du ‘mindfulness’ sur la psychopathologie pourraient être dûs à une déactivation de régions limbiques impliquées dans la réactivité émotionelle. De plus, les bienfaits à long-terme de la méditation sur la stabilité émotionelle pourrait être dûs à une déactivation de régions corticales et cingulaires impliquées dans l’évaluation de la signification émotive et une connectivité altérée entre régions du RMD à l’état de repos. / Mindfulness meditation promotes emotional stability, yet little is known of the brain mechanisms through which this is achieved. The impact of mindfulness on the neural and subjective responses to negative, positive, and neutral pictures in experienced meditators and beginners was investigated using functional magnetic resonance imaging (fMRI). Mindfulness attenuated emotional intensity via distinct neural pathways for each group. For beginners, mindfulness induced a deactivation of the amygdala during emotional processing compared to meditators. For meditators (relative to beginners), mindfulness induced deactivations of areas involved in the evaluation of emotional significance and the default mode network (DMN) across all picture categories (medial prefrontal cortex [MPFC], posterior cingulate cortex). The DMN consists of functionally connected brain areas typically activated at rest and deactivated during goal-directed tasks. It remains unknown whether meditation training influences functional connectivity within DMN regions, and if so, whether these effects persist beyond a state of meditation per se. Functional connectivity within DMN regions at rest was examined using fMRI in beginners and meditators. Relative to beginners, meditators exhibited decreased connectivity between MPFC subdivisions, and increased connectivity between the right inferior parietal lobule and three other DMN regions. These findings may reflect that early beneficial effects of mindfulness on psychopathology are due to deactivations of limbic regions involved in emotional reactivity. On the other hand, long-term effects of meditation on emotional stability may occur through a down-regulation of prefrontal and cingulate regions involved in the evaluation of emotional significance, and altered functional connectivity within DMN regions at rest.

Women exhibit greater habituation to painful stimuli than men. The neural mechanism underlying this sex difference is unknown. However, pain habituation has been associated with pain-evoked activity of the subgenual anterior cingulate cortex (sgACC), implicating a connection between the sgACC and the descending pain antinociceptive system. Therefore, the thesis hypothesis was that women have stronger connectivity than men between the sgACC and the descending antinociceptive system. Healthy subjects provided informed consent. 3T MRI images included anatomical diffusion-weighted imaging for structural connectivity analyses (SC) with probabilistic tractography and resting-state functional images for functional connectivity (FC) analyses. Women had stronger sgACC FC with nodes of the descending pain modulation system (raphe, PAG) and the medial thalamus. In contrast, men had stronger sgACC FC with nodes of the salience/attention network (anterior insula, TPJ) and stronger sgACC SC with the hypothalamus. These findings implicate a mechanism for pain habituation and its associated sex differences.

本研究的主要目的在於運用靜息態功能性磁振造影技術來探討高社會焦慮的自我參照處理腦區的功能聯結。根據Clark和Wells(1995)的模型，高社會焦慮者的負向自我心象只透過自我相關的在線索來建構；然而根據Rapee和Heimberg(1997)的模型則假設高社會焦慮者還會納入他人外在訊息，做自我與他人參照訊息的處理。本研究企圖透過神經影像的發現來檢測上述兩個模型。 本研究篩選出四十名大學生分為高社會焦慮組與低社會焦慮組，所有受試者都會進行靜息態功能性磁振造影的掃描，並使用MPFC、PCC、ACC、VMPFC、DMPFC作為種子進行全腦的功能聯結分析並獲得功能聯結圖譜做比較。 研究結果發現高社會焦慮者的MPFC、PCC、ACC都有增加的功能聯結，顯示他們比一般人更容易做自我參照處理，而VMPFC、DMPFC同時有增加的功能聯結，代表高社會焦慮者的自我參照處理除了自我內在的相關訊息外，還會包含他人外在相關訊息的處理，研究結果較支持Rapee和Heimberg(1997)的說法。最後並提出本論文研究限制，與對社會焦慮症的臨床理論與實務上之建議。 / The purpose of the present study was to utilize the resting-state functional magnetic resonance imaging(RS-fMRI) technique to investigate the brain regions in functional connectivity of self-referential processing in socially anxious individuals. According to Clark and Wells’ (1995) view, socially anxious individuals were hypothesized to construct their negative self-image with self-related internal information. However, according to Repee and Heimberg’ s (1997) model, they supposed that socially anxious individuals also brought other-related external information to make other-related external information self-referential and other-referential be processed. The present study was designed to use finding of neuroimaging to examine the two models Forty undergraduate students were assigned to either high or low social-anxiety group. All subjects were asked to be scanned with RS-fMRI. MPFC, PCC, ACC, VMPFC, DMPFC were used as seeds to proceed the whole-brain functional connectivity analysis and acquired functional connectivity maps for comparison. The results revealed that functional connectivity of MPFC, PCC, ACC of high social anxiety group increased, it displayed that they were more easily to do self-referential processing. Besides, functional connectivity of VMPFC and DMPFC also increased simultaneously, which means that the self-referential processing of high social anxiety group not only included self-related internal information but also included other-related external information. The result supported Repee and Heimberg’ s model. The limitations of this study and the suggestions for the theories and clinical treatment of social anxiety disorder were advanced in the end.

La complexité de la connaissance humaine est révèlée dans l'organisation spatiale et temporelle de la dynamique du cerveau. Nous pouvons connaître cette organisation grâce à l'analyse des signaux dépendant du niveau d'oxygène sanguin (BOLD), lesquels sont obtenus par l'imagerie par résonance magnétique fonctionnelle (IRMf). Nous observons des dépendances statistiques entre les régions du cerveau dans les données BOLD. Ce phénomène s' appelle connectivité fonctionnelle (CF). Des modèles computationnels sont développés pour reproduire la connectivité fonctionnelle (CF). Comme les études expérimentales précédantes, ces modèles assument que la CF est stationnaire, c'est-à-dire la moyenne et la covariance des séries temporelles BOLD utilisées par la CF sont constantes au fil du temps. Cependant, des nouvelles études expérimentales concernées par la dynamique de la CF à différentes échelles montrent que la CF change dans le temps. Cette caractéristique n'a pas été reproduite dans ces modèles computationnels précédants. Ici on a augmenté la non-linéarité de la dynamique locale dans un modèle computationnel à grande échelle. Ce modèle peut reproduire la grande variabilité de la CF observée dans les études expérimentales. / The complexity of human cognition is revealed in the spatio-temporal organization of brain dynamics. We can gain insight into this organization through the analysis of blood oxygenation-level dependent (BOLD) signals, which are obtained from functional magnetic resonance imaging (fMRI). In BOLD data we can observe statistical dependencies between brain regions. This phenomenon is known as functional connectivity (FC). Computational models are being developed to reproduce the FC of the brain. As in previous empirical studies, these models assume that FC is stationary, i.e. the mean and the covariance of the BOLD time series used for the FC are constant over time. Nevertheless, recent empirical studies focusing on the dynamics of FC at different time scales show that FC is variable in time. This feature is not reproduced in the simulated data generated by some previous computational models. Here we have enhanced the non-linearity of local dynamics in a large-scale computational model. By enhancing this non-linearity, our model is able to reproduce the variability of the FC found in empirical data.

Orientador: Prof. Dr. João Ricardo Sato / The brain is a complex system organized in structurally segregated and functionally specialized regions. The brain areas are composed of neuronal networks interconnected by axonal pathways that integrate through correlated neural activity. Recent studies on neural connectivity using graph theoretical analysis have revealed that brain networks interact through densely connected regions with high topological value called hubs. Previous studies of Default Mode Network (DMN), one of the most important resting-state networks, have improved the understanding of the intrinsic neuronal activity and the dynamics of the human brain. Spontaneous brain activity and Resting-State Functional Connectivity (RSFC) patterns of Resting-State Network (RSN) are essential for the comprehension of the brain function. Neuroimaging techniques such as functional Near Infrared Spectroscopy (fNIRS) make these studies possible. Thus, the main objective of this study was to investigate the RSFC using Eigenvector Centrality (EVC) measure of graph theory in fNIRS data. This work has demonstrated the effectiveness of the graph analysis for detection of hubs and mcommunities, and identified brain regions associated with rich-club, that integrates highly interconnected hubs and plays a central role in the flow and integration of Information throughout the brain. One can also conclude from the RSFC analysis the existence of functional hubs associated with DMN. / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia da Informação, 2017. / O cérebro é um sistema complexo organizado em regiões segregadas estruturalmente e especializadas funcionalmente que são compostas por redes neuronais interconectadas por vias axonais que se integram através de atividade neural correlacionada. Estudos recentes sobre conectividade neural usando teoria de grafos revelaram que as redes cerebrais interagem através de regiões densamente conectadas e com alto valor topológico denominadas hubs. Dentre as redes existentes destaca-se, por sua contribuição para a melhor compreensão do funcionamento do cérebro humano, a rede de modo padrão (Default Mode Network, DMN). A atividade espontânea do cérebro e os padrões de conectividade funcional (Resting-State Functional Connectivity, RSFC) das redes cerebrais na condição de repouso (Resting-State Network, RSN) também se tornam essenciais nos estudos que visam compreender a função desse órgão, estudos esses possibilitados graças às técnicas de neuroimagem destacando-se a espectroscopia funcional no infravermelho próximo (functional Near Infrared Spectroscopy, fNIRS). Assim, o objetivo principal deste estudo foi investigar a RSFC usando a medida de centralidade do autovetor (Eigenvector Centrality, EVC), técnica pertencente à teoria de grafos, em dados de fNIRS. Este estudo pode demonstrar a eficácia da metodologia empregada para analisar a RSFC além de revelar a existência de um núcleo estrutural, denominado hub complex, densamente conectado (rich-club), que integra hubs altamente interligados e desempenha papel central no fluxo e integração da informação ao longo do cérebro. Pode-se também concluir a partir da análise da RSFC a existência de hubs funcionais associados à DMN.

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.

Abstract The concept of resting state functional magnetic resonance imaging (fMRI) is built onto an original finding in 1995 that brain hemispheres present synchronous signal fluctuations with distinct patterns. fMRI measurements rely on blood oxygenation changes that indirectly mirror neural activity. Therefore, the origin of functional connectivity patterns, resting state networks (RSNs), has been a widely debated research question and numerous contributing factors have been identified. According to current understanding the fluctuations reflect maintenance of the system integrity in addition to spontaneous thought and action processes in the resting state. A popular method to study the functional connectivity in resting state fMRI is spatial independent component analysis (ICA) that decomposes signal sources into statistically independent components. The dichotomy of functional specialization versus functional integration has a correspondence in fMRI studies where RSNs play the integrative viewpoint of brain function. Although canonical large-scale RSNs are broadly distributed they also express modularity that can be accomplished by ICA with a high number of estimated components. The characteristics of high ICA dimensionality are broadly investigated in the thesis. An enduring issue in resting state research has been the confounding noise sources like motion and cardiorespiratory processes which may hamper the analysis. In this thesis the ability of ICA to separate these noise sources from the default mode network, a major RSN, is studied. Additionally, the suitability of ICA for full frequency spectrum analysis, a relatively rare setting in biosignal analysis, is investigated. The results of the thesis support the viewpoint of ICA as a robust analysis method for functional connectivity analysis. Cardiorespiratory and motion induced noise did not confound the functional connectivity analyses with ICA. High dimensional ICA provided better signal source separation, revealed the modular structure of the RSNs and pinpointed the specific aberrations in the autism spectrum disorder population. ICA was also found applicable for fully explorative analysis in both the spatial and temporal domains and indicated functional connectivity changes induced by transcranial bright light stimulation. / Tiivistelmä Konsepti lepotilan tutkimisesta toiminnallisella magneettikuvauksella (engl. functional magnetic resonance imaging, fMRI) on rakentunut vuonna 1995 tehdylle löydökselle aivopuoliskojen välillä synkronisesta signaalivaihtelusta. Mittaukset perustuvat veren hapetuksen muutoksiin, jotka epäsuorasti heijastelevat hermostollista toimintaa. Tämän takia toiminnallisen kytkennällisyyden muodot, lepotilaverkostot, ovat olleet laajasti väitelty tutkimusaihe ja monia verkostoihin vaikuttavia tekijöitä onkin tunnistettu. Nykykäsityksen mukaan signaalivaihtelut lepotilassa heijastelevat järjestelmän yhtenäisyyden ylläpitoa spontaanin ajattelun ja toiminnan lisäksi. Suosittu menetelmä toiminnallisen kytkennällisyyden tutkimiseen lepotilan fMRI:ssä on spatiaalinen itsenäisten komponenttien analyysi (engl. independent component analysis, ICA), joka hajottaa signaalilähteet tilastollisesti itsenäisiin komponentteihin. Aivotoiminnan mallintamisessa kahtiajaolla toiminnalliseen erikoistumiseen ja toiminnalliseen integraatioon on vastaavuus fMRI-tutkimukseen, jossa lepotilaverkostot vastaavat toiminnallisen integraation näkökulmasta. Vaikka kanoniset lepotilaverkostot ovat laaja-alaisia, ne ovat toisaalta modulaarisia, jota voidaan tutkia tutkimalla korkean komponenttimäärän ICA-hajotelmaa. Korkea- dimensioisen ICA-hajotelman ominaisuuksia tutkitaan laajasti tässä väitöskirjassa. Kestoaihe lepotilatutkimuksessa on ollut analyysiä hankaloittavien kohinalähteiden kuten liikkeen ja kardiorespiratoristen prosessien vaikutus. Väitöskirjassa tutkitaan ICA:n kykyä erotella kohinalähteitä ’default mode’ -verkostosta, joka on merkittävin lepotilaverkosto. Lisäksi tutkitaan ICA:n soveltuvuutta täyden taajuuskaistan analysointiin, joka on verrattain harvinaista biosignaalien analyysissä. Väitöskirjan tulokset tukevat näkemystä ICA:n suorituskyvystä toiminnallisen kytkennällisyyden analyysissä. Kardiorespiratorinen ja liikkeestä lähtöisin oleva kohina ei häirinnyt merkittävästi ICA-tuloksia. Korkeadimensioinen ICA tarjosi paremman erottelun signaalilähteille, paljasti lepotilaverkostojen modulaarisen rakenteen ja määritti erityisen poikkeaman autismin kirjon oireyhtymän populaatiossa. ICA:n havaittiin olevan soveltuva täyseksploratiiviselle analyysille ajassa ja avaruudessa; tulos viittaa toiminnallisen kytkennällisyyden muutoksiin kallon läpäisevän kirkasvalostimulaation aikaansaamana.