Two main theories of neural atypicality have been postulated in autism. One theory proposes that autism can be explained as the result of atypical patterns of hypo and hyper functional connectivity (FC) within and between brain areas. A complementary theory suggests that atypical functional communication in autism could result from an altered ratio between excitatory and inhibitory input (E:I imbalance). These theories have been previously explored as they might apply to all individuals with a behavioral diagnosis. However, given the multiscale heterogeneity characterizing autism, different subsets of individuals with autism may display different patterns of functional connectivity atypicalities and E:I imbalance. This thesis sets out to explore how neural atypicalities in connectivity and E:I imbalance might be differentially expressed in subsets of the autistic population. To this end, two empirical investigations were conducted. First, the connectivity hypothesis was explored by investigating whether behaviorally-defined subtypes were associated with different patterns of FC atypicalities. Behaviorally-defined subtypes were obtained by stratifying autistic individuals based on their relative balance between social communication (SC) and restricted and repetitive behaviors (RRBs) core symptom domains. This approach yielded three behaviorally-based subtypes: SC>RRB, SCRRB displayed hypoconnectivity between somatomotor and perisylvian circuitry, while subtypes SC=RRB showed hypoconnectivity between somatomotor and visual association areas and hyperconnectivity between medial motor and anterior salience networks. Finally, these subtype-specific FC alterations were shown to be enriched for partially distinct genetic mechanisms, some of which related to excitatory-inhibitory neurons and astrocytes. In a second study, the EI imbalance hypothesis was explored by investigating whether autism subtypes could be identified based on an E:I-sensitive metric computed from electroencephalographic (EEG) data. Specifically, the Hurst exponent (H) – a metric that has been shown to be affected by changes in excitatory input – was computed on EEG time-series data, obtained in two resting state conditions of eyes open and closed. H-based clustering revealed two E:I-based neurosubtypes across conditions with opposing patterns of E:I imbalance compared to neurotypical controls. Autism neurosubtype 1 showed on-average higher H values, while neurosubtype 2 displayed on-average lower H. These opposing E:I balance patterns were present globally across the brain, with the limited exception of an orthogonal larger decrease in H in non-frontal electrodes in neurosubtype 2. Finally, investigation at the behavioral level identified distinct multivariate brain-behavior relationships between age, intelligence, autistic traits and H. Taken together, these empirical findings demonstrate that the two major theories of neural atypicality in autism – FC alteration and E:I imbalance – do not apply equally to all individuals with a behavioral diagnosis. Rather, different subtypes of autism exist that display contrasting patterns of neural atypicality compared to typically-developing individuals. These contrasting patterns might be driven by differentially altered primary or compensatory E:I mechanisms shaping distinct atypical cortical organizations within the subtypes. Interestingly, the relationship between specific neural atypicalities and variability at the behavioral and genetic level is, however, subtle across the subtypes. This limited multiscale association could suggest that heterogeneity in autism might be due to the presence, within the larger population, of subtype-specific mosaic-like patterns of atypicalities at the behavioral and biological level. Further research is required to thoroughly characterize how these levels map onto one another within the subtypes and determine the pathophysiological mechanisms driving their development.

Post-traumatic stress disorder (PTSD) is a psychiatric disorder that is caused by exposure to traumatic or stressful events in life. 3,4-Methylenedioxymethamphetamine (MDMA) has been shown to be an effective agent in drug-assisted psychotherapy for PTSD. In this systematic review, we aim to evaluate the effect MDMA has on functional connectivity in healthy individuals and individuals with PTSD and investigate the potential mechanisms via which MDMA exerts its effects in MDMA-assisted psychotherapy for PTSD patients. A total of 134 articles from Web of Science and Medline EBSCO were screened and 5 articles relevant for the systematic review were identified. After MDMA administration, an increase and decrease in functional connectivity in multiple brain areas and networks was observed, such as the thalamus, visual cortex, anterior cingulate cortex, hippocampus, amygdala, prefrontal cortex, default mode network, cerebellar network, sensorimotor network, salience network, and executive network. Notably, MDMA increased amygdala-hippocampal functional connectivity which may link to improved emotion regulation and fear extinction in patients receiving MDMA-assisted therapy. The findings evidence the complex effects of MDMA on brain connectivity and highlight the need for further research in this area, although MDMA-assisted therapy does prove to be a promising alternative for treating PTSD.

Purpose: In a previous neuroimaging study, patients with taste loss showed stronger activations in gustatory cortices compared to people with normal taste function during taste stimulations. The aim of the current study was to examine whether there are changes in central-nervous functional connectivity in patients with taste loss. Methods: We selected 26 pairs of brain regions related to taste processing as our regions of interests (ROIs). Functional magnetic resonance imaging (fMRI) was used to measure brain responses in seven patients with taste loss and 12 healthy controls as they received taste stimulations (taste condition) and water (water condition). The data were analysed using ROI-to-ROI functional connectivity analysis (FCA). Results: We observed weaker functional connectivity in the patient group between the left and right orbitofrontal cortex in the taste condition and between the left frontal pole and the left superior frontal gyrus in the water condition. Conclusion: These results suggested that patients with taste loss experience changes of functional connectivity between brain regions not only relevant to taste processing but also to cognitive functions. While further studies are needed, fMRI might be helpful in diagnosing taste loss as an additional tool in exceptional cases.

No description available.

Obesity is associated with structural and functional alterations in brain areas that are often functionally distinct and anatomically distant. This suggests that obesity is associated with differences in functional connectivity of regions distributed across the brain. However, studies addressing whole brain functional connectivity in obesity remain scarce. Here, we compared voxel-wise degree centrality and eigenvector centrality between participants with obesity (n=20) and normal-weight controls (n=21). We analyzed resting state and task-related fMRI data acquired from the same individuals. Relative to normal-weight controls, participants with obesity exhibited reduced degree centrality in the right middle frontal gyrus in the resting-state condition. During the task fMRI condition, obese participants exhibited less degree centrality in the left middle frontal gyrus and the lateral occipital cortex along with reduced eigenvector centrality in the lateral occipital cortex and occipital pole. Our results highlight the central role of the middle frontal gyrus in the pathophysiology of obesity, a structure involved in several brain circuits signaling attention, executive functions and motor functions. Additionally, our analysis suggests the existence of task-dependent reduced centrality in occipital areas; regions with a role in perceptual processes and that are profoundly modulated by attention.

INTRODUÇÃO: Transtornos psiquiátricos com sintomas psicóticos trazem prejuízos ocupacionais e sociais significativos aos seus portadores, com aumento da mortalidade e morbidade. Estes transtornos têm sido estudados como alterações do padrão de conectividade funcional nas redes cerebrais do estado de repouso. Entretanto, tais relatos são mais frequentes em pacientes crônicos, com literatura escassa sobre pacientes em primeiro episódio psicótico, principalmente não realizando comparações entre as redes. OBJETIVO: Este foi um estudo exploratório com objetivo de caracterizar a conectividade funcional cerebral das redes do estado de repouso em pacientes de primeiro episódio psicótico através da ressonância nuclear magnética funcional comparando-os a irmãos e a controles de base populacional. MÉTODOS: A amostra foi composta por por 38 pacientes em primeiro episódio psicótico, 13 irmãos e 41 controles de base populacional. Foram coletadas imagens por ressonância magnética funcional e a conectividade funcional foi obtida através do coeficiente de correlação de Pearson da série temporal do sinal BOLD de 264 regiões de interesse. A comparação da conectividade funcional entre os grupos de participantes foi feita pelo método Partial Least Square. Também foi utilizado o método Behavior Partial Least Square para buscar um padrão de conexões alteradas que estivesse associado a gravidade dos sintomas psicóticos, ao tempo de tratamento e a duração da psicose não tratada. A análise estatística contou com 10.000 permutações e um método de reamostragem e foram considerados significativos valores de p<0.05. RESULTADOS: As alterações nas redes, em sua maioria, foram devido à mudança de correlação positiva para correlação negativa nos pacientes em relação aos controles. As redes com maior número de conexões alteradas entre pacientes e controles foram a rede sensóriomotor mão, Default Mode Network (DMN) e rede visual. As conexões estiveram mais alteradas no lobo frontal direito. Não foi encontrada associação entre o padrão de conectividade funcional dos pacientes e a duração de psicose não tratada, o tempo de tratamento farmacológico e a gravidade da psicose. Na comparação entre pacientes e irmãos, foi encontrada uma tendência à significância de um padrão de conexões alteradas. Não foi encontrada diferença significativa entre o grupo de irmãos e o grupo controle. DISCUSSÃO: Pacientes em primeiro episódio psicótico apresentaram maior segregação das redes do estado de repouso comparados a controles de base populacional, corroborando a hipótese etiológica da Esquizofrenia de uma desconectividade funcional do cérebro. A rede sensório-motor mão surpreendentemente foi a rede com maior número de alterações, apontando a necessidade de mais estudos sobre a mesma. Os irmãos não apresentaram um padrão de conexões do repouso diferente dos controles, não corroborando as hipóteses de que tal grupo apresentaria um padrão intermediário entre pacientes e controles. CONCLUSÃO: Os achados apontam para um uma topologia cerebral amplamente prejudicada já no início da psicose, com uma maior segregação entre as redes do estado de repouso em pacientes de primeiro episódio psicótico. / INTRODUCTION: Psychiatric disorders with psychotic symptoms bring significant occupational and social harm to their patients, with increased mortality and morbidity. These disorders have been studies as changes in the functional connectivity patterns in resting state brain networks. However, reports are more frequently made in chronic patients, with a scarce literature from first episode psychosis patients, mostly not making intra-networks comparison. OBJECTIVE: This was an exploratory study that had the objective of characterize the brain functional connectivity of resting networks in first episode psychosis patients through functional magnetic resonance imaging compared to siblings and to population based controls. METHODS: Final sample consisted of 38 first episode psychosis, 13 siblings and 41 population-based controls. Functional magnetic resonance images were collected in first episode psychosis, siblings and population based controls. Functional connectivity was obtained through the Pearson Correlation Coefficient of 264 regions of interest BOLD signal time series´. Comparison of functional connectivity among groups of participants was made using Partial Least Square method. Behavior Partial Least Square was performed to seek for a pattern associated with illness severity, pharmacological treatment time and duration of untreated psychosis. The statistical analysis was conducted with 10,000 permutations and bootstrap considering significant values of p<0.05. RESULTS: Aberrant network connections were mostrly due to changes of positive correlation to negative correlation in patients compared to controle. The majority of altered connections were found in sensory-motor network, DMN and visual network. The areas most affected were right frontal lobe. It was not found a functional connectivity pattern associated with illness severity, treatment time and duration of untreated psychosis. A tendency difference was found in the connectivity pattern between siblings and patients. No different connectivity pattern was found between siblings and controls. DISCUSSION: First episode psychosis presented more segregated resting state networks than controls, reinforcing the disconnectivity etiology hypothesis for schizophrenia. An unexpected result was sensory-motor hand network being the network with more altered connections, pointing to the need of more studies to comprehend it. The sibling group did not differ from the control group, not corroborating the hypotheses that such a group would present an intermediate pattern between patients and controls. CONCLUSION: The findings point to a largely impaired brain topology already at the beginning of the psychosis, with greater segregation between resting state networks in patients with first episode psychosis.

A quantidade de habitat remanescente, a conectividade e o tamanho dos fragmentos são sugeridos como determinantes para a manutenção de espécies em paisagens fragmentadas, e dessa maneira é essencial entendermos e modelarmos tais relações para o embasamento de políticas de conservação. Para analisarmos tais efeitos na riqueza e abundância de aves de sub-bosque e na abundância de 29 espécies de aves da Mata Atlântica, construímos modelos com variáveis representando o tamanho do fragmento e graus diversos de conectividade funcional em três paisagens com diferentes proporções de habitat (14, 31 e 45% de habitat). Posteriormente, confrontamos tais modelos com dados provenientes de amostragens com redes de neblina (4.818 indivíduos) com um esforço amostral total de quase 34.000 horas-rede em 53 fragmentos de diferentes tamanhos (2 a 159 ha) e graus de conectividades (considerando conexões por corredor ou por curtas distâncias pela matriz). Em seguida, hierarquizamos tais modelos através do critério de Informação de Akaike. Um total de 117 espécies foi capturado, e a paisagem com maior riqueza foi aquela de maior proporção de mata (87), enquanto as outras duas apresentaram riquezas semelhantes e menores (62 e 70), o que sugere um limiar de habitat entre 32 e 44% para a perda de um grande número de espécies. Além disso, os aspectos de configuração foram importantes em todas as paisagens, contudo, diferentes características foram relevantes em cada um dos casos. Enquanto na paisagem com menor proporção de habitat o tamanho dos fragmentos foi extremamente influente na determinação da riqueza e da abundância de espécies, os aspectos relacionados à conectividade foram mais importantes nas paisagens com 31 e 45% de proporção de habitat. Dentre as variáveis de conectividade, as que representam conectividade por corredores foram particularmente importantes, seguidas pelas de pequenos cruzamentos pela matriz (20 m). Modelos que levaram em consideração cruzamentos de 40 m pela matriz foram bem menos plausíveis que os demais. Os modelos para abundância das 29 espécies também resultaram em um padrão similar ao observado para a comunidade. No entanto, a importância relativa do tamanho do fragmento e da conectividade mudou em função da proporção de habitat, de acordo com a espécie abordada. Os resultados aqui apresentados são importantes para o embasamento de políticas de manejo para a conservação, e ressaltam a influência relativa das variáveis de configuração ao longo do gradiente de quantidade de hábitat, e devem ser consideradas quando na seleção de áreas para conservação, restauração ou qualquer forma de manejo voltado para a conservação. / Landscape aspects such as habitat amount, fragment size and connectivity, have been suggested as key features for maintaining species in altered landscapes, and thus are essential to be modeled and comprehended for management and conservation purposes. To test their effects on understory Atlantic forest bird species, we built models with variables representing fragment size and functional connectivity in 3 landscapes with different proportions of forest (14, 31 and 45%), and confronted with data from more than 4,818 individuals captured in 53 fragments of different sizes (2.06 to 158.45 ha) and connectivitys (connected by corridors, or by short distances), and then we ranked under a model selection approach (AIC). A total of 117 species were recorded, and the landscape with higher amount of forest was richer (87) than the two others which presented a similar lower richness (62 and 70), what suggests a threshold amount of habitat between 32 to 44%. Configuration aspects were important in all cases; however, different characteristics influenced species richness and abundance in each landscape. Patch size was important in determining species richness and abundance in the landscape with low amount of habitat, while connectivity aspects were crucial in the landscapes with higher amounts of habitat. Within the connectivity models, particularly the ones that take in to account the connectivity by corridors, but also the ones that consider short movements through the matrix are far better supported, then the ones by longer distances gaps. Moreover, specieslevel analyses yielded results similar to the pattern found for the whole assemblage, and the configuration variable influence varied along the habitat conversion gradient. The results presented here are important for management planning towards conservation, and should be considered in site selection for conservation, restoration or any other kind of management.

Face à l’effet des changements d’utilisations de sol sur la dispersion des espèces, des actions ont récemment été menées au niveau des régions françaises pour favoriser et maintenir la connectivité. L’objectif de cette étude a donc été de quantifier la connectivité chez une espèce modèle menacée en Europe occidentale : la vipère péliade (V. berus). Ses mœurs discrètes ont nécessité pour mesurer sa dispersion d’utiliser une approche indirecte basée sur l’individu et des outils moléculaire. Ainsi, les flux de gènes de V. berus ont été analysés à fine échelle spatiale (10 × 7 km²) sur un site d’étude (A0) constitué de deux secteurs paysagers contrastés (A1/A2), à la fois par l’utilisation des sols et leur stabilité temporelle (instable/stable). La différenciation génétique sur A0 est faible et surtout associée à un fort patron d’isolement par la distance (IBD). La dispersion est donc limitée spatialement chez V. berus (dispersion natale ≤ 500 m) et liée aux mâles à l’âge adulte. De plus, les flux de gènes sont aussi expliqués par l’hétérogénéité du paysage : (i) par les prairies (A0), l’urbanisation (A1) les pelouses et boisements (A2), (ii) particulièrement à 300 m autour des individus parmi les étendues spatiales testées (100-500 m) et (iii) plus par l’agencement spatial que le type et la quantité des taches d’habitats. Ces résultats innovants contribuent à (i) la réflexion sur la stratégie de conservation pour V. berus et (ii) souligner la diversité des facteurs à considérer dans l’étude et le maintien de la connectivité à une plus vaste échelle spatiale (patrons et processus de dispersion, échelles spatio-temporelles). / Face to the impact of land-use changes on species dispersal, decisions were recently conducted at French regional scale to favour and to maintain connectivity. The aim of this work was to quantified connectivity for a model species threatened in Western Europe : the common European adder (V. berus). Its secretive behaviour required to use an indirect and individual-based approach to measure its dispersal thanks to molecular techniques. Thus, V berus gene flow were analysed at fine spatial scale (10 × 7 km²) on a study site (A0) made up of two sub-areas with contrasting landscapes (A1/A2), both by land use and their temporal stability (instable/stable). Genetic differentiation on A0 is weak and mainly associated with a strong isolation-by-distance (IBD) pattern. Dispersal is therefore spatially limited in V. berus (natal dispersal ≤ 500m) and related to males concerning adults. Moreover, gene flow is also influenced by landscape heterogeneity : (i) by meadow (A0), urbanisation (A1) and dry grassland and forests (A2), (ii) particularly at 300m around individuals among spatial extent tested (10-500m) and (iii) more by the spatial configuration than the type and quantity of habitat patches. These innovative results contribute to (i) reflection about conservation strategies for V. Berus et (ii) underly the diversity of factors to consider in studying and maintaining connectivity at a more large spatial scale (dispersal pattern and process, spatio-temporal scales).

The strong relationship between cognitive processing and coherent behaviour and neurocognitive networks justifies the current huge interest in cortical functional connectivity modeling. This has fostered the development of connectivity estimators from the classical bivariate coherence concept to the notion of multivariate partial directed coherence (PDC) which provides information about temporal dependencies exposing cause and effect relationships. This work examines PDC performance for scalp EEG data whose research value has been subject to much debate in the light of the presence of volume conduction (VC) effects that often obscure the actual nature of cortical source dynamics. Through analytical considerations and simulations we show that even though (VC) can hinder accurate connectivity estimation, one can mitigate its effects by a judicious choice of scalp electrode configuration/ground reference. This observation allows settling the connectivity estimation adequacy debate in the presence of PDC. / A forte relação que processamento cognitivo e comportamento coerente tem com redes neurocognitivas justifica o enorme interesse atual em modelamento de conectividade cortical. Este fato tem justificado o desenvolvimento de estimadores de conectividade desde a clássica coerência bivariada até a noção multivariada de coerência parcial direcionada (PDC) que exibe informação a cerca de dependências temporais que permitem expor relações de causa e efeito. O presente trabalho examina o desempenho da PDC no contexto de EEG de escalpo cujo valor em pesquisa sob os efeitos de condução de volume (VC) tem sido objeto de uma quantidade substancial de questionamentos na medida em esta obscurece a observação da dinâmica das fontes corticais. Por meio de considerações analíticas e simulações, mostramos que é possível mitigar os erros de estimação devidos à VC através da escolha judiciosa da configuração de eletrodos e da referência de terra. Esta observação permite resolver o conflito acerca da adequabilidade da inferência cortical baseada em EEG de escalpo.

Le cerveau humain est un réseau très complexe. Le fonctionnement cérébral ne résulte donc pas de l'activation de régions cérébrales isolées mais au contraire met en jeu des réseaux distribués dans le cerveau (Bassett and Sporns, 2017; McIntosh, 2000). Par conséquent, l'analyse de la connectivité cérébrale à partir des données de neuroimagerie occupe aujourd'hui une place centrale dans la compréhension des fonctions cognitives (Sporns, 2010). Grâce à son excellente résolution spatiale, l'IRMf est devenue l'une des méthodes non invasives les plus couramment utilisées pour étudier cette connectivité. Cependant, l'IRMf a une faible résolution temporelle ce qui rend très difficile le suivi de la dynamique des réseaux cérébraux. Un défi considérable en neuroscience cognitive est donc l'identification et le suivi des réseaux cérébraux sur des durées courtes (Hutchison et al., 2013), généralement <1s pour une tâche de dénomination d'images, par exemple. Jusqu'à présent, peu d'études ont abordé cette question qui nécessite l'utilisation de techniques ayant une résolution temporelle très élevée (de l'ordre de la ms), ce qui est le cas pour la magnéto- ou l'électro-encéphalographie (MEG ou EEG). Cependant, l'interprétation des mesures de connectivité à partir d'enregistrements effectués au niveau des électrodes (scalp) n'est pas simple, car ces enregistrements ont une faible résolution spatiale et leur précision est altérée par les effets de conduction par le volume (Schoffelen and Gross, 2009). Ainsi, au cours des dernières années, l'analyse de la connectivité fonctionnelle au niveau des sources corticales reconstruites à partir des signaux du scalp a fait l'objet d'un intérêt croissant. L'avantage de cette méthode est d'améliorer la résolution spatiale, tout en conservant l'excellente résolution temporelle de l'EEG ou de la MEG (Hassan et al., 2014; Hassan and Wendling, 2018; Schoffelen and Gross, 2009). Cependant, l'aspect dynamique n'a pas été suffisamment exploité par cette méthode. Le premier objectif de cette thèse est de montrer comment l'approche « EEG connectivité source » permet de suivre la dynamique spatio-temporelle des réseaux cérébraux impliqués soit dans une tache cognitive, soit à l'état de repos. Par ailleurs, les études récentes ont montré que les désordres neurologiques sont le plus souvent associés à des anomalies dans la connectivité cérébrale qui entraînent des altérations dans des réseaux cérébraux «large-échelle» impliquant des régions distantes (Fornito and Bullmore, 2014). C'est particulièrement le cas pour l'épilepsie et les maladies neurodégénératives (Alzheimer, Parkinson) qui constituent, selon l'OMS, un enjeu majeur de santé publique. Dans ce contexte, la demande clinique est très forte pour de nouvelles méthodes capables d'identifier des réseaux pathologiques, méthodes simples à mettre en œuvre et surtout non invasives. Ceci est le deuxième objectif de cette thèse. / The human brain is a very complex network. Cerebral function therefore does not imply activation of isolated brain regions but instead involves distributed networks in the brain (Bassett and Sporns, 2017, McIntosh, 2000). Therefore, the analysis of the brain connectivity from neuroimaging data has an important role to understand cognitive functions (Sporns, 2010). Thanks to its excellent spatial resolution, fMRI has become one of the most common non-invasive methods used to study this connectivity. However, fMRI has a low temporal resolution which makes it very difficult to monitor the dynamics of brain networks. A considerable challenge in cognitive neuroscience is therefore the identification and monitoring of brain networks over short time durations(Hutchison et al., 2013), usually <1s for a picture naming task, for example. So far, few studies have addressed this issue which requires the use of techniques with a very high temporal resolution (of the order of the ms), which is the case for magneto- or electro-encephalography (MEG or EEG). However, the interpretation of connectivity measurements from recordings made at the level of the electrodes (scalp) is not simple because these recordings have low spatial resolution and their accuracy is impaired by volume conduction effects (Schoffelen and Gross, 2009). Thus, during recent years, the analysis of functional connectivity at the level of cortical sources reconstructed from scalp signals has been of increasing interest. The advantage of this method is to improve the spatial resolution, while maintaining the excellent resolution of EEG or MEG (Hassan et al., 2014; Hassan and Wendling, 2018; Schoffelen and Gross, 2009). However, the dynamic aspect has not been sufficiently exploited by this method. The first objective of this thesis is to show how the EEG connectivity approach source "makes it possible to follow the spatio-temporal dynamics of the cerebral networks involved either in a cognitive task or at rest. Moreover, recent studies have shown that neurological disorders are most often associated with abnormalities in cerebral connectivity that result in alterations in wide-scale brain networks involving remote regions (Fornito and Bullmore, 2014). This is particularly the case for epilepsy and neurodegenerative diseases (Alzheimer's, Parkinson's) which constitute, according to WHO, a major issue of public health.In this context, the need is high for new methods capable of identifying Pathological networks, from easy to use and non-invasive techniques. This is the second objective of this thesis.