Dissertations / Theses on the topic 'Functional connectomes'

Les neurones corticaux sont générés sur de longues périodes embryonnaires et post-natales. Des travaux précédents ont montré que les neurones générés à des stades embryonnaires précoces jouent un rôle essentiel dans la coordination de l'activité neuronale nécessaire à la maturation des réseaux de neurones corticaux. La première partie de mon travail a consisté à caractériser le connectome structural des neurones glutamatergiques et GABAergiques en utilisant la méthode du « fate mapping » permettant l’expression de protéines fluorescentes en fonction de la date de genèse des neurones. En utilisant la microscopie à feuillet de lumière sur des cerveaux transparisés, j’ai pu quantifier la distribution de différentes populations neuronales dans le cerveau entier.La deuxième partie de mon travail a été consacrée à caractériser le connectome fonctionnel des neurones GABAergiques et à démontrer la présence de neurones « hubs » dans le cortex en baril en développement. En utilisant des lignées de souris transgéniques exprimant l’indicateur de calcium GCaMP6s, nous avons suivi la maturation et la dynamique fonctionnelle du réseau neuronal au cours des deux premières semaines postnatales en utilisant l’imagerie à deux photons in vivo. La distribution des liens fonctionnels entre neurones suit une loi de probabilité à queue lourde suggérant la présence de neurones « hubs ». En utilisant l’imagerie calcique à deux photons et une stimulation « optogénétique-holographique », nous avons démontré le rôle « hub » d’une sous-population de neurones GABAergiques dans la synchronisation de l’activité du réseau dans le cortex en baril au cours du développement
Cortical neurons are generated throughout an extended embryonic period. Recent studies indicate that the cells originating from the earliest stages of neurogenesis are critically involved in coordinating neuronal activity, instructing network maturation throughout large cortical areas. The first part of my work was building and mining brain cell atlases and connectomes. I first characterized the brain-wide structural connectome of early-born glutamatergic and GABAergic neurons, fluorescently labeled according to their date of birth (genetic fate-mapping approach). Using light-sheet microscopy on cleared brains, I quantify the distribution of both populations in the whole brain to create an Atlas.The second part of my work was the characterization of GABAergic neurons functional connectome and the characterization of hub cells in the developing barrel cortex in vivo. By using transgenic mice lines expressing the calcium indicator GCaMP6s, we follow the maturation and the functional dynamics of the network during the two first postnatal weeks using two-photon imaging. The characteristically heavy-tailed distribution of functional connections between neurons that we observed, strongly suggest the presence of hub neurons. Using two-photon calcium imaging and holographic-optogenetic stimulation we entangle the necessary and sufficient conditions of how GABAergic neurons contribute to and synchronize network activity as acting as hub neuron in the barrel cortex

During the past decade, there has been a great interest in creating mathematical models to describe the properties of connectivity in the human brain. One of the established tools to describe these interactions among regions of the brain is graph theory. However, graph theoretical methods were mainly designed for the analysis of single network which is problematic for neuroscientists wishing to study groups of subjects. Specifically, studies using the Rich Club (RC) graph measure require cumbersome methods to make statistical inferences. In the first part of this work, we propose a framework to analyse the inter-subject variability in Rich Club organisation. The proposed framework is used to identify the changes in RC coefficient and RC organisation in patients with schizophrenia relative to healthy control. We follow this work by proposing a novel method, named Rich Block (RB), which is a combination of the tradition Rich Club and Stochastic Block Models (SBM). We show that using RBs can not only facilitate an inter-subject statistical inference, it can also account for differences in profile of connectivity, and control for subject-level covariates. We validate the Rich Block approach by simulating networks of different size and structure. We find that RB accurately estimates RC coefficients and RC organisations, specifically, in network with large number of nodes and blocks. With real data we use RB to identify changes in coefficient and organisation of highly connected sub-graphs of hub blocks in schizophrenia. In the final portion of this work, we examine the methods used to define each edge in networks formed from resting-state functional magnetic resonance imaging (rs-fMRI). The standard approach in rs-fMRI is to divide the brain into regions, extract time series, and compute the temporal correlation between each region. These correlations are assumed to follow standard results, when in fact serial autocorrelation in the time series can corrupt these results. While some authors have proposed corrections to account for autocorrelation, they are poorly documented and always assume homogeneity of autocorrelation over brain regions. Thus we propose a method to account for bias in interregion correlation estimates due to autocorrelation. We develop an exact method and an approximate, more computationally efficient method that adjusts for the sampling variability in the correlation coefficient. We use inter-subject scrambled real-data to validate the proposed methods under a null setting, and intact real-data to examine the impact of our method on graph theoretical measures. We find that the standard methods fail to practically correct the sensitivity and specificity level due to over-simplifying the temporal structure of BOLD time series, while even our approximate method is substantially more accurate.

Consciousness and loss of consciousness is something we encounter in our everyday lives. Despite its commonplace in everyday life, scientists are still trying to understand and find reliable markers for it. In this work we use a data-driven K-means clustering approach to uncover the different functional patterns associated with different consciousness levels. We pursue this study using a high resolution optogenetic voltage image of the mouse brain waking up from anesthesia. The main questions we addressed in this study are: Can we identify signatures of conscious and unconsciousness from functional connectivity patterns? What is the nature of the different patterns that correspond to wakefulness and anesthesia? What is the nature of dynamics between these functional patterns in wakefulness and anesthesia? How does the anatomical connectivity support the observed functional patterns in wakefulness and anesthesia? Our results show that during anesthesia, the brain is characterized by a single dominant brain pattern with short range connections. Furthermore, we observed from our results that during anaesthesia the brain is characterized by minimal temporal exploration of the different brain configurations. Conversely, in awake state we observed the opposite. The brain pattern with long range connections are frequent in wakefulness. In addition, wakefulness is characterized by somewhat frequent temporal exploration of brain states. Our results show that analysis of functional connectivity patterns can be a useful tool for identifying specific and generalizable fingerprints of wakefulness and anaesthesia

Capire come modellare l'attività del cervello a riposo, resting state, è il primo passo necessario per avvicinarsi a una reale comprensione della dinamica cerebrale. Sperimentalmente si osserva che, quando il cervello non è soggetto a stimoli esterni, particolari reti di regioni cerebrali presentano un'attività neuronale superiore alla media. Nonostante gli sforzi dei ricercatori, non è ancora chiara la relazione che sussiste tra le connessioni strutturali e le connessioni funzionali del sistema cerebrale a riposo, organizzate nella matrice di connettività funzionale. Recenti studi sperimentali mostrano la natura non stazionaria della connettività funzionale in disaccordo con i modelli in letteratura. Il modello implementato nella presente tesi per simulare l'evoluzione temporale del network permette di riprodurre il comportamento dinamico della connettività funzionale. Per la prima volta in questa tesi, secondo i lavori a noi noti, un modello di resting state è implementato nel cervello di un topo. Poco è noto, infatti, riguardo all'architettura funzionale su larga scala del cervello dei topi, nonostante il largo utilizzo di tale sistema nella modellizzazione dei disturbi neurologici. Le connessioni strutturali utilizzate per definire la topologia della rete neurale sono quelle ottenute dall'Allen Institute for Brain Science. Tale strumento fornisce una straordinaria opportunità per riprodurre simulazioni realistiche, poiché, come affermato nell'articolo che presenta tale lavoro, questo connettoma è il più esauriente disponibile, ad oggi, in ogni specie vertebrata. I parametri liberi del modello sono stati scelti in modo da inizializzare il sistema nel range dinamico ottimale per riprodurre il comportamento dinamico della connettività funzionale. Diverse considerazioni e misure sono state effettuate sul segnale BOLD simulato per meglio comprenderne la natura. L'accordo soddisfacente fra i centri funzionali calcolati nel network cerebrale simulato e quelli ottenuti tramite l'indagine sperimentale di Mechling et al., 2014 comprovano la bontà del modello e dei metodi utilizzati per analizzare il segnale simulato.

Il est possible d’aborder l'organisation fonctionnelle du cerveau en modélisant le cerveau comme un système dynamique, ce qui permet d'étudier comment l'architecture fonctionnelle dépend du squelette structurel sous-jacent. En combinant approches expérimentales et théoriques chez la souris, nous avons étudié de façon systématique comment le connectome structurel contraint le connectome fonctionnel.Dans une première partie nous avons généralisé à la souris le logiciel open source The Virtual Brain (Sanz-Leon et al., 2013, Melozzi et al., 2017).En utilisant les données d'IRM de diffusion (IRMd) de 19 souris, nous avons virtualisé leur cerveau pour générer un signal BOLD in silico que nous avons comparé aux données d'IRM fonctionnelle enregistrées chez les mêmes souris pendant la veille passive. Nous montrons que les prédictions du modèle basé sur le connectome dépendent strictement de la structure du réseau (Melozzi et al., en révision). Nous démontrons que les variations individuelles définissent une empreinte structurelle spécifique ayant un impact direct sur l'organisation fonctionnelle des cerveaux individuels. Ces résultats démontrent l’existence d’un lien causal entre le connectome structurel et le connectome fonctionnel.Finalement, nous confirmons certaines de nos conclusions en utilisant l’approche inverse: nous avons étudié s’il était possible de déduire le connectome structurel à partir du connectome fonctionnel en utilisant la méthode d'inférence Bayésienne (Melozzi et al., en préparation).Nos résultats aux futures études testant la causalité entre structure et fonction, au niveau du cerveau entier individuel, en conditions physiologique et pathologique
The connectome-based model approach aims to understand the functional organization of the brain by modeling the brain as a dynamical system and then studying how the functional architecture rises from the underlying structural skeleton. In this thesis, taking advantage of mice studies, we investigated the informative content of different structural features in explaining the functional ones.First, we extended the open-source software TVB (Leon et al., 2013), originally designed for humans, to accommodate the connectome-based model approach in mice (Melozzi et al., 2017).Using diffusionMRI (dMRI) data from 19 mice, we virtualised their brains to generate in silico fMRI that we compared to functional MRI data recorded in the same mice during passive wakefulness. We show that the predictions of the connectome-based model strictly depend on the structure of the underlying network (Melozzi et al., under review). We demonstrate that individual variations define a specific structural fingerprint with a direct impact upon the functional organization of individual brains. Comparing the predictive power of the tracer-based and the dMRI-based connectome we identify how the limitations of the dMRI method restrict our comprehension of the structural-functional relation. Together, these results strongly support the existence of a causal link between the structural and the functional connectomes.Finally, we infer the connectome form resting state dynamics by inferring the structural connectome using the Bayesian inference (Melozzi et al., in prep).Our results pave the way to future studies focusing on the causal link between structure and function at the individual brain level

Complex network models of functional connectivity have emerged as a paradigm shift in brain mapping over the past decade. Despite significant attention within the neuroimaging and cognitive neuroscience communities, these approaches have hitherto not been extensively explored in neurosurgery. The aim of this thesis is to investigate how the field of connectomics can contribute to understanding the effects of focal brain lesions and to functional brain mapping in neurosurgery. This datasets for this thesis include a clinical population with focal brain tumours and a cohort focused on healthy adolescent brain development. Multiple network analyses of increasing complexity are performed based upon resting state functional MRI. In patients with focal brain tumours, the full complement of resting state networks were apparent, while also suggesting putative patterns of network plasticity. Connectome analysis was able to identify potential signatures of node robustness and connections at risk that could be used to individually plan surgery. Focal lesions induced the formation of new hubs while down regulating previously established hubs. Overall these data are consistent with a dynamic rather than a static response to the presence of focal lesions. Adolescent brain development demonstrated discrete dynamics with distinct gender specific and age-gender interactions. Network architecture also became more robust, particularly to random removal of nodes and edges. Overall these data provide evidence for the early vulnerability rather than enhanced plasticity of brain networks. In summary, this thesis presents a combined analysis of pathological and healthy development datasets focused on understanding the functional effects of focal brain lesions at a network level. The coda serves as an introduction to a forthcoming study, known as Connectomics and Electrical Stimulation for Augmenting Resection (CAESAR), which is an evolution of the results and methods herein.

Human structural and functional brain architecture is increasingly studied by applying the mathematical framework of complex networks to data from magnetic resonance imaging. Connections (edges) in such brain networks are commonly constructed using correlations of features between pairs of brain regions, such as regional morphology (across participants) or neurophysiological time series (within participants). Subsequent analyses frequently focus on summary network statistics calculated using the strongest correlations, but often neglect potential underlying shifts within the correlation distribution. This thesis presents methods for the construction and analysis of correlation-derived structural and functional brain networks, focusing on the implications of changes within the correlation distribution. First, schizophrenia is considered as an example disease which is known to present a reduction in mean correlation between regional neurophysiological time series. Previous studies reported increased network randomisation in schizophrenia, but these results may have been driven by inclusion of a greater number of noisy edges in patients’ networks, based on retention of a fixed proportion of the strongest edges during network thresholding. Here, a novel probabilistic thresholding procedure is applied, based on the realisation that the strongest edges are not necessarily most likely to be true following adjustment of edge probabilities for effects of participant in-scanner motion. Probabilistically thresholded functional networks show decreased randomness, and increased consistency across participants. Further, applying probabilistic thresholding eliminates increased network randomisation in schizophrenia, supporting the hypothesis that previously reported group differences originated in the application of standard thresholding approaches to patient networks with decreased functional correlations. Subsequently, healthy adolescent development is studied, to help understand the frequent emergence of psychiatric disorders in this period. Importantly, both structural and functional brain networks undergo maturational shifts in correlation distribution over adolescence. Due to reliance of structural correlation networks on a group of subjects, previous studies of adolescent structural network development divided groups into discrete age-bins. Here, a novel sliding-window method is used to describe adolescent development of structural correlation networks in a continuous manner. Moreover, networks are probabilistically thresholded by retaining edges that are most consistent across bootstrapped samples of participants, leading to clearer maturational trajectories. These structural networks show non-linear trajectories of adolescent development driven by changes in association cortical areas, compatible with a developmental process of pruning combined with consolidation of surviving connections. Robustness of the results is demonstrated using extensive sensitivity analyses. Finally, adolescent developmental changes in functional network architecture are described, focusing on the characterisation of unthresholded (fully weighted) networks. The distribution of functional correlations presents a non-uniform shift over adolescence. Initially strong cortical connections to primary sensorimotor areas further strengthen into adulthood, whereas association cortical and subcortical edges undergo a subtler reorganisation of functional connectivity. Furthermore, individual subcortical regions show distinct maturational profiles. Patterning of maturation according to known functional systems is affirmed by partitioning regions developing at similar rates into maturational modules. Taken together, this thesis comprises novel methods for the characterisation of disease-related and normative developmental changes in structural and functional correlation brain networks. These methods are generalizable to a wide range of scenarios, beyond the specific disease and developmental age-ranges presented herein.

MEG and fMRI offer complementary insights into connected human brain function. Evidence from the use of both techniques in the study of networked activity indicates that functional connectivity reflects almost every measurable aspect of human reality, being indicative of ability and deteriorating with disease. Functional network analyses may offer improved prediction of dysfunction and characterisation of cognition. Three factors holding back progress are the difficulty in synthesising information from multiple imaging modalities; a need for accurate modelling of connectivity in individual subjects, not just average effects; and a lack of scalable solutions to these problems that are applicable in a big-data setting. I propose two methodological advances that tackle these issues. A confound to network analysis in MEG, the artificial correlations induced across the brain by the process of source reconstruction, prevents the transfer of connectivity models from fMRI to MEG. The first advance is a fast correction for this confound, allowing comparable analyses to be performed in both modalities. A comparative study demonstrates that this new approach for MEG shows better repeatability for connectivity estimation, both within and between subjects, than a wide range of alternative models in popular use. A case-study analysis uses both fMRI and MEG recordings from a large dataset to determine the genetic basis for functional connectivity in the human brain. Genes account for 20% - 65% of the variation in connectivity, and outweigh the influence of the developmental environment. The second advance is a Bayesian hierarchical model for sparse functional networks that is applicable to both modalities. By sharing information over a group of subjects, more accurate estimates can be constructed for individuals' connectivity patterns. The approach scales to large datasets, outperforms state-of-the-art methods, and can provide a 50% noise reduction in MEG resting-state networks.

L'idée que l'intelligence s’appuie non seulement sur des régions spécifiques du cerveau, mais également sur des réseaux cérébraux efficaces s’est récemment affirmée. En effet, on pense que l'organisation du cerveau humain repose sur des réseaux complexes et dynamiques dans lesquels la communication entre les régions cérébrales garantit un transfert efficace d'informations. Ces concepts nous ont amené à explorer les bases neurales de l'intelligence en combinant des techniques avancées d'IRM et la théorie des graphes. D'un côté, les techniques avancées d'IRM, telles que l'IRM fonctionnelle au repos (IRMf-rs) et l'IRM par diffusion (IRMd), permettent d'explorer respectivement la connectivité cérébrale fonctionnelle et structurale, tandis que la théorie des graphes permettent la caractérisation des propriétés des réseaux à différentes échelles, grâce à des métriques globales et locales. L'objectif de cette thèse est de caractériser la topologie des réseaux cérébraux fonctionnels et structurels chez les enfants et les adultes avec un quotient intellectuel supérieur (HIQ) par rapport aux sujets de niveau standard (SIQ). Premièrement, nous avons concentré notre attention sur une population d’enfants présentant différentes caractéristiques cognitives. Deux profils HIQ, à savoir homogène (Hom-HIQ) et hétérogène HIQ (Het-HIQ), ont été définis sur la base d'observations cliniques et de sous-tests du quotient intellectuel (QI). En utilisant des techniques d’IRMf-rs, nous avons examiné la topologie du réseau fonctionnel par « l’indice de rupture de nœud ». Nous avons trouvé des différences topologiques significatives dans les propriétés d'intégration et de ségrégation des réseaux chez les enfants HIQ par rapport aux enfants SIQ, pour le graphe cérébral entier, pour chaque graphe hémisphérique et pour la connectivité homotopique. De plus, ces changements de topologie étaient plus prononcés dans le sous-groupe Het-HIQ. Enfin, nous avons trouvé des corrélations significatives entre les changements des métriques de graphes et le QI total et d’autres indices du QI. Ces résultats ont démontré pour la première fois que les deux profils HIQ sont liés à une organisation différente du substrat neuronal. Ensuite, la connectivité structurale du réseau cérébral, mesurée par IRMd chez l’ensemble des enfants HIQ, est significativement différente de celle des enfants SIQ. Nous avons également aussi de fortes corrélations entre la densité des réseaux cérébraux des enfants et leurs scores d'intelligence. De plus, plusieurs corrélations ont été trouvées entre les métriques de graphe d'intégration suggérant que les performances de l'intelligence peuvent être liées à une organisation homogène des réseaux. Ces résultats ont démontré que le substrat neuronal de l'intelligence repose sur une microarchitecture de la substance blanche de forte densité et sur une organisation homogène des réseaux. Cette population a finalement été étudiée par IRMf avec une tâche de mémorisation de mots. Des changements significatifs ont été observés entre les groupes HIQ et SIQ. Cette étude confirme notre hypothèse selon laquelle les deux profils HIQ sont caractérisés par une activité cérébrale différente, avec un effet plus prononcé chez les enfants Het-HIQ. Enfin, nous avons étudié la connectivité fonctionnelle et structurale dans une population d’adultes HIQ. Nous avons trouvé plusieurs corrélations entre les métriques de graphe et les autres indices du QI. De même que pour la population d’enfants, les capacités cognitives élevées des adultes sont corrélées à une organisation homogène des réseaux structurels et fonctionnels et une modularité réduite. En conclusion, on a démontré que la sensibilité des métriques de graphes basées sur des techniques 'IRM avancées et de connectivité, telles que l’IRMf-rs et l'IRMd, était très utile pour mieux caractériser les réseaux cérébraux des enfants et des adultes, ainsi que pour distinguer différents profils d'intelligence chez les enfants
The idea that intelligence is embedded not only in specific brain regions, but also in efficient brain networks has grown up. Indeed, human brain organization is believed to rely on complex and dynamic networks in which the communication between cerebral regions guarantees an efficient transfer of information. These recent concepts have led us to explore the neural bases of intelligence using both advanced MRI techniques in combination with graph analysis. On one hand, advanced MRI techniques, such as resting-state functional MRI (rs-fMRI) and diffusion MRI (dMRI) allow the exploration of respectively the functional and the structural brain connectivity while on the other hand, graph theory models allow the characterization of brain networks properties at different scales, thanks to global and local metrics. The aim of this thesis is to characterize the topology of functional and structural brain networks in children and in adults with an intelligence quotient higher (HIQ) than standard levels (SIQ). First, we focused our attention on a children population with different cognitive characteristics. Two HIQ profiles, namely homogeneous (Hom-HIQ) and heterogeneous HIQ (Het-HIQ), have been defined based on clinical observations and Intelligence Quotient (IQ) sub-tests. Using resting-state fMRI techniques, we examined the functional network topology changes, estimating the "hub disruption index", in these two HIQ profiles. We found significant topological differences in the integration and segregation properties of brain networks in HIQ compared to SIQ children, for the whole brain graph, for each hemispheric graph, and for the homotopic connectivity. These brain networks changes resulted to be more pronounced in Het-HIQ subgroup. Finally, we found significant correlations between the graph networks’ changes and the full-scale IQ, as well as some intelligence subscales. These results demonstrated for the first time, that different HIQ profiles are related to a different neural substrate organization. Then, the structural brain network connectivity, measured by dMRI in all HIQ children, were significantly different than in SIQ children. Also, we found strong correlations between the children brain networks density and their intelligence scores. Furthermore, several correlations were found between integration graph metrics suggesting that intelligence performances are probably related to a homogeneous network organization. These findings demonstrated that intelligence neural substrate is based on a strong white matter microarchitecture of the major fiber-bundles and a well-balanced network organization between local and global scales. This children population was finally studied using a memory-word task of fMRI. Significant changes were observed between both HIQ and SIQ groups. This study confirms our hypothesis that both HIQ profiles are characterized by a different brain activity, with stronger evidences in Het-HIQ children. Finally, we investigated both functional and structural connectivity in a population of adults HIQ. We found several correlations between graph metrics and intelligence sub-scores. As well as for the children population, high cognitive abilities of adults seem to be related brain structural and functional networks organization with a decreased modularity. In conclusion, the sensitivity of graph metrics based on advanced MRI techniques, such as rs-fMRI and dMRI, was demonstrated to be very helpful to provide a better characterization of children and adult HIQ, and further, to distinguish different intelligence profiles in children

This dissertation introduces a new approach for assessing the effects of pediatric epilepsy on the language connectome. Two novel data-driven network construction approaches are presented. These methods rely on connecting different brain regions using either extent or intensity of language related activations as identified by independent component analysis of fMRI data. An auditory description decision task (ADDT) paradigm was used to activate the language network for 29 patients and 30 controls recruited from three major pediatric hospitals. Empirical evaluations illustrated that pediatric epilepsy can cause, or is associated with, a network efficiency reduction. Patients showed a propensity to inefficiently employ the whole brain network to perform the ADDT language task; on the contrary, controls seemed to efficiently use smaller segregated network components to achieve the same task. To explain the causes of the decreased efficiency, graph theoretical analysis was carried out. The analysis revealed no substantial global network feature differences between the patient and control groups. It also showed that for both subject groups the language network exhibited small-world characteristics; however, the patient’s extent of activation network showed a tendency towards more random networks. It was also shown that the intensity of activation network displayed ipsilateral hub reorganization on the local level. The left hemispheric hubs displayed greater centrality values for patients, whereas the right hemispheric hubs displayed greater centrality values for controls. This hub hemispheric disparity was not correlated with a right atypical language laterality found in six patients. Finally it was shown that a multi-level unsupervised clustering scheme based on self-organizing maps, a type of artificial neural network, and k-means was able to fairly and blindly separate the subjects into their respective patient or control groups. The clustering was initiated using the local nodal centrality measurements only. Compared to the extent of activation network, the intensity of activation network clustering demonstrated better precision. This outcome supports the assertion that the local centrality differences presented by the intensity of activation network can be associated with focal epilepsy.

Orientador: Gabriela Castellano
Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Ciências Médicas
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Resumo: O conectoma cerebral refere-se ao mapeamento dos circuitos neurais com os objetivos de 1) identificar regiões que dão suporte às atividades mentais e comportamentais, e 2) detectar alterações nesses circuitos que levam a distúrbios de ordem psiquiátrica e neurológica. Na prática, os estudos de conectoma cerebral consistem na integração de técnicas multimodais de imageamento como ressonância magnética (RM), eletroencefalograma (EEG) e magnetoencefalograma (MEG) com o intuito de estimar os tipos e os níveis de conexão entre regiões cerebrais remotas. Essa "conectividade" entre regiões cerebrais é geralmente classificada em três tipos: anatômica, funcional e efetiva. No presente trabalho, as técnicas de conectividade, usando dados de MR, foram aplicadas na comparação de grupos saudáveis e patológicos. Pela técnica de conectividade anatômica observou-se anomalias na substância branca de pacientes com mutação no gene SPG11. Essa anomalias foram detectadas através da redução da anisotropia fracional (FA) e aumento da difusividade média (MD), difusividade radial (RD) e difusividade axial (AD) em regiões subcorticais dos lobos temporal e frontal, bem como no giro do cíngulo, cuneus striatum, corpo caloso e tronco cerebral. Tais achados indicam que o dano neuronal é mais difuso do que indicava a literatura. Um segundo estudo de conectividade anatômica demonstrou que esses índices de difusividade não foram robustos para diferenciar idosos com e sem diagnóstico de depressão indicando a necessidade de avanços na formulação de novos índices com maior sensibilidade. A técnica de conectividade funcional foi empregada em três estudos. No primeiro, observou-se que pacientes com epilepsia de lobo temporal medial unilateral apresentam redução da conectividade funcional durante a execução de tarefas de memória verbal e visual. Essa redução foi predominantemente ipslateral à lesão e associada ao material-específico utilizado no teste de memória. No segundo estudo, verificou-se uma redução dos padrões de conectividade funcional hipotalâmica em sujeitos obesos e a sua parcial elevação após a cirurgia bariátrica concomitantemente à redução de indicadores bioquímicos de inflamação. No terceiro estudo, observou-se que pacientes com doença de Alzheimer apresentaram elevação dos níveis de conectividade funcional na rede saliente (Salience Network) e redução na rede de modo padrão (Default-mode network). Adicionalmente, verificou-se nos pacientes a correlação positiva da síndrome hiperativa com os níveis de conectividade funcional no cíngulo anterior e em áreas da ínsula direita. O conjunto desses resultados ilustra um possível significado clínico para futuro diagnóstico e tratamento da doença de Alzheimer. Pela técnica de conectividade efetiva observou-se que em função do envelhecimento sadio há uma mudança dos parâmetros de conectividade durante a codificação de palavras com conteúdo emocional. A influência do hipocampo sobre a amígdala ipslateral é reduzida nos sujeitos mais velhos enquanto a influência da amígdala direita sobre o hipocampo direito é elevada. Tais achados reforçam a tese da ininterrupta plasticidade etária e da dinâmica cerebral normal. Essa mesma técnica foi também empregada para demonstrar os diferentes padrões de influência entre os lobos frontal e temporal de pacientes com ELTM esquerda e sujeitos controle. Encontrou-se alteração nos padrões de conectividade efetiva dos pacientes, indicando que estes podem ser potenciais biomarcadores para a epilepsia
Abstract: Connectome refers to the neural circuitry mapping aiming to identify brain regions that support mental and behavioral functions as well as to detect circuit changes that are linked to psychiatric or neurologic disorders. In practice, connectome studies link several neuroimaging approaches such as MRI, EEG and MEG by means of the estimation of connections among remote brain regions. This "connectivity" among brain regions is usually classified as anatomic, functional or effective. In this work, the technique of connectivity, using MR data, was applied to compare healthy and pathological groups. By means of the anatomical connectivity abnormalities in the white matter of patients with SPG11 mutation were observed. These abnormalities were expressed as the reduction of the levels of fractional anisotropy (FA) and the increase in mean (MD) and radial diffusivities (RD) in sub-cortical regions of temporal and frontal lobe as well as in cingulated gyrus, cuneus, striatum, corpus callosum and brainstem. These findings suggest that neuronal damage/dysfunction is more widespread than previously recognized in this condition. Another anatomical connectivity study showed that such indices of diffusivity were not robust to statistically differentiate between old subjects with and without depression. This lacking on finding differences between both groups indicates that new indices of diffusivity have to emerge in order to provide complementary information about brain subtle microstructures. Functional connectivity was applied to three studies. In the first study, it was observed that patients with unilateral medial temporal lobe epilepsy presented lower levels of functional connectivity during visual or verbal memory tasks. Such reduction was ipsilateral to the side of the lesion and associated to the specific-material used in the memory task. In the second work, the levels of functional connectivity were reduced in hypothalamic regions of obese patients but a partial reversibility of hypothalamic dysfunction was observed after bariatric surgery. In the third, patients with Alzheimer disease presented higher values of functional connectivity in the salience network and a reduction of connectivity values in the default-mode network. Also in these patients, significant correlations between the levels of hyperactivity syndrome and the salience network were observed in the anterior cingulate cortex and right insula areas. These results indicate the potential clinical significance of resting state alterations in future diagnosis and therapy of Alzheimer disease. The effective connectivity approaches demonstrated that old and young subjects have significant differences when encoding words with emotional contents. The influence of the hippocampus on the ipsilateral amygdale was lower for older subjects whereas the influence of the right amygdale on the right hippocampus was increased for these subjects. These findings suggest that brain plasticity also happens as function of age. The same approach was used to estimate the influence from frontal to temporal lobes in patients with left MTLE compared to healthy subjects. The patterns of effective connectivity were changed in patients and may be potentially considered as biomarkers for epilepsy
Doutorado
Neurociencias
Doutor em Ciências

El cerebro está constituido por numerosos elementos que se encuentran interconectados de forma masiva y organizados en módulos que forman redes jerárquicas. Ciertas patologías cerebrales, como la enfermedad de Alzheimer y el trastorno por consumo de alcohol, se consideran el resultado de efectos en cascada que alteran la conectividad cerebral. La presente tesis tiene como objetivo principal la aplicación de las técnicas de análisis de la ciencia de redes para el estudio de las redes estructurales y funcionales en el cerebro, tanto en un estado control como en un estado patológico. Así, en el primer estudio de la presente tesis se examina la relación entre la conectividad estructural y funcional en la corteza cerebral de la rata. Se lleva a cabo un análisis comparativo entre las conexiones estructurales en la corteza cerebral de la rata y los valores de correlación calculados sobre las mismas regiones. La información acerca de la conectividad estructural se ha obtenido a partir de estudios previos, mientras que la conectividad funcional se ha calculado a partir de imágenes de resonancia magnética funcional. Determinadas propiedades topológicas, y extraídas de la conectividad estructural, se relacionan con la organización modular de las redes funcionales en estado de reposo. Los resultados obtenidos en este primer estudio demuestran que la conectividad estructural y funcional cortical están altamente relacionadas entre sí. Estudios recientes sugieren que el origen de la enfermedad de Alzheimer reside en un mecanismo en el cual depósitos de ovillos neurofibrilares y placas de beta-amiloide se acumulan en ciertas regiones cerebrales, y tienen la capacidad de diseminarse por el cerebro actuando como priones. En el segundo estudio de la presente tesis se investiga si las redes estructurales que se generan con la técnica de resonancia magnética ponderada en difusión podrían ser de utilidad para el diagnóstico de la pre-demencia causada por la enfermedad de Alzheimer. Mediante el uso de imágenes procedentes de la base de datos ADNI, se aplican técnicas de aprendizaje máquina con el fin de identificar medidas de centralidad que se encuentran alteradas en la demencia. En la segunda parte del estudio, se utilizan imágenes procedentes de la base de datos NKI para construir un modelo matemático que simule el proceso de envejecimiento normal, así como otro modelo que simule el proceso de desarrollo de la enfermedad. Con este modelado matemático, se pretende estimar la etapa más temprana que está asociada con la demencia. Los resultados obtenidos de las simulaciones sugieren que en etapas tempranas de la enfermedad de Alzheimer se producen alteraciones estructurales relacionados con la demencia. La cuantificación de la relación estadística entre las señales BOLD de diferentes regiones puede informar sobre el estado funcional cerebral característico de enfermedades neurológicas y psiquiátricas. En el tercer estudio de la presente tesis se estudian las alteraciones en la conectividad funcional que tienen lugar en ratas dependientes del consumo de alcohol cuando se encuentran en estado de reposo. Para ello, se ha aplicado el método NBS. El análisis de este modelo de rata revela diferencias estadísticamente significativas en una subred de regiones cerebrales que están implicadas en comportamientos adictivos. Por lo tanto, estas estructuras cerebrales podrían ser el foco de posibles dianas terapéuticas. La tesis aporta tres innovadoras contribuciones para entender la conectividad cerebral bajo la perspectiva de la ciencia de redes, tanto en un estado control como en un estado patológico. Los resultados destacan que los modelos basados en las redes cerebrales permiten esclarecer la relación entre la estructura y la función en el cerebro. Y quizás más importante, esta perspectiva de red tiene aplicaciones que se podrían trasladar a la práctica clínica.
The brain is composed of massively connected elements arranged into modules that form hierarchical networks. Experimental evidence reveals a well-defined connectivity design, characterized by the presence of strategically connected core nodes that critically contribute to resilience and maintain stability in interacting brain networks. Certain brain pathologies, such as Alzheimer's disease and alcohol use disorder, are thought to be a consequence of cascading maladaptive processes that alter normal connectivity. These findings have greatly contributed to the development of network neuroscience to understand the macroscopic organization of the brain. This thesis focuses on the application of network science tools to investigate structural and functional brain networks in health and disease. To accomplish this goal, three specific studies are conducted using human and rodent data recorded with MRI and tracing technologies. In the first study, we examine the relationship between structural and functional connectivity in the rat cortical network. Using a detailed cortical structural matrix obtained from published histological tracing data, we first compare structural connections in the rat cortex with their corresponding spontaneous correlations extracted empirically from fMRI data. We then show the results of this comparison by relating structural properties of brain connectivity to the functional modularity of resting-state networks. Specifically, we study link reciprocity in both intra- and inter-modular connections as well as the structural motif frequency spectrum within functionally defined modules. Overall, our results provide further evidence that structural connectivity is coupled to and shapes functional connectivity in cortical networks. The pathophysiological process of Alzheimer's disease is thought to begin years before clinical decline, with evidence suggesting pahtogenic seeding and subsequent prion-like spreading processes of neurofibrillary tangles and amyloid plaques. In the second study of this thesis, we investigate whether structural brain networks as measured with dMRI could serve as a complementary diagnostic tool in prodromal dementia. Using imaging data from the ADNI database, we first aim to implement machine learning techniques to extract centrality features that are altered in Alzheimer's dementia. We then incorporate data from the NKI database and create dynamical models of normal aging and Alzheimer's disease to estimate the earliest detectable stage associated with dementia in the simulated disease progression. Our model results suggest that changes associated with dementia begin to manifest structurally at early stages. Statistical dependence measures computed between BOLD signals can inform about brain functional states in studies of neurological and psychiatric disorders. Furthermore, its non-invasive nature allows comparable measurements between clinical and animal studies, providing excellent translational capabilities. In the last study, we apply the NBS method to investigate alterations in the resting-state functional connectivity of the rat brain in a PD state, an established animal model of clinical relevant features in alcoholism. The analysis reveal statistically significant differences in a connected subnetwork of structures with known relevance for addictive behaviors, hence suggesting potential targets for therapy. This thesis provides three novel contributions to understand the healthy and pathological brain connectivity under the perspective of network science. The results obtained in this thesis underscore that brain network models offer further insights into the structure-function coupling in the brain. More importantly, this network perspective provides potential applications for the diagnosis and treatment of neurological and psychiatric disorders.
El cervell està constituït per nombrosos elements que es troben interconnectats de forma massiva i organitzats en mòduls que formen xarxes jeràrquiques. Certes patologies cerebrals, com la malaltia d'Alzheimer i el trastorn per consum d'alcohol, es consideren el resultat d'efectes en cascada que alteren la connectivitat cerebral. La present tesi té com a objectiu principal l'aplicació de les tècniques d'anàlisi de la ciència de xarxes per a l'estudi de les xarxes estructurals i funcionals en el cervell, tant en un estat control com en un estat patològic. Així, en el primer estudi de la present tesi s'examina la relació entre la connectivitat estructural i funcional en l'escorça cerebral de la rata. Es du a terme una anàlisi comparativa entre les connexions estructurals en l'escorça cerebral de la rata i els valors de correlació calculats sobre les mateixes regions. La informació sobre la connectivitat estructural s'ha obtingut a partir d'estudis previs, mentre que la connectivitat funcional s'ha calculat a partir d'imatges de ressonància magnètica funcional. Determinades propietats topològiques, i extretes de la connectivitat estructural, es relacionen amb l'organització modular de les xarxes funcionals en estat de repòs. Els resultats obtinguts en este primer estudi demostren que la connectivitat estructural i funcional cortical estan altament relacionades entre si. Estudis recents suggereixen que l'origen de la malaltia d'Alzheimer resideix en un mecanisme en el qual depòsits d'ovulets neurofibrilars i plaques de beta- miloide s'acumulen en certes regions cerebrals, i tenen la capacitat de disseminar-se pel cervell actuant com a prions. En el segon estudi de la present tesi s'investiga si les xarxes estructurals que es generen amb la tècnica de la imatge per ressonància magnètica ponderada en difusió podrien ser d'utilitat per al diagnòstic de la predemència causada per la malaltia d'Alzheimer. Per mitjà de l'ús d'imatges procedents de la base de dades ADNI, s'apliquen tècniques d'aprenentatge màquina a fi d'identificar mesures de centralitat que es troben alterades en la demència. En la segona part de l'estudi, s'utilitzen imatges procedents de la base de dades NKI per a construir un model matemàtic que simule el procés d'envelliment normal, així com un altre model que simule el procés de desenrotllament de la malaltia. Amb este modelatge matemàtic, es pretén estimar l'etapa més primerenca que està associada amb la demència. Els resultats obtinguts de les simulacions suggereixen que en etapes primerenques de la malaltia d'Alzheimer es produeixen alteracions estructurals relacionats amb la demència. La quantificació de la relació estadística entre els senyals BOLD de diferents regions pot informar sobre l'estat funcional cerebral característic de malalties neurològiques i psiquiàtriques. A més, a causa de la seua naturalesa no invasiva, és possible comparar els resultats obtinguts entre estudis clínics i estudis amb animals d'experimentació. En el tercer estudi de la present tesi s'estudien les alteracions en la connectivitat funcional que tenen lloc en rates dependents del consum d'alcohol quan es troben en estat de repòs. Per a realitzar-ho, s'ha aplicat el mètode NBS. L'anàlisi d'aquest model de rata revela diferències estadísticament significatives en una subxarxa de regions cerebrals que estan implicades en comportaments addictius. Per tant, estes estructures cerebrals podrien ser el focus de possibles dianes terapèutiques. La tesi aporta tres innovadores contribucions per a entendre la connectivitat cerebral davall la perspectiva de la ciència de xarxes, tant en un estat control com en un estat patològic. Els resultats destaquen que els models basats en les xarxes cerebrals permeten aclarir la relació entre l'estructura i la funció en el cervell. I potser més important, esta perspectiva de xarxa té aplicacions que es podrien traslladar a la pràcti
Díaz Parra, A. (2018). A network science approach of the macroscopic organization of the brain: analysis of structural and functional brain networks in health and disease [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/106966
TESIS

Si les régions cérébrales du langage ont étélargement explorées grâce à l’IRM fonctionnelle (IRMf) et la stimulation électrique directe (SED)peropératoire, leur connectivité reste encore incomplètement documentée. Il n’est pas seulement débattuquels faisceaux de SB contribuent au langage, mais également quelle est leur anatomie précise et leur rôlefonctionnel spécifique. Une meilleure compréhension du connectome du langage est requise pourdiminuer la morbidité postopératoire en neurochirurgie et développer de nouveaux traitements cibléspour la rééducation des aphasies. Notre objectif était de cartographier structurellement etfonctionnellement, in vivo, la connectivité du langage. Dans une première étude préclinique portant sur 2Oadultes sains, nous avons combiné des informations structurelles axonales révélées par la tractographieavec des informations fonctionnelles corticales dérivées de l’IRMf (tâche de lecture compréhensive). Huitfaisceaux de SB ont été explorés —i.e. faisceau arqué, faisceau longitudinal supérieur, faisceau frontooccipitalinférieur, faisceau unciné, faisceau longitudinal inférieur, faisceau longitudinal moyen, faisceauoperculo-prémoteur, faisceau frontal transverse—, dont le rôle fonctionnel a été analysé en recherchantune connexion entre leurs terminaisons corticales et les activations IRMf. Les caractéristiquesanatomiques des faisceaux (i.e. volume, longueur, terminaisons corticales), leurs asymétries interhémisphériqueset leurs variations interindividuelles ont été colligées. Ce protocole a permis deconstruire le connectome du langage et d’étudier en détails son organisation structurelle macroscopique.Dans une seconde partie, ces données ont été transposées à la clinique pour le traitement chirurgical depatients souffrant de tumeurs cérébrales (gliomes) en régions du langage. Pendant la résection tumorale,des images de tractographie intégrées à un système de neuronavigation ont été systématiquementcombinées à la SED au cours d’un test de dénomination orale d’images. Ce protocole opératoire a permisd’optimiser les résultats chirurgicaux en termes de qualité d’exérèse et de préservation du langage, et aconstitué une opportunité unique d’étudier en temps réel les corrélations structure – fonction. Encouplant la localisation anatomique précise où chaque SED a été délivrée —obtenue grâce aux images detractographie naviguées— et la sémiologie des paraphasies induites par la SED —colligée par unorthophoniste présent au bloc opératoire—, nous avons déterminé le rôle spécifique de 5 faisceaux tantcortico-corticaux (faisceau arqué, faisceau fronto-occipital inférieur, faisceau frontal transverse) quecortico-sous-corticaux (fibres prémotrices orofaciales, faisceau fronto-striatal) dans différentes souscomposantesdu langage, i.e. traitement phonologique, traitement sémantique, contrôle moteur,planification articulatoire, contrôle exécutif/cognitif de la réponse verbale. Considérés de façon globale,nos résultats permettent d’envisager une meilleure compréhension de l’organisation anatomofonctionnelledes réseaux cérébraux du langage. Au-delà de l’intérêt scientifique, la possibilité deconstruire le connectome du langage spécifique à chaque individu ouvre la voie vers d’importantesapplications en neurochirurgie, dans une perspective de médecine personnalisée. Aujourd’hui, la chirurgiedes tumeurs cérébrales guidée par l’image. Demain, le développement de nouveaux traitements pour larééducation des aphasies, e.g. la déposition ciblée d’agents pharmacologiques, de cellules souches ou deneuromodulations, interagissant directement avec la connectivité résiduelle épargnée par la lésion
The langage connectome is defined as the neuronal networks that subserve languagefunctions. Anatomically, it comprises specialized cortical areas and modulatory subcortical areas (i.e. deepgray nuclei and cerebellum), as well as their interconnections trough white matter (WM) fascicles.Although brain regions involved in language have been largely explored thanks to functional MRI (fMRI)and intraoprative electrical stimulation (IES), the underlying WM connectivity is still not mastered. It isnot only unknown which WM fascicles specifically contribute to language, but there is also much debateabout their precise anatomy and the functions they subserve during language processing. Betterunderstanding of the structural and functional organization of the language connectome is requisite toreduce postoperative morbidity in neurosurgery and develop targeted treatments for aphasiarehabilitation. Herein, our objective was to map structurally and functionally, in vivo, the subcorticalconnectivity of language. First, we conducted a preclinical study in 20 healthy subjects, combining DTItractography and fMRI (reading comprehension task) to yield connectivity associated with language. Weexplored 8 WM fascicles that have been proposed as putative candidates for language —i.e. arcuatefascicle, superior longitudinal fascicle, inferior fronto-occipital fascicle, uncinate fascicle, inferiorlongitudinal fascicle, middle longitudinal fascicle, operculopremotor fascicle, frontal aslant tract—, towhich we assigned functionality by tracking their connections to the fMRI-derived clusters. We generateda normative database of anatomical characteristics for each WM fascicle, such as volume, length, corticalterminations and their interhemispheric and interindividual variations. By using this construct, weprovided in explicit details the structural map of the language connectome. Second, this body ofknowledge was transposed to brain tumor surgery. Patients suffering of gliomas located close to languageregions were operated on under local anesthesia (i.e. awake surgery) in order to perform intraoperativelanguage mapping (object naming task). Essential language sites were localized through IES andanatomically characterized thanks to navigated tractography images. This intraoperative protocol allowedmaximum tumor resection while preserving language functions. Furthermore, it gave us a uniqueopportunity to perform reliable, real-time structure – function relationships, determining the role of 5WM fascicles (arcuate fascicle, inferior fronto-occipital fascicle, frontal aslant tract, orofacial premotorfibers, frontostriatal fascicle) in different subcomponents of language, i.e. phonological processing,semantic processing, articulatory planning, motor control and executive/cognitive control of verbalresponse. Globally considered, our results allow a better understanding of the anatomo-functionalorganization of the language network in the human brain. Beyond the scientific interest, the possibility toconstruct the individual (patient-specific) connectome paves the way for major applications inneurosurgery, in the perspective of personalized medicine. Today, the maximum safe resection of braintumors located in eloquent language areas, guided by navigated, multimodal images. Tomorrow, thedevelopment of new treatments for rehabilitation of post-stroke aphasia patients, such as the targeteddelivery of drugs, stem cells, or neuromodulation devices, fitting with the residual functional connectivityspared by the lesion

Image registration methods underpin many analysis techniques in neuroimaging. They are essential in group studies when images of different individuals or different modalities need to be brought into a common reference frame. This thesis explores the potential of brain connectivity- driven alignment and develops surface registration techniques for magnetic resonance imaging (MRI), which is a noninvasive neuroimaging tool for probing function and structure of the human brain. The first part of this work develops a novel surface registration framework, based on free mesh deformations, which aligns cortical and subcortical surfaces by matching structural connectivity patterns derived using probabilistic tractography (diffusion-weighted MRI). Structural, i.e. white matter, connectivity is a good predictor of functional specialisation and structural connectivity-driven registration can therefore be expected to enhance the alignment of functionally homologous areas across subjects. The second part validates developed methods for cortical surfaces. Resting State Networks are used in an innovative way to delineate several functionally distinct regions, which were then used to quantify connectivity-driven registration performance by measuring the inter- subject overlap before and after registration. Consequently, the proposed method is assessed using an independent imaging modality and the results are compared to results from state-of-the-art cortical geometry-driven surface registration methods. A connectivity-driven registration pipeline is also developed for, and applied to, the surfaces of subcortical structures such as the thalamus. It is carefully validated on a set of artificial test examples and compared to another novel surface registration paradigm based on spherical wavelets. The proposed registration pipeline is then used to explore the differences in the alignment of two groups of subjects, healthy controls and Alzheimer's disease patients, to a common template. Finally, we propose how functional connectivity can be used instead of structural connectivity for driving registrations, as well as how the surface-based framework can be extended to a volumetric one. Apart from providing the benefits such as the improved functional alignment, we hope that the research conducted in this thesis will also represent the basis for the development of templates of structural and functional brain connectivity.

Es conocido en la literatura de neuroimagen que las redes cerebrales funcionales reflejan rasgos personales. Estas características individuales, podrían interferir al caracterizar la cognición entendida como la manera en que se coordinan las redes para realizar una tarea, como mantener la atención, recordar, o procesar información visual. Cómo estos aspectos individuales coexisten con mecanismos generales es, por tanto, una pregunta clave en investigación sobre conectividad cerebral. Este trabajo estudia la relación entre marcadores de conectividad específicos tanto de sujetos, como de tareas. Se centra en dos escalas temporales distintas: la variabilidad entre sesiones, y las fluctuaciones rápidas producidas durante una sesión de adquisición. Utilizamos técnicas de machine learning para separar cuantitativamente las contribuciones de información del sujeto y del estado cognitivo a la conectividad. La metodología presentada nos permite extraer aquellas redes representativas de ambas dimensiones, así como profundizar en su evolución, sugiriendo las escalas temporales relevantes en la cognición.
És conegut en la literatura de neuroimatge que les xarxes cerebrals funcionals reflecteixen trets personals. Aquestes característiques individuals podrien interferir en caracteritzar la cognició entesa com la manera en què les xarxes es coordinen per realitzar una tasca, com mantenir l'atenció, recordar o processar informació visual. Cóm aquests aspectes individuals coexisteixen amb mecanismes generals, és, per tant, una pregunta clau en recerca sobre connectivitat cerebral. Aquest treball estudia la relació entre marcadors de connectivitat específics tant de subjectes, com de tasques. Se centra en dues escales temporals: la variabilitat entre sessions, i les fluctuacions ràpides produïdes durant una sessió d'adquisició. Utilitzem tècniques de machine learning per separar quantitativament les contribucions d'informació del subjecte i de l'estat cognitiu a la connectivitat. La metodologia presentada ens permet extreure aquelles xarxes representatives d'ambdues dimensions, així com aprofundir en la seva evolució, suggerint les escales temporals rellevants en la cognició.
There is consistent evidence in the neuroimaging literature that functional brain networks reflect personal traits. Individual specificity may interfere with the characterization of cognition, in terms of coordination of brain networks to perform a task, such as sustained attention, memory retrieval or visual information processing. How individual traits coexist with invariant mechanisms is, therefore, a key question in brain connectivity research. This work aims to examine the relationship between subject- and task-specific connectivity signatures. It focuses on two different timescales: day-to-day variability and faster fluctuations exhibited within a scanning session. We adopt a machine learning approach to quantitatively disentangle the contribution of subject information and cognitive state to the connectivity patterns. The proposed methodology allows us to extract the specific brain networks that support each of the two dimensions, as well as to delve into their changes over time, suggesting the relevant timescales for cognition.

Every individual is born with different natural competencies that can be honed by both voluntary and involuntary environmental stimuli. The response our genotype decides to make, if any, towards those stimuli, determines how well our competencies develop. Each person’s coding and variations of genes will result in unique qualities in their phenotype, or physical structure. As a result, a person has various traits that are displayed through their behavior. DNA is genetically shown to express itself through traits by up to 75%. This leaves a sort of buffer of around 25%. This region is available for us to adapt to our environmental stimuli. Your innate qualities will not reach their full potential without stimulation from the environment, in a leadership case, with education and training and therefore it can be argued that environmental exposure is necessary to fully expose the potentials and capabilities of an individual, rather than instill a new skill or develop a talent that was not existent before. Innate leadership is not a permanent state, on the contrary, it is a continuously adaptive situation demanding contextual evolutionary changes or resignation from the subject occupying the role. When the needs and demands of a society or era outweigh the relevance of the innate leaders' traits and competencies, an evolution of leadership is needed to maintain a positive relationship between all parties involved. As a result, the innate leader will begin to lose their innateness in their role and unless they evolve and adapt (because the two actions are not the same) to new contextual needs, their tenure as leader will begin to be detrimental and counter-functional. What we want to put forward is a real, universal and constructive understanding of what makes a human happy, motivated and productive and how an innate person in context is a much better solution in the short and long run, for those around them when put to a task.

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This thesis analyzes often verbally functioning based expressions ou seja (that is) and quer dizer (that is to say) which introduce appositive constructions, present in op-eds in weekly periodicals belonging to Brazilian journalistic realm (VEJA, ISTOÉ, ÉPOCA) in 2012. Despite the fact that the labels attributed to such grammatical forms in current literature are varied, they are at first denominated conectores (connectors) in this thesis (GONÇALVES et al., 2007), as they connect the two units which compose the appositive construction – base and appositive units. They are later referred to as marcadores (markers) (MARTELOTTA; VOTRE; CEZÁRIO, 1996) as they sign reformulations carried out by text speaker/author. In order to carry out the research, interdisciplinary theoretical reference was Functional Linguistics, whose investigations are grounded in conceptual fundamentals of apposition and appositive constructions description in journalistic texts, allied to Textual Linguistics, which, through semantic relations study, helps to make a discursive connectors/markers’ profile. In this investigation, our main objective is to describe appositive constructions behavior spearheaded by the previously mentioned expressions, with reference to: a) generalizations about linguistic embodiment forms, marked by various punctuation marks, which permit their identification as desgarradas (dislocated) forms (DECAT, 2011); b) the different syntactic functions driven by the semantic relation of correferência do ponto de vista do locutor (co-reference from the speaker’s point of view) and performed by unit A base element (base or matrix); c) units weight relation (symmetry and asymmetry); d) expressions’ textual and discursive functions represented by unit B (appositive); and e) paraphrases types (WENZEL,1985) introduced by such connectors/markers. In order to achieve this purpose, we have taken as an object for analysis SN constructions (nominal syntagma) as well as the clause form (in the sentence) starting with a pragmatic and discursive approach. In corpus texts, the appositive constructions are used as argument and referencing strategy carriers. This is a descriptive and interpretative research, which leads to data qualitative and quantitative analysis, bearing in mind expressions’ syntactic, semantic and discursive profile. Final results confirm the hypothesis of discursive connectors/markers ou seja and quer dizer productivity in media written texts, introducing dislocated constructions which are highly functional in paraphrase’s contexts of use stablishing apposition.
En esta tesis se analiza el funcionamiento de las expresiones de base verbal, o sea, es decir, introductoras de las construcciones apositivas presentes en artículos de opinión en revistas semanales de ámbito periodístico (VEJA, ISTOÉ, ÉPOCA) de 2012. Aunque en la literatura actual, han sido cambiadas las rotulaciones asignadas a estas formas gramaticales, se les llama en esta tesis, al comienzo, conectores (GONÇALVES et al., 2007) para hacer la conexión entre las dos unidades que componen la construcción de aposición - unidad base y la unidad aposición; siendo después denominadas marcadores (MARTELOTTA; VOTRE; CEZÁRIO, 1996), por señalizar reformulaciones realizadas por el hablante/ autor del texto. Para la investigación, tomamos como base teórica, de carácter interdisciplinario, la Lingüística Funcional, que constituye la base de las investigaciones sobre los fundamentos conceptuales de la aposición y de la descripción de construcciones apositivas en estos textos, junto con Linguística Textual que, a través del estudio de las relaciones semánticas, ayuda en la caracterización de los conectores / marcadores del discurso. En este estudio, objetivamos describir esencialmente el comportamiento de las construcciones apositivas encabezadas por las expresiones citadas en relación con: a) las generalizaciones acerca de las formas de materialización lingüística, señaladas por varios signos de puntuación, que permiten identificarlas como desgarradas (DECAT, 2011); b) las diferentes funciones sintácticas, impulsadas por la relación semántica de correferencia bajo punto de vista del hablante y realizadas por el elemento base de la unidad (base o matriz); c) al cociente de peso (simetría y asimetría) de las unidades; d) las funciones textuales-discursivas representadas por la unidad B (aposición) de dichas construcciones; y e) los tipos de paráfrasis (WENZEL, 1985) introducidas por estos conectores / marcadores. Para lograr este propósito, tomemos como objeto de análisis construcciones en forma de SN (sintagma nominal) y también en la forma clausular (oracional), a partir de un enfoque que consideramos pragmático-discursivo. En los textos que conforman el corpus, las construcciones apositivas se utilizan como portadoras de las estrategias de argumentos y de remisión. La investigación es de carácter descriptivo e interpretativo, lo que llevó al análisis cuantitativo y cualitativo de los datos recogidos, teniendo en cuenta el perfil sintáctico, semántico y discursivo de esas construcciones. Los resultados finales confirman la hipótesis de la productividad de los conectores/marcadores del discurso, o sea, es decir, en textos escritos en los medios de comunicación, introductores de construcciones desgarradas, siendo altamente funcionales en los contextos de uso de las paráfrasis que forman la aposición.
Esta tese analisa o funcionamento das expressões de base verbal ou seja e quer dizer, introdutoras de construções apositivas, presentes em textos opinativos de periódicos semanais da esfera jornalística (VEJA, ISTOÉ, ÉPOCA) do ano de 2012. Apesar de, na literatura corrente, serem variadas as rotulações atribuídas a essas formas gramaticais, elas são denominadas nesta tese, a princípio, de conectores (GONÇALVES et al., 2007), por fazerem a conexão entre as duas unidades que compõem a construção apositiva – unidade base e unidade apositiva; sendo depois referidas como marcadores (MARTELOTTA; VOTRE; CEZÁRIO, 1996), por sinalizarem reformulações realizadas pelo autor do texto. Para a realização da pesquisa, tomamos como referencial teórico, de caráter interdisciplinar, a Linguística Funcional, que alicerça as investigações em torno dos fundamentos conceituais da aposição e da descrição de construções apositivas nesses textos, aliada à Linguística Textual, que, através do estudo das relações semânticas, auxilia na caracterização dos conectores/marcadores discursivos. Nesta investigação, objetivamos, essencialmente, descrever o comportamento das construções apositivas encabeçadas pelas expressões citadas no que concerne: a) a generalizações sobre as formas de materialização linguística, assinaladas por diversos sinais de pontuação, os quais permitem identificá-las como desgarradas (DECAT, 2011); b) às diferentes funções sintáticas, impulsionadas pela relação semântica de correferência do ponto de vista do locutor e desempenhadas pelo elemento base da unidade A (base ou matriz); c) à relação de peso (simetria e assimetria) das unidades; d) às funções textual-discursivas representadas pela unidade B (apositiva) das referidas construções; e e) aos tipos de paráfrases (WENZEL, 1985) introduzidas por esses conectores/marcadores. Para atingir esse propósito, tomamos como objeto de análise construções sob a forma de SN (sintagma nominal) e também sob a forma clausular (oracional), a partir de uma abordagem que consideramos pragmático-discursiva. Nos textos que constituem o corpus, as construções apositivas são usadas como portadoras de estratégias de argumentação e referenciação. A pesquisa tem caráter descritivo-interpretativo, o que levou à análise quanti-qualitativa dos dados colhidos, tendo em mente o perfil sintático, semântico e discursivo das referidas construções. Os resultados finais confirmam a hipótese da produtividade dos conectores/marcadores discursivos ou seja e quer dizer em textos escritos da mídia, introdutores de construções desgarradas, sendo estes altamente funcionais nos contextos de uso das paráfrases que dão forma à aposição.

Indiana University-Purdue University Indianapolis (IUPUI)
Prodromal Alzheimer’s disease (AD) has recently been identified as a disease state where pathophysiological changes may progress despite the absence of significant clinical symptoms. Yet, the specific processes of neural dysfunction occurring during this preclinical phase remain unclear. Resting state fMRI (RS-fMRI) in combination with brain connectomic measurements may be able to provide ways to measure subtle connectivity changes in different neurological disease states. For instance, RS-fMRI scans allow us to determine functionally connected yet spatially distinct brain regions that can then be separated into resting-state networks (RSNs). More recently, the exploration of RSNs in disease states have proved promising since they have been reliably altered when compared to a control population. By using brain connectomic approaches to assess functional connectivity we can evaluate the human connectome from a different and more global perspective to help us better understand and detect prodromal neurodegenerative disease states.

碩士
國立成功大學
醫學資訊研究所
102
Recently, the relation among activated human brain regions has drawn interests and has been investigated. The imaging technique of functional magnetic resonance imagimg (fMRI) can be used to observe by changes in cerebral blood oxygenation and, therefore, brain connectivity. To understand how white matter (WM) tractography influences brain connectivity, we use diffusion magnetic resonance imagimg (dMRI) technique and algorithm to calculate WM map. The connectivity measurement combining fMRI and dMRI datasets is called anatomically weighted functional connectivity (awFC). Finally, the results show that, when using awFC datasets, the clusters have higher functional connectivity (FC) and structural connectivity (SC) strength when using awFC datasets.

Contexte La connectomique, ou la cartographie des connexions neuronales, est un champ de recherche des neurosciences évoluant rapidement, promettant des avancées majeures en ce qui concerne la compréhension du fonctionnement cérébral. La formation de circuits neuronaux en réponse à des stimuli environnementaux est une propriété émergente du cerveau. Cependant, la connaissance que nous avons de la nature précise de ces réseaux est encore limitée. Au niveau du cortex visuel, qui est l’aire cérébrale la plus étudiée, la manière dont les informations se transmettent de neurone en neurone est une question qui reste encore inexplorée. Cela nous invite à étudier l’émergence des microcircuits en réponse aux stimuli visuels. Autrement dit, comment l’interaction entre un stimulus et une assemblée cellulaire est-elle mise en place et modulée? Méthodes En réponse à la présentation de grilles sinusoïdales en mouvement, des ensembles neuronaux ont été enregistrés dans la couche II/III (aire 17) du cortex visuel primaire de chats anesthésiés, à l’aide de multi-électrodes en tungstène. Des corrélations croisées ont été effectuées entre l’activité de chacun des neurones enregistrés simultanément pour mettre en évidence les liens fonctionnels de quasi-synchronie (fenêtre de ± 5 ms sur les corrélogrammes croisés corrigés). Ces liens fonctionnels dévoilés indiquent des connexions synaptiques putatives entre les neurones. Par la suite, les histogrammes peri-stimulus (PSTH) des neurones ont été comparés afin de mettre en évidence la collaboration synergique temporelle dans les réseaux fonctionnels révélés. Enfin, des spectrogrammes dépendants du taux de décharges entre neurones ou stimulus-dépendants ont été calculés pour observer les oscillations gamma dans les microcircuits émergents. Un indice de corrélation (Rsc) a également été calculé pour les neurones connectés et non connectés. Résultats Les neurones liés fonctionnellement ont une activité accrue durant une période de 50 ms contrairement aux neurones fonctionnellement non connectés. Cela suggère que les connexions entre neurones mènent à une synergie de leur inter-excitabilité. En outre, l’analyse du spectrogramme dépendant du taux de décharge entre neurones révèle que les neurones connectés ont une plus forte activité gamma que les neurones non connectés durant une fenêtre d’opportunité de 50ms. L’activité gamma de basse-fréquence (20-40 Hz) a été associée aux neurones à décharge régulière (RS) et l’activité de haute fréquence (60-80 Hz) aux neurones à décharge rapide (FS). Aussi, les neurones fonctionnellement connectés ont systématiquement un Rsc plus élevé que les neurones non connectés. Finalement, l’analyse des corrélogrammes croisés révèle que dans une assemblée neuronale, le réseau fonctionnel change selon l’orientation de la grille. Nous démontrons ainsi que l’intensité des relations fonctionnelles dépend de l’orientation de la grille sinusoïdale. Cette relation nous a amené à proposer l’hypothèse suivante : outre la sélectivité des neurones aux caractères spécifiques du stimulus, il y a aussi une sélectivité du connectome. En bref, les réseaux fonctionnels «signature » sont activés dans une assemblée qui est strictement associée à l’orientation présentée et plus généralement aux propriétés des stimuli. Conclusion Cette étude souligne le fait que l’assemblée cellulaire, plutôt que le neurone, est l'unité fonctionnelle fondamentale du cerveau. Cela dilue l'importance du travail isolé de chaque neurone, c’est à dire le paradigme classique du taux de décharge qui a été traditionnellement utilisé pour étudier l'encodage des stimuli. Cette étude contribue aussi à faire avancer le débat sur les oscillations gamma, en ce qu'elles surviennent systématiquement entre neurones connectés dans les assemblées, en conséquence d’un ajout de cohérence. Bien que la taille des assemblées enregistrées soit relativement faible, cette étude suggère néanmoins une intrigante spécificité fonctionnelle entre neurones interagissant dans une assemblée en réponse à une stimulation visuelle. Cette étude peut être considérée comme une prémisse à la modélisation informatique à grande échelle de connectomes fonctionnels.
Background ‘Connectomics’— the mapping of neural connections, is a rapidly advancing field in neurosciences and it promises significant insights into the brain functioning. The formation of neuronal circuits in response to the sensory environment is an emergent property of the brain; however, the knowledge about the precise nature of these sub-networks is still limited. Even at the level of the visual cortex, which is the most studied area in the brain, how sensory inputs are processed between its neurons, is a question yet to be completely explored. Heuristically, this invites an investigation into the emergence of micro-circuits in response to a visual input — that is, how the intriguing interplay between a stimulus and a cell assembly is engineered and modulated? Methods Neuronal assemblies were recorded in response to randomly presented drifting sine-wave gratings in the layer II/III (area 17) of the primary visual cortex (V1) in anaesthetized cats using tungsten multi-electrodes. Cross-correlograms (CCGs) between simultaneously recorded neural activities were computed to reveal the functional links between neurons that were indicative of putative synaptic connections between them. Further, the peristimulus time histograms (PSTH) of neurons were compared to divulge the epochal synergistic collaboration in the revealed functional networks. Thereafter, perievent spectrograms were computed to observe the gamma oscillations in emergent microcircuits. Noise correlation (Rsc) was calculated for the connected and unconnected neurons within these microcircuits. Results The functionally linked neurons collaborate synergistically with augmented activity in a 50-ms window of opportunity compared with the functionally unconnected neurons suggesting that the connectivity between neurons leads to the added excitability between them. Further, the perievent spectrogram analysis revealed that the connected neurons had an augmented power of gamma activity compared with the unconnected neurons in the emergent 50-ms window of opportunity. The low-band (20-40 Hz) gamma activity was linked to the regular-spiking (RS) neurons, whereas the high-band (60-80 Hz) activity was related to the fast-spiking (FS) neurons. The functionally connected neurons systematically displayed higher Rsc compared with the unconnected neurons in emergent microcircuits. Finally, the CCG analysis revealed that there is an activation of a salient functional network in an assembly in relation to the presented orientation. Closely tuned neurons exhibited more connections than the distantly tuned neurons. Untuned assemblies did not display functional linkage. In short, a ‘signature’ functional network was formed between neurons comprising an assembly that was strictly related to the presented orientation. Conclusion Indeed, this study points to the fact that a cell-assembly is the fundamental functional unit of information processing in the brain, rather than the individual neurons. This dilutes the importance of a neuron working in isolation, that is, the classical firing rate paradigm that has been traditionally used to study the encoding of a stimulus. This study also helps to reconcile the debate on gamma oscillations in that they systematically originate between the connected neurons in assemblies. Though the size of the recorded assemblies in the current investigation was relatively small, nevertheless, this study shows the intriguing functional specificity of interacting neurons in an assembly in response to a visual input. One may form this study as a premise to computationally infer the functional connectomes on a larger scale.

Les recherches menées pour comprendre les troubles du spectre autistique (TSA) et la schizophrénie (SZ) ont communément utilisé une approche dite descendante, partant du diagnostic clinique pour investiguer des phénotypes intermédiaires cérébraux ainsi que des variations génétiques associées. Des études transdiagnostiques récentes ont remis en question ces frontières nosologiques, et suggèrent des mécanismes étiologiques imbriqués. L’approche montante propose de composer des groupes de porteurs d’un même variant génétique afin d’investiguer leur contribution aux conditions neuropsychiatriques (NPs) associées. Les variations du nombre de copies (CNV, perte ou gain d’un fragment d’ADN) figurent parmi les facteurs biologiques les plus associés aux NPs, et sont dès lors des candidats particulièrement appropriés. Les CNVs induisant un risque pour des conditions similaires, nous posons l’hypothèse que des classes entières de CNVs convergent sur des dimensions d’altérations cérébrales qui contribuent aux NPs. L’imagerie fonctionnelle au repos (rs-fMRI) s’est révélée un outil prometteur en psychiatrie, mais presqu’aucune étude n’a été menée pour comprendre l’impact des CNVs sur la connectivité fonctionnelle cérébrale (FC). Nos objectifs étaient de: 1) Caractériser l’effet des CNVs sur la FC; 2) Rechercher la présence des motifs conférés par ces signatures biologiques dans des conditions idiopathiques; 3) Tester si la suppression de gènes intolérants à l’haploinsuffisance réorganise la FC de manière indépendante à leur localisation dans le génome. Nous avons agrégé des données de rs-fMRI chez: 502 porteurs de 8 CNVs associées aux NPs (CNVs-NP), de 4 CNVs sans association établie, ainsi que de porteurs de CNVs-NPs éparses; 756 sujets ayant un diagnostic de TSA, de SZ, ou de trouble déficitaire de l’attention/hyperactivité (TDAH), et 5377 contrôles. Les analyses du connectome entier ont montré un effet de dosage génique positif pour les CNVs 22q11.2 et 1q21.1, et négatif pour le 16p11.2. La taille de l’effet des CNVs sur la FC était corrélée au niveau de risque psychiatrique conféré par le CNV. En accord avec leurs effets sur la cognition, l’effet des délétions sur la FC était plus élevé que celui des duplications. Nous avons identifié des similarités entre les motifs cérébraux conférés par les CNVs-NP, et l’architecture fonctionnelle des individus avec NPs. Le niveau de similarité était associé à la sévérité du CNV, et était plus fort avec la SZ et les TSA qu’avec les TDAH. La comparaison des motifs conférés par les délétions les plus sévères (16p11.2, 22q11.2) à l’échelle fonctionnelle, et d’expression génique, nous a confirmé l’existence présumée de relation entre les mutations elles-mêmes. À l’aide d’une mesure d’intolérance aux mutations (pLI), nous avons pu inclure tous les porteurs de CNVs disponibles, et ainsi identifier un profil d’haploinsuffisance impliquant le thalamus, le cortex antérieur cingulaire, et le réseau somato-moteur, associé à une diminution de mesure d’intelligence générale. Enfin, une analyse d’exploration factorielle nous a permis de confirmer la contribution de ces régions cérébrales à 3 composantes latentes partagées entre les CNVs et les NPs. Nos résultats ouvrent de nouvelles perspectives dans la compréhension des mécanismes polygéniques à l’oeuvre dans les maladies mentales, ainsi que des effets pléiotropiques des CNVs.
Research on Autism Spectrum Disorder (ASD) and schizophrenia (SZ) has mainly adopted a ‘top-down’ approach, starting from psychiatric diagnosis, and moving to intermediate brain phenotypes and underlying genetic factors. Recent cross-disorder studies have raised questions about diagnostic boundaries and pleiotropic mechanisms. By contrast, the recruitment of groups based on the presence of a genetic risk factor allows for the investigation of molecular pathways related to a particular risk for neuropsychiatric conditions (NPs). Copy number variants (CNVs, loss or gain of a DNA segment), which confer high risk for NPs are natural candidates to conduct such bottom-up approaches. Because CNVs have a similar range of adverse effects on NPs, we hypothesized that entire classes of CNVs may converge upon shared connectivity dimensions contributing to mental illness. Resting-state functional MRI (rs-fMRI) studies have provided critical insight into the architecture of brain networks involved in NPs, but so far only a few studies have investigated networks modulated by CNVs. We aimed at 1) Delineating the effects of neuropsychiatric variants on functional connectivity (FC), 2) Investigating whether the alterations associated with CNVs are also found among idiopathic psychiatric populations, 3) Testing whether deletions reorganize FC along general dimensions, irrespective of their localization in the genome. We gathered rsfMRI data on 502 carriers of eight NP-CNVs (high-risk), four CNVs without prior association to NPs as well as carriers of eight scarcer NP-CNVs. We also analyzed 756 subjects with idiopathic ASD, SZ, and attention deficit hyperactivity disorder (ADHD), and 5,377 controls. Connectome-wide analyses showed a positive gene dosage effect for the 22q11.2 and 1q21.1 CNVs, and a negative association for the 16p11.2 CNV. The effect size of CNVs on relative FC (mean-connectivity adjusted) was correlated with the known level of NP-risk conferred by CNVs. Consistent with results on cognition, we also reported that deletions had a larger effect size on FC than duplications. We identified similarities between high-risk CNV profiles and the connectivity architecture of individuals with NPs. The level of similarity was associated with mutation severity and was strongest in SZ, followed by ASD, and ADHD. The similarity was driven by the thalamus, and the posterior cingulate cortex, previously identified as hubs in transdiagnostic psychiatric studies. These results raised questions about shared mechanisms across CNVs. By comparing deletions at the 16p11.2 and 22q11.2 loci, we identified similarities at the connectivity, and at the gene expression level. We extended this work by pooling all deletions available for analysis. We asked if connectivity alterations were associated with the severity of deletions scored using pLI, a measure of intolerance to haploinsufficiency. The haploinsufficiency profile involved the thalamus, anterior cingulate cortex, and somatomotor network and was correlated with lower general intelligence and higher autism severity scores in 3 unselected and disease cohorts. An exploratory factor analysis confirmed the contribution of these regions to three latent components shared across CNVs and NPs. Our results open new avenues for understanding polygenicity in psychiatric conditions, and the pleiotropic effect of CNVs on cognition and on risk for neuropsychiatric disorders.