Genes microexônicos (MEGs) apresentam uma arquitetura bastante peculiar, sendo compostos predominantemente por quatro ou mais exons simétricos bem pe- quenos dispostos em tandem (microexons Š 36 bp, com tamanhos múltiplos de 3). Eles foram descritos pela primeira vez em 2009 no platelminto parasita Schistosoma mansoni (agente etiológico da esquistossomose). Alguns desses genes apresentam evidência (de transcritômica e proteômica) de gerar diferentes isoformas de proteínas através do mecanismo de splicing alternativo. Os MEGs não apresentam homólogos fora do gênero Schistosoma. Microexons individuais já foram reportados em genes de organismos modelo e do ser humano, normalmente atuando como um hotspot de splicing alternativo, porém nestes casos apenas um único microexon por gene fora reportado. Com este pano de fundo, fizemos o seguinte questionamento: existem genes com arquitetura similar (ou seja, múltiplos microexons em tandem) em outros organismos? Desenvolvemos uma heurística capaz de detectar genes com a arquitetura dos MEGs e a aplicamos no transcritoma de S. mansoni e, além de detectar os MEGs originais, detectamos 31 novos genes. Este pipeline foi aplicado a uma coleção de anotações de genomas e detectou 494 genes distribuídos entre 125 organismos (incluindo animais, plantas, fungos e alguns eucariotos unicelulares). / Microexon genes (MEGs) have an unusual architecture, composed predominantly by four or more very small tandemly disposed symmetric exons (microexons 36 bp, with exon sizes multiple of 3). They were first described in 2009 in the parasitic platyhelminth Schistosoma mansoni (etiologic agent of schistosomiasis). Some of those genes display evidence (by transcriptomics and proteomics) of generating variable protein isoforms through alternative splicing. MEGs have no homologs outside the Schistosoma genus. The presence of individual microexons has also been reported in genes of model organisms and humans, usually as a hotspot of alternative splicing, but in those cases only a single microexon per gene was observed. Within this background, we asked the following question: are there genes with similar architecture (i.e., with multiple internal microexons in tandem) in other organisms? We developed a pipeline to detect genes with the architecture of S. mansoni MEGs, applied it to an updated transcriptome mapping of the S. mansoni genome and successfully detected the original MEGs and 31 new genes. This pipeline could be applied to the collection of public data from genome annotations of other species to eventually detect new genes with multiple tandem microexons.

With MEG, the tiny magnetic fields produced by neuronal currents within the brain can be measured completely non-invasively. But the signals are very small (~100 fT) and often obscured by spontaneous brain activity and external noise. So, a recurrent issue in MEG data analysis is the identification and elimination of this unwanted interference within the recordings. Various strategies exist to meet this purpose. In this thesis, two of these strategies are scrutinized in detail. The first is the commonly used procedure of averaging over trials which is a successfully applied data reduction method in many neurocognitive studies. However, the brain does not always respond identically to repeated stimuli, so averaging can eliminate valuable information. Alternative approaches aiming at single trial analysis are difficult to realize and many of them focus on temporal patterns. Here, a compromise involving random subaveraging of trials and repeated source localization is presented. A simulation study with numerous examples demonstrates the applicability of the new method. As a result, inferences about the generators of single trials can be drawn which allows deeper insight into neuronal processes of the human brain. The second technique examined in this thesis is a preprocessing tool termed Signal Space Separation (SSS). It is widely used for preprocessing of MEG data, including noise reduction by suppression of external interference, as well as movement correction. Here, the mathematical principles of the SSS series expansion and the rules for its application are investigated. The most important mathematical precondition is a source-free sensor space. Using three data sets, the influence of a violation of this convergence criterion on source localization accuracy is demonstrated. The analysis reveals that the SSS method works reliably, even when the convergence criterion is not fully obeyed. This leads to utilizing the SSS method for the transformation of MEG data to virtual sensors on the scalp surface. Having MEG data directly on the individual scalp surface would alleviate sensor space analysis across subjects and comparability with EEG. A comparison study of the transformation results obtained with SSS and those produced by inverse and subsequent forward computation is performed. It shows strong dependence on the relative position of sources and sensors. In addition, the latter approach yields superior results for the intended purpose of data transformation.

Ce projet consiste en la compréhension et la reproduction de systèmes électrodynamiques, ou plus spécifiquement électromagnétiques, pouvant potentiellement offrir un coefficient de performance supérieur à 1. Le système plus spécifiquement étudié ici est le MEG (Motionless Electromagnetic Generator).Ce dernier est étudié et analysé en détail dans le but de comprendre et d'expliquer son fonctionnement. Cette analyse consiste principalement en l'identification et l'explication des principaux phénomènes, théories et effets impliqués dans le fonctionnement du MEG. Celle-ci comprend également une analyse d'un prototype construit selon les spécifications de l'inventeur original. Une caractérisation des modèles théoriques et d'un modèle physique ont été faite afin de pousser l'analyse et de pouvoir comparer les résultats attendus, basé sur les théories électrodynamiques traditionnelles, et les résultats réels. Tel que présenté dans le titre, la reproduction du MEG n'a pas donnée les résultats prévus par les concepteurs. Plusieurs explications sont proposées afin d'expliquer pourquoi il en est ainsi.

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Inhibition, an important cognitive skill relying on frontal lobe function, is often deficient in individuals with autism spectrum disorders (ASD). Spatiotemporal measures of brain activity were acquired using magnetoencephalography during a Go/No-go task with adolescents and adults with ASD and matched controls. During the task, participants responded to Go stimuli and withheld their response to No-go stimuli. Typical inhibitory network development was investigated in study 1. Adolescents displayed a distributed activity pattern, recruiting temporal and parietal regions, in addition to frontal areas, unlike adults. In study 2, inhibition was compared between individuals with and without ASD. Lateralization differences were found: adults with ASD activated the left and control adults recruited the right inferior prefrontal cortex. Adolescents with ASD recruited predominantly frontal regions, unlike their controls. Implications include immature inhibitory networks in typical adolescence and deficits in adolescents with ASD in recruiting distal cortical regions to supplement poor frontal lobe function.

Inhibition, an important cognitive skill relying on frontal lobe function, is often deficient in individuals with autism spectrum disorders (ASD). Spatiotemporal measures of brain activity were acquired using magnetoencephalography during a Go/No-go task with adolescents and adults with ASD and matched controls. During the task, participants responded to Go stimuli and withheld their response to No-go stimuli. Typical inhibitory network development was investigated in study 1. Adolescents displayed a distributed activity pattern, recruiting temporal and parietal regions, in addition to frontal areas, unlike adults. In study 2, inhibition was compared between individuals with and without ASD. Lateralization differences were found: adults with ASD activated the left and control adults recruited the right inferior prefrontal cortex. Adolescents with ASD recruited predominantly frontal regions, unlike their controls. Implications include immature inhibitory networks in typical adolescence and deficits in adolescents with ASD in recruiting distal cortical regions to supplement poor frontal lobe function.

This thesis explores the spatiotemporal network dynamics underlying natural speech comprehension, as measured by electro-magnetoencephalography (E/MEG). I focus on the transient effects of incrementality and constraints in speech on access to lexical semantics. Through three E/MEG experiments I address two core issues in systems neuroscience of language: 1) What are the network dynamics underpinning cognitive computations that take place when we map sounds to rich semantic representations? 2) How do the prior semantic and syntactic contextual constraints facilitate this mapping? Experiment 1 investigated the cognitive processes and relevant networks that come online prior to a word’s recognition point (e.g. “f” for butterfly) as we access meaning through speech in isolation. The results revealed that 300 ms before the word is recognised, the speech incrementally activated matching phonological and semantic representations resulting in transient competition. This competition recruited LIFG, and modality specific regions (LSMG, LSTG for the phonological; LAG and MTG for the semantic domain). Immediately after the word’s recognition point the semantic representation of the target concept was boosted, and rapidly accessed recruiting bilateral MTG and AG. Experiment 2 explored the cortical networks underpinning contextual semantic processing in speech. Participant listened to two-word spoken phrases where the semantic constraint provided by the modifier was manipulated. To separate out cognitive networks that are modulated by semantic constraint from task positive networks I performed a temporal independent component analysis. Among 14 networks extracted, only the activity of bilateral AG was modulated by semantic constraint between -400 to -300 ms before the noun’s recognition point. Experiment 3 addressed the influence of sentential syntactic constraint on anticipation and activation of upcoming syntactic frames in speech. Participants listened to sentences with local syntactic ambiguities. The analysis of the connectivity dynamics in the left frontotemporal syntax network showed that the processing of sentences that contained the less anticipated syntactic structure showed early increased feedforward information flow in 0-100 ms, followed by increased recurrent connectivity between LIFG and LpMTG from the 200-500 ms from the verb onset. Altogether the three experiments reveal novel insights into transient cognitive networks recruited incrementally over time both in the absence of and with context, as the speech unfolds, and how the activation of these networks are modulated by contextual syntactic and semantic constraints. Further I provide neural evidence that contextual constraints serve to facilitate speech comprehension, and how the speech networks recover from failed anticipations.

<p> The focus of this thesis is on the utilization of the sparsity concept in solving some challenging problems, e.g., finding a unique solution to the under-determined linear system of equations in which the number of equations is less than the number of unknowns. This concept is extended to the problem of solving the under-determined blind source separation (BSS) problem in which the number of source signals is greater than the number of sensors and both the mixing matrix and the source signals are unknowns. In this respect we study three problems: </p> <p> 1. Developing some algorithms for solving the under-determined linear system of equations for the case of a sparse solution vector. In this thesis we develop a new methodology for minimizing a class of non-convex (concave on the non-negative orthant) functions for solving the aforementioned problem. The proposed technique is based on locally replacing the original objective function by a quadratic convex function which is easily minimized. For a certain selection of the convex objective function, the existing class of algorithms called Iterative Re-weighted Least Squares (IRLS) can be derived from the proposed methodology. Thus the proposed algorithms are a generalization and unification of the previous methods. In this thesis we also propose a convex objective function that produces an algorithm that can converge to a sparse solution vector in significantly fewer iterations than the IRLS algorithms.</p> <p> 2. Solving the under-determined BSS problem by developing new clustering algorithms for estimating the mixing matrix. The under-determined BSS problem is usually solved by following a two-step approach, in which the mixing matrix is estimated in the first step, then the sources are estimated in the second step. For the case of sparse sources, the mixing matrix is usually estimated by clustering the columns of the observation matrix. In this thesis we develop three novel clustering algorithms that can efficiently estimate the mixing matrix, as well as the number of sources, which is usually unknown. Numerical simulations verify the efficiency of the proposed algorithms compared to some well known algorithms that are usually used for solving the same problem.</p> <p> 3. Extraction of a desired source signal from a linear mixture of hidden sources when prior information is available about the desired source signal. There are many situations in which one is interested in extracting a specific source signal. The a priori available information about the desired source signal could be temporal, spatial, or both. In this thesis we develop new algorithms for extracting a desired sparse source signal from a linear mixture of hidden sources. The information available about the desired source signal, as well as its sparsity, are incorporated in an optimization problem for extracting this source signal. Four different algorithms have been developed for solving this problem. Numerical simulations show that the proposed algorithms can be used successfully for removing different kind of artifacts from real electroencephalographic (EEG) data and for estimating the event related potential (ERP) signal from synthesized EEG data.</p> / Thesis / Doctor of Philosophy (PhD)

The capacity to estimate the number of objects (numerosity) in the environment is ontogenetically precocious and phylogenetically ancient. In animals, this ability holds significant adaptive advantages, directly influencing survival and reproductive success. In humans, it may serve an additional purpose by providing a start-up kit for the acquisition of symbolic numbers, thus making it a potential focus for mathematics education and intervention strategies. Behavioral, neurophysiological, and neuroimaging findings suggest that numerosity information is directly extracted from the environment. However, numerosity is inherently linked with other visual characteristics of sets (such as larger sets often occupy more space or are more densely spaced), making it challenging to determine the extent to which the observed response to numerosity is distinct from the response to other visual attributes. In my PhD research I provide experimental evidence through neuroimaging and computational modeling techniques elucidating where, when, and how numerical information is encoded in the human brain. This work therefore provides a threefold contribution. First, I show that numerosity is represented over and above nonnumeric visual features in a widespread network of areas starting from early visual areas and further amplified in associative areas along the dorsal but also notably the ventral stream, and that the neural representational geometries of regions across the two steams are substantially identical. Second, I showed that numerosity is represented at an early stage and seemingly in parallel across of a set of regions including early visual, parietal, and temporal, preceding the emergence of non-numeric features that could indirectly contribute to numerosity computation. Finally, by comparing the fMRI data with a convolutional neural network (CNN) to explore similarities and differences between the model and human brain data, I discovered that although the CNN can perform approximate numerosity comparisons and the structure of their representation in their hidden layers captures well numerosity representation in early visual areas of humans, it falls short of fully simulating the way in which associative brain regions represent numerosity. Taken together, the findings of this thesis provide experimental evidence supporting the notion that number is a primary visual feature, encoded independent from other visual features quickly and widely across the human brain. Furthermore, they emphasize the need for additional investigation to unravel the computational mechanisms underlying numerosity in the human brain.

Ce travail de thèse vise à étudier les mécanismes de contrôle cognitif mobilisés durant les modulations séquentielles de l’exécution stratégique. Nous avons également étudié l’évolution au cours du vieillissement de ces mécanismes. Les données recueillies montrent que, contrairement aux postulats des modèles des stratégies, l’exécution stratégique sur un problème est modulée par la stratégie utilisée sur le problème précédent. De plus, les données de la neuro-imagerie (i.e., électroencéphalographie et magnétoencéphalographie) ont montré l’activation des régions cingulaires antérieures et frontales inférieures, précédemment observées dans les tâches de conflit. Chez les participants âgés, on observe globalement un déclin de la capacité à moduler d’un essai à l’autre l’exécution stratégique. Toutefois, nous avons étudié un sous-groupe d’adultes âgés présentant un maintien des modulations séquentielles. Au niveau neurophysiologique, ces participants présentaient un décours temporel plus précoce et l’activation d’un réseau neuronal plus étendu. Ces modifications ont été interprétées comme reflétant l’activation de processus compensatoires afin de maintenir des performances similaires à celles des adultes jeunes. Les résultats nous permettent de préciser l’implication des mécanismes de contrôle cognitif dans les performances stratégiques, et de comprendre la contribution de ces mécanismes dans les variations stratégiques observées avec l’âge. / Recent studies suggest that cognitive control mechanisms, allowing regulations of behavior to support goal-directed behaviors, are involved during strategy execution, together with aging effects therein. However, the processes involved and how they change with age need further investigations. The present work aims to study cognitive control processes involved in sequential modulations of strategy execution. It also examines how these mechanisms evolve during aging. Altogether, these findings reveal that, in contrast with theoretical models of strategies that assume strategy independence, strategy execution on a given trial is modulated as a function of strategy execution on previous trial. Moreover, neuroimaging data (i.e., electroencephalography and magnetoencephalography) showed a specific neural network activated during such sequential modulations, involving anterior cingulate and inferior frontal regions. These regions are known to be activated in conflict tasks. In older adults, a decline in sequential modulations of strategy execution was observed. However, some older adults showed preserved behavioral performance, associated with changes in time course and brain regions engaged. Such changes were interpreted as reflecting compensatory mechanisms involved to maintain behavioral performance similar to young adults. All in all, results specify the implication of cognitive control mechanisms in strategic processing, and in strategic variations during aging.