A manutenção do equilíbrio depende da ativação sinérgica de músculos dos dois hemicorpos, e há evidências de que essa coordenação é mediada por circuitos medulares, que estão sob controle supra-segmentar. O objetivo desse trabalho é descrever mecanismos neurofisiológicos e biomecânicos envolvidos no controle postural de sujeitos saudáveis frente a uma perturbação provocada por uma contração reflexa, enfatizando-se os mecanismos associados à coordenação entre membros. A perturbação postural ocorreu em resposta a um estímulo elétrico unilateral no nervo tibial. Devido a restrições em estudos anteriores, utilizou-se uma ampla abordagem (múltiplos músculos, reflexos cruzados) e estimulação precisamente controlada. Os resultados mostraram um complexo padrão de ativação dos músculos dos membros inferiores bilateralmente. Logo após o estímulo, foram encontradas respostas de curta e média latência em músculos da perna e da coxa. Posteriormente, foram observadas algumas ações musculares de longa latência nos músculos mais distais, que provavelmente foram ativadas em resposta às oscilações posturais. As respostas musculares iniciais sugerem que as informações aferentes e os reflexos medulares possuem uma função muito importante na regulação da coordenação entre membros, durante a manutenção da postura ereta quieta. / Balance depends on the synergic activation of muscles bilaterally, and there is evidence that this coordination is mediated by spinal circuits, which are under supra-spinal control. The objective of this study is to describe neurophysiologic and biomechanical mechanisms involved in the postural control of healthy subjects submitted to a disturbance provoked by a muscular reflex contraction. The postural perturbation was caused by a unilateral electric stimulation to the popliteal fossa. The analysis emphasizes the mechanisms associated with interlimb coordination. In this work, methodological approaches expanded those of previous work, the recordings being done bilaterally and the stimulus being precisely controlled. The results showed a complex pattern of bilateral muscular activation. Short and medium latency responses were found in the leg and thigh muscles. These were followed by some muscular activity at longer latencies, probably occurring due to the postural oscillations. The initial muscular responses suggest that the afferent inflow and the spinal cord reflexes have an important function in the between-limb coordination during the standing posture.

Nas cirurgias de ressecção de tumores do ângulo pontocerebelar, a preservação do nervo facial está entre os seus principais objetivos. Diversas técnicas neurofisiológicas vêm sendo empregadas com o objetivo de predizer déficit imediato do nervo facial no pós-operatório, como a eletromiografia contínua para registro de atividade neurotônica tipo A, a estimulação direta do nervo facial no sítio tumoral e a estimulação elétrica transcraniana com captação em músculos de face. Analisamos 23 pacientes de forma prospectiva, submetidos à cranectomia retrossigmoide para ressecção de tumores em fossa posterior no período de janeiro de 2008 a março de 2010. Os pacientes foram avaliados clinicamente de acordo com a gradação de House-Brackmann para a função do nervo facial. Foram observadas a ocorrência de atividade neurotônica do tipo A, também chamada de atividade irritativa, a queda da amplitude do potencial motor do nervo facial obtido com a estimulação elétrica transcraniana e o aumento na intensidade do estímulo elétrico da estimulação elétrica transcraniana para a obtenção desse potencial. Esses dados foram relacionados à condição clínica do nervo facial no pós-operatório imediato e na última data de acompanhamento. Observamos que a queda da amplitude do nervo facial acima de 60% do seu valor inicial basal foi a variável mais sensível (89%) e com maior valor preditivo positivo (92%) para a piora clínica do nervo facial. A ocorrência de atividade irritativa isolada foi a variável menos sensível (7%) e com valor preditivo positivo de apenas 25%. O aumento na intensidade da estimulação elétrica transcraniana não mostrou significância estatística (p = 0,287). Concluímos que das variáveis estudadas, a queda na amplitude do potencial evocado motor do 7º nervo craniano acima de 60% foi a melhor na predição de piora clínica imediata do nervo facial / The preservation of facial nerve function is one of the most important goals of the cerebellopontine angle tumor resection surgeries. Valuable neurophysiologic techniques have been used to predict the facial nerve outcome, such as continuous electromyography to identify neurotonic activity type A, direct facial nerve stimulation in the vicinity of the tumor and transcranial motor evoked potential recording in face muscles. We analyzed 23 patients undergoing retrossigmoidectomy approaches for posterior fossa tumor resection between January 2008 and March 2010. Their facial nerve function was evaluated using the House-Brackmann score. We correlated the occurrence of type A neurotonic activity, facial nerve motor evoked potential amplitude obtained with transcranial electrical stimulation and increase in the electric stimulus threshold to the immediate and last follow-up facial nerve outcome. In this series, the increase in electric stimulus threshold showed no statistical significance (p = 0,287). The drop of the facial nerve motor evoked potential amplitude equal or above 60% was the most sensitive (89%) and with the highest positive predictive value (92%) in identifying poor facial nerve outcome. The occurrence of neurotonic activity type A showed to be the least sensitive (7%) and with the poorest positive predictive value (25%) of them. We conclude that among the used parameters, the drop of the final 7º nerve motor evoked potential amplitude equal or above 60% of basal recording was the best one in predicting poor facial nerve outcome

Systematic investigations through several experimental techniques have revealed that hippocampal pyramidal neurons express voltage gated ion channels (VGICs) with well-defined gradients along their dendritic arbor. These actively maintained gradients in various dendritic VGICs effectuate several stereotypic, topographically continuous functional gradients along the topograph of the dendritic arbor, and have been referred to as intraneuronal functional maps. The prime goal of my thesis was to understand the emergence and homeostasis of the several coexistent functional maps that express within hippocampal pyramidal neurons. In the first part of the thesis, we focus only on spatial interactions between ion channels and analyzed the role of such interactions in the emergence of functional maps. We developed a generalized quantitative framework, the influence field, to analyze the extent of influence of a spatially localized VGIC cluster. Employing this framework, we showed that a localized VGIC cluster could have spatially widespread influence, and was heavily reliant on the specific physiological property and background conductances. Using the influence field model, we reconstructed functional gradients from VGIC conductance gradients, and demonstrated that the cumulative contribution of VGIC conductances in adjacent compartments plays a critical role in determining physiological properties at a given location. These results suggested that spatial interactions among spatially segregated VGIC clusters are necessary for the emergence of the functional maps. In the second part of the thesis, we assessed the specific roles of only kinetic interactions between ion channels in determining physiological properties by employing a single-compartmental model. In doing this, we analyzed the roles of interactions among several VGICs in regulating intrinsic response dynamics. Using global sensitivity analysis, we showed that functionally similar models could be achieved even when underlying parameters displayed tremendous variability and exhibited weak pair-wise correlations. These results suggested that that response homeostasis could be achieved through several non-unique channel combinations, as an emergent consequence of kinetic interactions among these channel conductances. In the final part of the thesis, we analyzed the combined impact of both spatial and kinetic interactions among ion channel conductances on the emergence and homeostasis of functional maps in a neuronal model endowed with extensive dendritic arborization. To do this, we performed global sensitivity analysis on morphologically realistic conductance-based models of hippocampal pyramidal neurons that coexpressed six functional maps. We found topographically continuous functional maps to emerge from disparate model parameters with weak pair-wise correlations between parameters. These results implied that individual channel properties need not be set at constant values in achieving overall homeostasis of several coexistent functional maps. We suggest collective channelostasis, where several channels regulate their properties and expression profiles in an uncorrelated manner, as an alternative for accomplishing functional map homeostasis. Finally, we developed a methodology to assess the contribution of individual channel conductances to the various functional measurements employing virtual knockout simulations. We found that the deletion of individual channels resulted in variable, measurement-and location-specific impacts across the model population.

Un accès aux représentations mentales. Voici une phrase qui pourrait bientôt devenir une réalité. La recherche sur les interfaces cerveau-Machines est un champ de recherche en plein essor. En particulier, de grandes avancées ont été réalisées pour permettre par exemple à des tétraplégiques de retrouver une relative autonomie en actionnant un bras robotique par l'activité de leur cerveau. L'équipe de Hochberg a mis en évidence un système permettant à une femme tétraplégique d'attraper une boisson et de boire. Cela montre la précision incroyable que peut avoir une prothèse artificielle pilotée par le cerveau. Ma thèse porte sur un aspect peu exploré des interfaces cerveau-Machines, celui des interfaces cerveau-Machines cognitives, c'est-À-Dire utilisant le contenu représentationnel intime de l'activité du cerveau. Son objectif est de démontrer, sur un modèle primate non-Humaine, la possibilité d'accéder en temps-Réel à ce type de contenu complexe, y compris dans un environnement en perpétuel changement. L'adaptation des interfaces cerveau-Machines dans le monde réel, où nous sommes constamment confrontés à de nouvelles informations, est critique pour son fonctionnement. Un autre aspect, très important, porte sur l'exploration et la compréhension du système nerveux au niveau populationnel en utilisant des méthodes similaires à celles utilisées pour extraire de l'information dans les interfaces cerveau-Machines. Cela nous permet d'étudier le contenu instantané et sa dynamique dans l'évolution du temps. En résumé, nous démontrons la faisabilité d'accéder en temps-Réel à des informations complexes de l'attention spatiale et de la perception visuelle. Cet accès en temps-Réel n'est que peu affecté par un environnement qui change. Le potentiel de ce type d'interfaces cerveau-Machines est immense en vue du traitement de pathologies neurologiques aigües (suite à des accidents cérébraux vasculaires ou suite à des traumatismes accidentés) ou neurodégénératives (dans la maladie d'Alzheimer ou de Parkinson, pour ne parler que des plus connues) / The field of invasive Brain Machine Interfaces (iBMI) has during the last ten years proven its enormous potential in restoring movements in paralyzed patients. The present doctoral thesis introduces a new dimension to this field by using complex cognitive behavior to drive an iBMI. In this respect, visual processes including spatial attention and perception are of special interest. This thesis project has three principal objectives: first, show the feasibility of decoding cognitive information in an offline setup. Second, evaluate the decoding of cognitive information in a real time experimental setup and third, investigate the impact of this setup in a changing environment, this both from the perspective of driving real time brain-Machine interfaces and that of understanding distributed populational neuronal codes. In line with the first objective of this thesis, an evaluation of several different classification techniques has been carried out in order to choose the best suited method for reading out cognitive information. The study provides evidence that visual information can be read out with similar performance as cognitive information. This study is the first study aiming at explicitly comparing the read out of sensory and cognitive information. The two last objectives of the present thesis are carried out on data from a new real-Time experimental setup. First we demonstrate the feasibility of real-Time readout of spatial attention and perception and we bring about a novel understanding about these two cognitive processes. Second, we show that in a changing environment, remarkable reconfigurations of prefrontal neural populations occur under certain contexts while left unaffected by other contexts. This Ph.D. thesis has taken the field of cognitive brain-Machine interfaces one step further by establishing the impact on spatial attention and perception of a changing environment. Facing the many neurological and neurodegenerative pathologies existing today, this thesis provides a steady ground for the continuation of research in this area

Nous possédons la faculté de reconnaître individuellement des centaines d’individus. Ceci nous permet d’évoluer dans une société complexe dont l’organisation est en partie forgée par les relations interindividuelles. La reconnaissance individuelle peut être réalisée par l'identification de divers éléments distincts, comme le visage ou la voix, qui forment chez l’Homme une seule représentation conceptuelle de l'identité de la personne. Nous avons démontré que les singes rhésus, comme les humains, reconnaissent individuellement leurs congénères familiers, mais également les individus humains connus. Ceci montre que la reconnaissance fine est une compétence partagée par un éventail d'espèces de primates pouvant servir de fondement à la vie en réseaux sociaux sophistiqués, et également que le cerveau s’adapte de façon flexible pour reconnaître les individus d'autres espèces lorsque ceux-ci ont une importance socioécologique. Par la suite, au niveau neuronal, ce projet a mis en lumière que les connaissances sociales concernant autrui sont représentées par les neurones hippocampiques ainsi que par les neurones inférotemporaux. Ainsi nous avons observé l’existence de neurones sélectifs aux visages non seulement dans le cortex inferotemporal, comme ceci a été décrit précédemment, mais également dans l’hippocampe. La comparaison des propriétés de ces neurones au sein de ces deux structures, suggère que les deux régions joueraient des rôles complémentaires au cours de la reconnaissance individuelle. Enfin, parce que l'hippocampe est une structure qui a évolué à des degrés divers chez différents mammifères pour soutenir la mémoire autobiographique et les représentations spatiales, la caractérisation des différents types de neurones et de leur connectivité a fourni un cadre commun pour comparer les fonctions de l’hippocampe à travers les espèces / Humans can individually recognize some hundreds of persons and therefore operate within a rich and complex society. Individual recognition can be achieved by identifying distinct elements such as the face or voice as belonging to one individual. In humans, those different cues are linked into one conceptual representation of individual identity. I demonstrated that rhesus monkeys, like humans, recognize familiarpeers but also familiar humans individually and that they match their voice to their corresponding memorized face. Thus it shows that fine individual recognition is a skill shared across a range of primate species, which may serve as the basis of a sophisticated social network. It also suggests that animals’ brains flexibly adapt to recognize individuals of other species when socio-ecologically relevant. Following at the neuronal level, this project put in light that social knowledge about other individuals is represented by hippocampal neurons as well as by inferotemporal neurons. For instance I observed the existence of face preferring neurons not only in the inferotemporal cortex as previously described but also in the hippocampus. Comparison of their properties across both structures, suggests that they could play complementary roles in recognition of individuals. Finally, because the hippocampus is a structure that evolved in various degrees to support autobiographical memory and spatial information in different mammals, I characterized the different subtypes of neurons and their network connectivity in the monkey hippocampus to provide a common anatomical framework to discuss hippocampal functions across species

Intraoperative neurophysiologic monitoring is an integral part of spinal surgeries and involves the recording of somatosensory evoked potentials (SSEP). However, clinical application of IONM still requires anywhere between 200 to 2000 trials to obtain an SSEP signal, which is excessive and introduces a significant delay during surgery to detect a possible neurological damage. The aim of this study is to develop a means to obtain the SSEP using a much less, twelve number of recordings. The preliminary step involved was to distinguish the SSEP with the ongoing brain activity. We first establish that the brain activity is indeed quasi-stationary whereas an SSEP is expected to be identical every time a trial is recorded. An algorithm was developed using Chebychev time windowing for preconditioning of SSEP trials to retain the morphological characteristics of somatosensory evoked potentials (SSEP). This preconditioning was followed by the application of a principal component analysis (PCA)-based algorithm utilizing quasi-stationarity of EEG on 12 preconditioned trials. A unique Walsh transform operation was then used to identify the position of the SSEP event. An alarm is raised when there is a 10% time in latency deviation and/or 50% peak-to-peak amplitude deviation, as per the clinical requirements. The algorithm shows consistency in the results in monitoring SSEP in up to 6-hour surgical procedures even under this significantly reduced number of trials. In this study, the analysis was performed on the data recorded in 29 patients undergoing surgery during which the posterior tibial nerve was stimulated and SSEP response was recorded from scalp. This method is shown empirically to be more clinically viable than present day approaches. In all 29 cases, the algorithm takes 4sec to extract an SSEP signal, as compared to conventional methods, which take several minutes. The monitoring process using the algorithm was successful and proved conclusive under the clinical constraints throughout the different surgical procedures with an accuracy of 91.5%. Higher accuracy and faster execution time, observed in the present study, in determining the SSEP signals provide a much improved and effective neurophysiological monitoring process.

A multitude of sensory inputs needs to be processed during sensorimotor integration. A crucial factor for detecting relevant information is its complexity, since information content can be conflicting at a perceptual level. This may be central to executive control processes, such as response inhibition. This EEG study aims to investigate the system neurophysiological mechanisms behind effects of perceptual conflict on response inhibition. We systematically modulated perceptual conflict by integrating a Global-local task with a Go/Nogo paradigm. The results show that conflicting perceptual information, in comparison to non-conflicting perceptual information, impairs response inhibition performance. This effect was evident regardless of whether the relevant information for response inhibition is displayed on the global, or local perceptual level. The neurophysiological data suggests that early perceptual/ attentional processing stages do not underlie these modulations. Rather, processes at the response selection level (P3), play a role in changed response inhibition performance. This conflict-related impairment of inhibitory processes is associated with activation differences in (inferior) parietal areas (BA7 and BA40) and not as commonly found in the medial prefrontal areas. This suggests that various functional neuroanatomical structures may mediate response inhibition and that the functional neuroanatomical structures involved depend on the complexity of sensory integration processes.

Dans les séries temporelles neurophysiologiques, on observe de fortes oscillations neuronales, et les outils d'analyse sont donc naturellement centrés sur le filtrage à bande étroite.Puisque cette approche est trop réductrice, nous proposons de nouvelles méthodes pour représenter ces signaux.Nous centrons tout d'abord notre étude sur le couplage phase-amplitude (PAC), dans lequel une bande haute fréquence est modulée en amplitude par la phase d'une oscillation neuronale plus lente.Nous proposons de capturer ce couplage dans un modèle probabiliste appelé modèle autoregressif piloté (DAR). Cette modélisation permet une sélection de modèle efficace grâce à la mesure de vraisemblance, ce qui constitue un apport majeur à l'estimation du PAC.%Nous présentons différentes paramétrisations des modèles DAR et leurs algorithmes d'inférence rapides, et discutons de leur stabilité.Puis nous montrons comment utiliser les modèles DAR pour l'analyse du PAC, et démontrons l'avantage de l'approche par modélisation avec trois jeux de donnée.Puis nous explorons plusieurs extensions à ces modèles, pour estimer le signal pilote à partir des données, le PAC sur des signaux multivariés, ou encore des champs réceptifs spectro-temporels.Enfin, nous proposons aussi d'adapter les modèles de codage parcimonieux convolutionnels pour les séries temporelles neurophysiologiques, en les étendant à des distributions à queues lourdes et à des décompositions multivariées. Nous développons des algorithmes d'inférence efficaces pour chaque formulations, et montrons que l'on obtient de riches représentations de façon non-supervisée. / In neurophysiological time series, strong neural oscillations are observed in the mammalian brain, and the natural processing tools are thus centered on narrow-band linear filtering.As this approach is too reductive, we propose new methods to represent these signals.We first focus on the study of phase-amplitude coupling (PAC), which consists in an amplitude modulation of a high frequency band, time-locked with a specific phase of a slow neural oscillation.We propose to use driven autoregressive models (DAR), to capture PAC in a probabilistic model. Giving a proper model to the signal enables model selection by using the likelihood of the model, which constitutes a major improvement in PAC estimation.%We first present different parametrization of DAR models, with fast inference algorithms and stability discussions.Then, we present how to use DAR models for PAC analysis, demonstrating the advantage of the model-based approach on three empirical datasets.Then, we explore different extensions to DAR models, estimating the driving signal from the data, PAC in multivariate signals, or spectro-temporal receptive fields.Finally, we also propose to adapt convolutional sparse coding (CSC) models for neurophysiological time-series, extending them to heavy-tail noise distribution and multivariate decompositions. We develop efficient inference algorithms for each formulation, and show that we obtain rich unsupervised signal representations.

The main goal of the dissertation was to determine task-dependent modulation of corticospinal descending output. From this main goal, I conducted three different studies to determine how corticospinal output to muscles of the upper arm and hand changed as a function of the task demands. In study 1, I examined how a somatosensory-motor circuit changes when a muscle needs to be active in a task and found that this circuit may be dependent on the movement phase, type of afferent input, and the task demands. In study 2, I examined how this same somatosensory-motor circuit acts to both allow and prevent muscle activity before movement. I revealed that this somatosensory-motor circuit may function to prevent muscle activity when a muscle is not needed in a task and creates facilitation of corticospinal output when it needs to be active in a task. These effects, however, are dependent on the movement phase and the digit the muscle is controlling. Study 3 determined how corticospinal output is modulated to upper arm muscles when performing movements that required different combinations of segmental interactions to achieve the task successfully. Corticospinal output was increased when inertia and the BBC moment at a joint resisted the intended joint rotation and these effects were dependent on the muscle and movement phase. I propose a model of the connectivity between the primary motor and somatosensory cortices that would increase, modulate, or decrease corticospinal output to a muscle depending on its role in the task. The findings from this work provides information to guide future neural rehabilitative interventions for individuals who have movement disorders arising from altered somatosensory-motor processing such as Cerebellar Ataxia, Developmental Coordination Disorder, Focal Hand Dystonia, Parkinson’s disease, and stroke. / Dissertation / Doctor of Philosophy (PhD) / On a day to day basis, we perform a variety of movements without giving much thought to how complicated it is for our nervous system to perform said movements. There are many different areas of the brain that are responsible for controlling movement. This dissertation focuses on two key areas that are critical for movement performance, namely the primary motor and somatosensory cortices. The primary motor cortex is largely responsible for sending signals to the muscles to control movement, while the primary somatosensory cortex plays a crucial role in receiving and understanding sensory input from our body. The studies in this dissertation describe how these two areas of the brain communicate during finger and arm movements to produce or prevent muscle activity. This work has implications for individuals with disorders that impact their everyday movements.

No description available.