931 resultados para Variational Convergence
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Abstract (English)General backgroundMultisensory stimuli are easier to recognize, can improve learning and a processed faster compared to unisensory ones. As such, the ability an organism has to extract and synthesize relevant sensory inputs across multiple sensory modalities shapes his perception of and interaction with the environment. A major question in the scientific field is how the brain extracts and fuses relevant information to create a unified perceptual representation (but also how it segregates unrelated information). This fusion between the senses has been termed "multisensory integration", a notion that derives from seminal animal single-cell studies performed in the superior colliculus, a subcortical structure shown to create a multisensory output differing from the sum of its unisensory inputs. At the cortical level, integration of multisensory information is traditionally deferred to higher classical associative cortical regions within the frontal, temporal and parietal lobes, after extensive processing within the sensory-specific and segregated pathways. However, many anatomical, electrophysiological and neuroimaging findings now speak for multisensory convergence and interactions as a distributed process beginning much earlier than previously appreciated and within the initial stages of sensory processing.The work presented in this thesis is aimed at studying the neural basis and mechanisms of how the human brain combines sensory information between the senses of hearing and touch. Early latency non-linear auditory-somatosensory neural response interactions have been repeatedly observed in humans and non-human primates. Whether these early, low-level interactions are directly influencing behavioral outcomes remains an open question as they have been observed under diverse experimental circumstances such as anesthesia, passive stimulation, as well as speeded reaction time tasks. Under laboratory settings, it has been demonstrated that simple reaction times to auditory-somatosensory stimuli are facilitated over their unisensory counterparts both when delivered to the same spatial location or not, suggesting that audi- tory-somatosensory integration must occur in cerebral regions with large-scale spatial representations. However experiments that required the spatial processing of the stimuli have observed effects limited to spatially aligned conditions or varying depending on which body part was stimulated. Whether those divergences stem from task requirements and/or the need for spatial processing has not been firmly established.Hypotheses and experimental resultsIn a first study, we hypothesized that auditory-somatosensory early non-linear multisensory neural response interactions are relevant to behavior. Performing a median split according to reaction time of a subset of behavioral and electroencephalographic data, we found that the earliest non-linear multisensory interactions measured within the EEG signal (i.e. between 40-83ms post-stimulus onset) were specific to fast reaction times indicating a direct correlation of early neural response interactions and behavior.In a second study, we hypothesized that the relevance of spatial information for task performance has an impact on behavioral measures of auditory-somatosensory integration. Across two psychophysical experiments we show that facilitated detection occurs even when attending to spatial information, with no modulation according to spatial alignment of the stimuli. On the other hand, discrimination performance with probes, quantified using sensitivity (d'), is impaired following multisensory trials in general and significantly more so following misaligned multisensory trials.In a third study, we hypothesized that behavioral improvements might vary depending which body part is stimulated. Preliminary results suggest a possible dissociation between behavioral improvements andERPs. RTs to multisensory stimuli were modulated by space only in the case when somatosensory stimuli were delivered to the neck whereas multisensory ERPs were modulated by spatial alignment for both types of somatosensory stimuli.ConclusionThis thesis provides insight into the functional role played by early, low-level multisensory interac-tions. Combining psychophysics and electrical neuroimaging techniques we demonstrate the behavioral re-levance of early and low-level interactions in the normal human system. Moreover, we show that these early interactions are hermetic to top-down influences on spatial processing suggesting their occurrence within cerebral regions having access to large-scale spatial representations. We finally highlight specific interactions between auditory space and somatosensory stimulation on different body parts. Gaining an in-depth understanding of how multisensory integration normally operates is of central importance as it will ultimately permit us to consider how the impaired brain could benefit from rehabilitation with multisensory stimula-Abstract (French)Background théoriqueDes stimuli multisensoriels sont plus faciles à reconnaître, peuvent améliorer l'apprentissage et sont traités plus rapidement comparé à des stimuli unisensoriels. Ainsi, la capacité qu'un organisme possède à extraire et à synthétiser avec ses différentes modalités sensorielles des inputs sensoriels pertinents, façonne sa perception et son interaction avec l'environnement. Une question majeure dans le domaine scientifique est comment le cerveau parvient à extraire et à fusionner des stimuli pour créer une représentation percep- tuelle cohérente (mais aussi comment il isole les stimuli sans rapport). Cette fusion entre les sens est appelée "intégration multisensorielle", une notion qui provient de travaux effectués dans le colliculus supérieur chez l'animal, une structure sous-corticale possédant des neurones produisant une sortie multisensorielle différant de la somme des entrées unisensorielles. Traditionnellement, l'intégration d'informations multisen- sorielles au niveau cortical est considérée comme se produisant tardivement dans les aires associatives supérieures dans les lobes frontaux, temporaux et pariétaux, suite à un traitement extensif au sein de régions unisensorielles primaires. Cependant, plusieurs découvertes anatomiques, électrophysiologiques et de neuroimageries remettent en question ce postulat, suggérant l'existence d'une convergence et d'interactions multisensorielles précoces.Les travaux présentés dans cette thèse sont destinés à mieux comprendre les bases neuronales et les mécanismes impliqués dans la combinaison d'informations sensorielles entre les sens de l'audition et du toucher chez l'homme. Des interactions neuronales non-linéaires précoces audio-somatosensorielles ont été observées à maintes reprises chez l'homme et le singe dans des circonstances aussi variées que sous anes- thésie, avec stimulation passive, et lors de tâches nécessitant un comportement (une détection simple de stimuli, par exemple). Ainsi, le rôle fonctionnel joué par ces interactions à une étape du traitement de l'information si précoce demeure une question ouverte. Il a également été démontré que les temps de réaction en réponse à des stimuli audio-somatosensoriels sont facilités par rapport à leurs homologues unisensoriels indépendamment de leur position spatiale. Ce résultat suggère que l'intégration audio- somatosensorielle se produit dans des régions cérébrales possédant des représentations spatiales à large échelle. Cependant, des expériences qui ont exigé un traitement spatial des stimuli ont produits des effets limités à des conditions où les stimuli multisensoriels étaient, alignés dans l'espace ou encore comme pouvant varier selon la partie de corps stimulée. Il n'a pas été établi à ce jour si ces divergences pourraient être dues aux contraintes liées à la tâche et/ou à la nécessité d'un traitement de l'information spatiale.Hypothèse et résultats expérimentauxDans une première étude, nous avons émis l'hypothèse que les interactions audio- somatosensorielles précoces sont pertinentes pour le comportement. En effectuant un partage des temps de réaction par rapport à la médiane d'un sous-ensemble de données comportementales et électroencépha- lographiques, nous avons constaté que les interactions multisensorielles qui se produisent à des latences précoces (entre 40-83ms) sont spécifique aux temps de réaction rapides indiquant une corrélation directe entre ces interactions neuronales précoces et le comportement.Dans une deuxième étude, nous avons émis l'hypothèse que si l'information spatiale devient perti-nente pour la tâche, elle pourrait exercer une influence sur des mesures comportementales de l'intégration audio-somatosensorielles. Dans deux expériences psychophysiques, nous montrons que même si les participants prêtent attention à l'information spatiale, une facilitation de la détection se produit et ce toujours indépendamment de la configuration spatiale des stimuli. Cependant, la performance de discrimination, quantifiée à l'aide d'un index de sensibilité (d') est altérée suite aux essais multisensoriels en général et de manière plus significative pour les essais multisensoriels non-alignés dans l'espace.Dans une troisième étude, nous avons émis l'hypothèse que des améliorations comportementales pourraient différer selon la partie du corps qui est stimulée (la main vs. la nuque). Des résultats préliminaires suggèrent une dissociation possible entre une facilitation comportementale et les potentiels évoqués. Les temps de réactions étaient influencés par la configuration spatiale uniquement dans le cas ou les stimuli somatosensoriels étaient sur la nuque alors que les potentiels évoqués étaient modulés par l'alignement spatial pour les deux types de stimuli somatosensorielles.ConclusionCette thèse apporte des éléments nouveaux concernant le rôle fonctionnel joué par les interactions multisensorielles précoces de bas niveau. En combinant la psychophysique et la neuroimagerie électrique, nous démontrons la pertinence comportementale des ces interactions dans le système humain normal. Par ailleurs, nous montrons que ces interactions précoces sont hermétiques aux influences dites «top-down» sur le traitement spatial suggérant leur occurrence dans des régions cérébrales ayant accès à des représentations spatiales de grande échelle. Nous soulignons enfin des interactions spécifiques entre l'espace auditif et la stimulation somatosensorielle sur différentes parties du corps. Approfondir la connaissance concernant les bases neuronales et les mécanismes impliqués dans l'intégration multisensorielle dans le système normale est d'une importance centrale car elle permettra d'examiner et de mieux comprendre comment le cerveau déficient pourrait bénéficier d'une réhabilitation avec la stimulation multisensorielle.
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To sense myriad environmental odors, animals have evolved multiple, large families of divergent olfactory receptors. How and why distinct receptor repertoires and their associated circuits are functionally and anatomically integrated is essentially unknown. We have addressed these questions through comprehensive comparative analysis of the Drosophila olfactory subsystems that express the ionotropic receptors (IRs) and odorant receptors (ORs). We identify ligands for most IR neuron classes, revealing their specificity for select amines and acids, which complements the broader tuning of ORs for esters and alcohols. IR and OR sensory neurons exhibit glomerular convergence in segregated, although interconnected, zones of the primary olfactory center, but these circuits are extensively interdigitated in higher brain regions. Consistently, behavioral responses to odors arise from an interplay between IR- and OR-dependent pathways. We integrate knowledge on the different phylogenetic and developmental properties of these receptors and circuits to propose models for the functional contributions and evolution of these distinct olfactory subsystems.
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We present existence, uniqueness and continuous dependence results for some kinetic equations motivated by models for the collective behavior of large groups of individuals. Models of this kind have been recently proposed to study the behavior of large groups of animals, such as flocks of birds, swarms, or schools of fish. Our aim is to give a well-posedness theory for general models which possibly include a variety of effects: an interaction through a potential, such as a short-range repulsion and long-range attraction; a velocity-averaging effect where individuals try to adapt their own velocity to that of other individuals in their surroundings; and self-propulsion effects, which take into account effects on one individual that are independent of the others. We develop our theory in a space of measures, using mass transportation distances. As consequences of our theory we show also the convergence of particle systems to their corresponding kinetic equations, and the local-in-time convergence to the hydrodynamic limit for one of the models.
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Weak solutions of the spatially inhomogeneous (diffusive) Aizenmann-Bak model of coagulation-breakup within a bounded domain with homogeneous Neumann boundary conditions are shown to converge, in the fast reaction limit, towards local equilibria determined by their mass. Moreover, this mass is the solution of a nonlinear diffusion equation whose nonlinearity depends on the (size-dependent) diffusion coefficient. Initial data are assumed to have integrable zero order moment and square integrable first order moment in size, and finite entropy. In contrast to our previous result [CDF2], we are able to show the convergence without assuming uniform bounds from above and below on the number density of clusters.
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We propose a mixed finite element method for a class of nonlinear diffusion equations, which is based on their interpretation as gradient flows in optimal transportation metrics. We introduce an appropriate linearization of the optimal transport problem, which leads to a mixed symmetric formulation. This formulation preserves the maximum principle in case of the semi-discrete scheme as well as the fully discrete scheme for a certain class of problems. In addition solutions of the mixed formulation maintain exponential convergence in the relative entropy towards the steady state in case of a nonlinear Fokker-Planck equation with uniformly convex potential. We demonstrate the behavior of the proposed scheme with 2D simulations of the porous medium equations and blow-up questions in the Patlak-Keller-Segel model.
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We consider a nonlinear cyclin content structured model of a cell population divided into proliferative and quiescent cells. We show, for particular values of the parameters, existence of solutions that do not depend on the cyclin content. We make numerical simulations for the general case obtaining, for some values of the parameters convergence to the steady state but also oscillations of the population for others.
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Minimal models for the explanation of decision-making in computational neuroscience are based on the analysis of the evolution for the average firing rates of two interacting neuron populations. While these models typically lead to multi-stable scenario for the basic derived dynamical systems, noise is an important feature of the model taking into account finite-size effects and robustness of the decisions. These stochastic dynamical systems can be analyzed by studying carefully their associated Fokker-Planck partial differential equation. In particular, we discuss the existence, positivity and uniqueness for the solution of the stationary equation, as well as for the time evolving problem. Moreover, we prove convergence of the solution to the the stationary state representing the probability distribution of finding the neuron families in each of the decision states characterized by their average firing rates. Finally, we propose a numerical scheme allowing for simulations performed on the Fokker-Planck equation which are in agreement with those obtained recently by a moment method applied to the stochastic differential system. Our approach leads to a more detailed analytical and numerical study of this decision-making model in computational neuroscience.
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To describe the collective behavior of large ensembles of neurons in neuronal network, a kinetic theory description was developed in [13, 12], where a macroscopic representation of the network dynamics was directly derived from the microscopic dynamics of individual neurons, which are modeled by conductance-based, linear, integrate-and-fire point neurons. A diffusion approximation then led to a nonlinear Fokker-Planck equation for the probability density function of neuronal membrane potentials and synaptic conductances. In this work, we propose a deterministic numerical scheme for a Fokker-Planck model of an excitatory-only network. Our numerical solver allows us to obtain the time evolution of probability distribution functions, and thus, the evolution of all possible macroscopic quantities that are given by suitable moments of the probability density function. We show that this deterministic scheme is capable of capturing the bistability of stationary states observed in Monte Carlo simulations. Moreover, the transient behavior of the firing rates computed from the Fokker-Planck equation is analyzed in this bistable situation, where a bifurcation scenario, of asynchronous convergence towards stationary states, periodic synchronous solutions or damped oscillatory convergence towards stationary states, can be uncovered by increasing the strength of the excitatory coupling. Finally, the computation of moments of the probability distribution allows us to validate the applicability of a moment closure assumption used in [13] to further simplify the kinetic theory.
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We investigate in this note the dynamics of a one-dimensional Keller-Segel type model on the half-line. On the contrary to the classical configuration, the chemical production term is located on the boundary. We prove, under suitable assumptions, the following dichotomy which is reminiscent of the two-dimensional Keller-Segel system. Solutions are global if the mass is below the critical mass, they blow-up in finite time above the critical mass, and they converge to some equilibrium at the critical mass. Entropy techniques are presented which aim at providing quantitative convergence results for the subcritical case. This note is completed with a brief introduction to a more realistic model (still one-dimensional).
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While much of the literature on immigrants' assimilation has focused on countries with a large tradition of receiving immigrants and with flexible labor markets, very little is known on how immigrants adjust to other types of host economies. With its severe dual labor market, and an unprecedented immigration boom, Spain presents a quite unique experience to analyze immigrations' assimilation process. Using data from the 2000 to 2008 Labor Force Survey, we find that immigrants are more occupationally mobile than natives, and that much of this greater flexibility is explained by immigrants' assimilation process soon after arrival. However, we find little evidence of convergence, especially among women and high skilled immigrants. This suggests that instead of integrating, immigrants occupationally segregate, providing evidence consistent with both imperfect substitutability and immigrants' human capital being under-valued. Additional evidence on the assimilation of earnings and the incidence of permanent employment by different skill levels also supports the hypothesis of segmented labor markets.
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In this paper we propose a stabilized conforming finite volume element method for the Stokes equations. On stating the convergence of the method, optimal a priori error estimates in different norms are obtained by establishing the adequate connection between the finite volume and stabilized finite element formulations. A superconvergence result is also derived by using a postprocessing projection method. In particular, the stabilization of the continuous lowest equal order pair finite volume element discretization is achieved by enriching the velocity space with local functions that do not necessarily vanish on the element boundaries. Finally, some numerical experiments that confirm the predicted behavior of the method are provided.
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El projecte Statmedia 3 ha consolidat definitivament la proposta de les assignatures Bioestadística de Biologia, Anàlisi de dades de Ciències Ambientals i d’Estadística Matemàtica de la Diplomatura renovant una part del material creat amb Statmedia 2. S’han inclòs a més Matemàtiques d’Ambientals i Introducció a la Probabilitat del Grau d’Estadística. L’anterior MQD abastava només pràctiques mentre que aquest projecte permet una oferta diversa d’activitats individualitzades. La individualització consisteix en que cada estudiant rep una proposta de cas personalitzada amb dades diferents. Les activitats poden ser programades presencialment o no, però la clau de l’èxit de l’activitat és que l’alumne obtingui reconeixement del seu treball en l’avaluació continuada. La valoració que fan als alumnes de Statmedia és molt bo, i observem que es produeix una millora en els resultats acadèmics. Statmedia 3 ha implicat un important esforç en la vessant informàtica del projecte, la barreja de tecnologies que utilitzem son punteres: Ajax, servlets i applets Java... Hem posat a punt un assistent on-line per dissenyar documents i planificar activitats que facilita la tasca dels professors. La nostre participació en primera línea del procés de convergència a l’EEES ens ha permès anticipar alguns canvis, i s’ha traduït en que el claustre del Departament d’Estadística assumís que Statmedia és una metodologia essencial dels seus plans docents. El projecte continua en un quart projecte MQD consecutiu, on desplegarem la nova tecnologia implementada. L’objectiu principal serà dotar a les assignatures dels 7 graus on participa el departament d’activitats individualitzades en forma de casos pràctics, problemes i proves diverses. La col·lecció de material emmagatzemada en la nostra biblioteca, forjada després de quasi deu anys de treball continuat, juntament amb l’experiència acumulada de com utilitzar Statmedia de la forma més eficient han començat a ser explotades en els nous graus aquest mateix curs 2009-2010.
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We analyze the rate of convergence towards self-similarity for the subcritical Keller-Segel system in the radially symmetric two-dimensional case and in the corresponding one-dimensional case for logarithmic interaction. We measure convergence in Wasserstein distance. The rate of convergence towards self-similarity does not degenerate as we approach the critical case. As a byproduct, we obtain a proof of the logarithmic Hardy-Littlewood-Sobolev inequality in the one dimensional and radially symmetric two dimensional case based on optimal transport arguments. In addition we prove that the onedimensional equation is a contraction with respect to Fourier distance in the subcritical case.
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This paper presents value added estimates for the Italian regions, in benchmark years from 1891 until 1951, which are linked to those from official figures available from 1971 in order to offer a long-term picture. Sources and methodology are documented and discussed, whilst regional activity rates and productivity are also presented and compared. Thus some questions are briefly reconsidered: the origins and extent of the north-south divide, the role of migration and regional policy in shaping the pattern of regional inequality, the importance of social capital, and the positioning of Italy in the international debate on regional convergence, where it stands out for the long run persistence of its disparities.
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Nonlinear Noisy Leaky Integrate and Fire (NNLIF) models for neurons networks can be written as Fokker-Planck-Kolmogorov equations on the probability density of neurons, the main parameters in the model being the connectivity of the network and the noise. We analyse several aspects of the NNLIF model: the number of steady states, a priori estimates, blow-up issues and convergence toward equilibrium in the linear case. In particular, for excitatory networks, blow-up always occurs for initial data concentrated close to the firing potential. These results show how critical is the balance between noise and excitatory/inhibitory interactions to the connectivity parameter.