1,822 research outputs found
A graphical, scalable and intuitive method for the placement and the connection of biological cells
We introduce a graphical method originating from the computer graphics domain
that is used for the arbitrary and intuitive placement of cells over a
two-dimensional manifold. Using a bitmap image as input, where the color
indicates the identity of the different structures and the alpha channel
indicates the local cell density, this method guarantees a discrete
distribution of cell position respecting the local density function. This
method scales to any number of cells, allows to specify several different
structures at once with arbitrary shapes and provides a scalable and versatile
alternative to the more classical assumption of a uniform non-spatial
distribution. Furthermore, several connection schemes can be derived from the
paired distances between cells using either an automatic mapping or a
user-defined local reference frame, providing new computational properties for
the underlying model. The method is illustrated on a discrete homogeneous
neural field, on the distribution of cones and rods in the retina and on a
coronal view of the basal ganglia.Comment: Corresponding code at https://github.com/rougier/spatial-computatio
A computational approach to the covert and overt deployment of spatial attention
Popular computational models of visual attention tend to neglect the
influence of saccadic eye movements whereas it has been shown that the primates
perform on average three of them per seconds and that the neural substrate for
the deployment of attention and the execution of an eye movement might
considerably overlap. Here we propose a computational model in which the
deployment of attention with or without a subsequent eye movement emerges from
local, distributed and numerical computations
Distributed, Asynchronous, Numerical and Adaptive computing: from neurons to behavior
National audienceComputational models of the brain exist at several different levels of description, from the very precise modelling of a unique spiking neuron, taking into account ion channels and/or dendrites spatial geometry, up to the modelling of very large assemblies of neuron that express complex dynamic interactions. I'm interested in a mesoscopic approach of the brain where the computational paradigm is grounded on the notion of a unit that is essentially a set of time dependent values varying under the influence of other units via adaptive weighted connections. The evolution of the units' value and weights are simply defined by a set of differential equations. This is a strongly constrained framework that has been designed such as to avoid any modeling artifact like a central supervisor or a homunculus. If some properties are to emerge from our models, we want to make sure they are properties of the model as opposed to properties of the software that run the simulation
Open Science
National audienceL’Open science est un mouvement créé par une communauté de chercheu•r•ses. Né d’un constat, celui des difficultés et des obstacles quotidiens que rencontre la communauté scientifique, l’Open science tente d’apporter des solutions aux failles du système de recherche actuel. Si l’Open science s’inscrit donc dans un contexte bien précis et actuel, il ne s’agit pas, cependant, d’un phénomène nouveau. Les notions de patrimoine, de dissémination du savoir et de communauté scientifique sont anciennes. Toutefois, ce phénomène connaît une résurgence certaine grâce au développement des technologies d’information et de communication (TIC). Le numérique permet en effet de faire émerger de nouvelles possibilités en terme de communication, d’échanges entre les chercheur•es•s et de créer de nouveaux modèles de recherche collective et collaborative inclusifs.Ainsi, quelles sont les différentes formes de l’Open science ? Qui sont ses acteurs? Dans quel contexte ce mouvement est-il apparu ? Dans quelle mesure ce phénomène nous éclaire-t-il sur l’évolution du concept de science ? Dans une perspective historique, le mouvement actuel de l’Open science représente-t-il une rupture ou bien une continuité
Mémoires déclarative et procédurale pour la navigation autonome d'un animat
Colloque avec actes et comité de lecture.Parmi les différentes stratégies de navigation autonome issues du monde animal, il semble que celles à base de carte cognitive soient les plus performantes puisqu'elles permettent de rallier à tout moment un lieu précédemment visité. Cette tâche de navigation autonome, à l'instar de la plupart des tâches cognitives, requiert l'utilisation d'une mémoire déclarative et d'une mémoire procédurale dont le fonctionnement est généralement attribué aux structures cérébrales de l'hippocampe et du cortex. A la lumière du fonctionnement et de la modélisation de chacun de ces deux systèmes, cet article propose un modèle de coopération entre ces deux structures autorisant la navigation autonome à l'aide d'une carte cognitive topologique distribuée. || Among the different autonomous navigation strategies available in the animal world, it seems that those based on cognitive maps are the most useful since they allow to reach a known place anytime. This task of autonomous navigation, like most other cogni
Une brève histoire de l'intelligence artificielle
National audienceL'intelligence artificielle (IA) a nourri de nombreux fantasmes depuis sa création. Encore aujourd'hui, certains redoutent l'avènement de robots qui viendraient détruire l'humanité à plus ou moins long terme. Mais où en sommes-nous exactement aujourd'hui ? Peut-on réellement comparer les prouesses de l'IA aux merveilles de l'esprit humain ? Nous verrons au travers de l'histoire de l'IA que rien n'est simple et qu'il est facile de donner l'apparence de l'intelligence sans l'être pour autant
Dynamic Neural Field with Local Inhibition
A lateral-inhibition type neural field model with restricted connections is presented here and represents an experimental extension of the Continuum Neural Field Theory (CNFT) by suppression of the global inhibition. A modified CNFT equation is introduced and allows for a locally defined inhibition to spatially expand within the network and results in a global competition extending far beyond the range of local connections by virtue of diffusion of inhibition. The resulting model is able to attend to a moving stimulus in the presence of a very high level of noise, several distractors or a mixture of both
One critic for two actors
National audienceWe introduces a new hypothesis concerning the dissociated role of the basal ganglia in the selection and the evaluation of action that has been formulated using a theoretical model and confirmed experimentally in monkeys. To do so, and prior to learning, we inactivated the internal part of the Globus Pallidus (GPi, the main output structure of the BG) with injections of Muscimol and we tested monkeys on a variant of a two-armed bandit task where two stimuli are associated with two distinct reward probabilities (0.25 and 0.75 respectively). Unsurprisingly, performance in such condition are at the chance level since the output of basal ganglia cannot influence behaviour. However, the theoretical model predicts that in the meantime, values of the stimuli are nonetheless covertly evaluated and learned. This has been tested and confirmed on the next day, when inhibition has been removed: monkeys instantly showed significant improved performances (above chance level), hence demonstrating they have learned and knew the relative value of the two stimuli. This tends to suggest that the critic part of the basal ganglia may be utilized for evaluating different actors whose origin are yet to be determined experimentally
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