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

Decision Making: who’s in charge?

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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

Hippocampal Auto-Associative Memory

In the framework of autonomous navigation, the use of a cognitive map requires to perform fast and robust storage of different pieces of information. Classical models of auto-associative memory have been proven to be limited in such a context because of the well known catastrophic interference phenomenon. Taking strong inspiration from the inner organization of the hippocampus, we present in this paper a model of auto-associative memory based on 4 distinct structures (EC, DG, CA3 and CA1) where information is processed along a loop at three distinct levels and has been tested successfully on a real robot