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Jean paul Banquet

Jean paul Banquet
French National Centre for Scientific Research CNRS UMR 8051 ENSEA Cergy Pontoise Uni · Neurocybernetics and robotics

MD, phD Applied Mathematics

About

98
Publications
11,373
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2,224
Citations
Citations since 2016
4 Research Items
411 Citations
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2016201720182019202020212022020406080
2016201720182019202020212022020406080
2016201720182019202020212022020406080

Publications

Publications (98)
Article
Experiences of animal and human beings are structured by the continuity of space and time coupled with the unidirectionality of time. In addition to its pivotal position in spatial processing and navigation, the hippocampal system also plays a central, multiform role in several types of temporal processing. These include timing and sequence learnin...
Article
Full-text available
Place recognition is a complex process involving idiothetic and allothetic information. In mammals, evidence suggests that visual information stemming from the temporal and parietal cortical areas ('what' and 'where' information) is merged at the level of the entorhinal cortex (EC) to build a compact code of a place. Local views extracted from spec...
Conference Paper
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The distinction between cognitive goal-oriented and SR habitual behavior has long been classical in Neuroscience. Nevertheless, the mechanisms of the two types of behaviors as well as their interactions are poorly understood, in spite of significant advances in the knowledge of their supporting structures, the cortico-striatal loops. A neural netwo...
Chapter
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Unravelling the neural substrates of behavior has made possible to dissociate a high level representation system dedicated to the build-up and storage of a world model, and an implementation system for decision, strategic choices, and sequential behavior. In most ecological situations, particularly in the animal kingdom, a tight functional associat...
Data
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We present a neural network model where the spatial and temporal components of a task are merged and learned in the hippocampus as chains of associations between sensory events. The prefrontal cortex integrates this information to build a cognitive map representing the environment. The cognitive map can be used after latent learning to select optim...
Article
Full-text available
We present a neural network model where the spatial and temporal components of a task are merged and learned in the hippocampus as chains of associations between sensory events. The prefrontal cortex integrates this information to build a cognitive map representing the environment. The cognitive map can be used after latent learning to select optim...
Article
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revue Connaître, Réseau Blaise Pascal
Article
Patients with Parkinson's disease (PD) have difficulties in movement adaptation to optimize performance in novel environmental contexts such as altered screen cursor-hand relationships. Prior studies have shown that the time course of the distortion differentially affects visuomotor adaptation to screen cursor rotations, suggesting separate mechani...
Conference Paper
Full-text available
In this paper we present a model of reinforcement learning (RL) which can be used to solve goal-oriented navigation tasks. Our model supposes that transitions between places are learned in the hip- pocampus (CA pyramidal cells) and associated with information coming from path-integration. The RL neural network acts as a bias on these transitions to...
Article
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In a previous model [3], a spectral timing neural network [4] was used to account for the role of the Hs in the acquisition of classical conditioning. The ability to estimate the timing between separate events was then used to learn and predict transitions between places in the environment. We propose a neural architecture based on this work and ex...
Article
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Place cells are hippocampal pyramidal neurons that discharge strongly in relation to the rat's location in the environment. We recently reported that many place cells recorded from rats performing place or cue navigation tasks also discharged when they were at the goal location rather than in the primary firing field. Furthermore, subtle difference...
Article
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In this paper, we present a model for the generation of grid cells and the emergence of place cells from multimodal input to the entorhinal cortex (EC). In this model, grid cell activity in the dorsocaudal medial entorhinal cortex (dMEC) [28] results from the operation of a long-distance path integration system located outside the hippocampal forma...
Article
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In this paper, a model of visual place cells (PCs) based on precise neurobiological data is presented. The robustness of the model in real indoor and outdoor environments is tested. Results show that the interplay between neurobiological modelling and robotic experiments can promote the understanding of the neural structures and the achievement of...
Article
Full-text available
In this paper, a model of place cells (PCs) built from precise neurobiologi- cal data is presented. The robustness of the model in real indoor and outdoor environ- ments is tested. Results show that the inter- play between precise neurobiological mod- elling and robotic experiments can promote the understanding of the biological circuitry and the a...
Article
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In this letter we describe a hippocampo-cortical model of spatial processing and navigation based on a cascade of increasingly complex associative processes that are also relevant for other hippocampal functions such as episodic memory. Associative learning of different types and the related pattern encoding-recognition take place at three successi...
Conference Paper
A neural network model of intrahippocampal and hippocampo-cortico-gangliobasal loops allows the robotic implementation of the spatial information contained within cognitive maps in neural space, into temporo-spatial sequences of movements during goal-oriented navigation in outer space. At the representation level, the intrahippocampal loop features...
Article
Full-text available
Place cells are hippocampal neurons whose discharge is strongly related to a rat's location in the environment. The existence of such cells, combined with the reliable impairments seen in spatial tasks after hippocampal damage, has led to the proposal that place cells form part of an integrated neural system dedicated to spatial navigation. This hy...
Conference Paper
Full-text available
Understanding the brain and the cognitive mechanisms is a central question for philosophers, neuroscientists, psychologs and engineers as well. In our team, we try to reconcile the old cybernetic approach with neural network modelling and artificial intelligence. This neurocybernetics approach aims at participating in the effort to build a science...
Conference Paper
Full-text available
This article introduces a neural network capable of learning a temporal sequence. Directly inspired from a hippocampus model [2], this architecture allows an autonomous robot to learn how to imitate a sequence of movements with the correct timing. The results show that the network model is fast, accurate and robust.
Article
Full-text available
The goal of this paper is to propose a model of the hippocampal system that reconciles the presence of neurons that look like "place cells" with the implication of the hippocampus (Hs) in other cognitive tasks (e.g., complex conditioning acquisition and memory tasks). In the proposed model, "place cells" or "view cells" are learned in the perirhina...
Conference Paper
Full-text available
A biologically inspired integrated model of different hippocampal subsystems makes a distinction between place cells (PC) within the entorhinal cortex (EC) (diffuse) or dentate gyrus (segregated), and transition cells (TC) in CA3-CA1 that encode transitions between events. These two types of codes support two kinds of hippocampo-cortical cognitive...
Article
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A biologically inspired integrated model of dif­ ferent hippoc ampal su bs ystems makes a distinc­ tion be tween place cells (PC) within entorhinal cortex (diffuse) or dentate gyrus (segregated), and transition cells (TC) in CA3-CA1 that enco de transitions between events. These two types of codes support two kinds of hippocampo-cortical cogniti ve...
Article
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As models of living beings acting in a real world biorobots undergo an accelerated “philogenic” complexification. The first efficient robots performed simple animal behaviours (e.g., those of ants, crickets) and later on isolated elementary behaviours of complex beings. The increasing complexity of the tasks robots are dedicated to is matched by an...
Article
Spatial working memory has been shown to be impaired in schizophrenia. In contrast, memory for temporal order has been poorly studied in patients with schizophrenia. The aim of this study was to compare and to further characterize spatial working memory and sequence reproduction deficits in patients with schizophrenia under stable medication by man...
Article
After critical appraisal of mathematical and biological characteristics of the model, we discuss how a classical hippocampal neural network expresses functions similar to those of the chaotic model, and then present an alternative stimulus-driven chaotic random recurrent neural network (RRNN) that learns patterns as well as sequences, and controls...
Article
Working memory deficit in schizophrenia is classically attributed to a prefrontal dysfunction. Here, we further characterize spatial working memory and sequence reproduction deficits in schizophrenics by manipulating cues, delay, set size, and response type in various recall and recognition tasks. This allowed us to dissociate working memory proces...
Article
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This paper proposes a neural network architecture designed to exhibit learning and communication capabilities via imitation. Our architecture allows a “protoimitation” behavior using the “perception ambiguity” inherent in real environments. In the perspective of turn-taking and gestural communication between two agents, new experiments on movement...
Article
Full-text available
This paper proposes a neural architecture for a robot in order to learn how to imitate a sequence of movements performed by another robot or by a human. The main idea is that the imitation process does not need to be given to the system but can emerge from a mis-interpretation of the perceived situation at the level of a simple sensory-motor system...
Article
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une s'equence motrice et de son timing pr'ecis. Un autre int'eret de ce travail est que le r'eseau de neurones utilis'e pour l'apprentissage des s'equences est directement inspir'e d'une structure c'er'ebrale, l'hippocampe, principalement impliqu'ee dans les processus de m'emoire. Nous discutons l'importance des processus d'imitation pour la compr...
Conference Paper
Full-text available
A basic architecture inspired from dentate gyrus and CA3-CA1 hippocampal fields combines a spectral timing module and an association network learning event transitions. According to the type of input the system can learn and replay: purely temporal sequences of aperiodic events; place-field chains as building blocks of graphs and maps, by combining...
Article
Taking inspiration from animal strategies, we propose an artificial neural network model for robot visual navigation in a maze-like environment. It is composed of two structures. The first one enables visual homing. The second one builds a “cognitive map” of the environment in order to plan a path. This architecture is successfully tested on variou...
Article
Full-text available
In this paper, we describe how a mobile robot under simple visual control can retrieve a particular goal location in an open environment. Our model neither needs a precise map nor to learn all the possible positions in the environment. The system is a neural architecture inspired by neurobiological analysis of how visual patterns named landmarks ar...
Conference Paper
Full-text available
Visually guided landmark navigation is based on space coding by hippocampal place cells (PC). A biologically realistic architecture of cooperative-competitive associative networks (implemented as a control system for mobile agents) emulates PC activity during local navigation in exploration and goal-retrieval. The system builds and stores panoramic...
Conference Paper
We present here a neural model for mobile robot action selection and trajectories planning. It is based on the elaboration of a “cognitive map”. This cognitive map builds up a graph linking together reachable places. We first demonstrate that this map may be used for the control of the robot speed assuring a convergence to the goal. We show afterwa...
Article
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To test the hypothesis of a planning dysfunction in schizophrenia using a precise temporal definition, the readiness potential (RP), a negative cortical wave preceding self-initiated movements and reflecting motor preparation processes, was studied in patients under stable medication and in controls. The supplementary motor area (SMA), known to be...
Article
Psychology and neurobiology nowadays provide a large amount of precise information on visual system function. This information can be used in the design of autonomous systems capable of learning and recognising objects and places important for survival in complex unknown (real or virtual) environments. Our work is based on the principles that perce...
Conference Paper
Full-text available
. In this paper, we present a generic robotic control architectureinspired from the hippocampus (a brain structure involved inmemory). Moreover, we show how the implantation on a real robot hashelped us to gradually refine the neurobiological model.1. IntroductionThe main goal of our research team is to design neural architectures for thecontrol of...
Article
Full-text available
This paper proposes a neural architecture for a robot to learn how to imitate a sequence of move-ments performed by another robot or by a hu-man. The main idea is that the imitation pro-cess does not need to be given to the system but can emerge from a mis-interpretation of the per-ceived situation at the level of a simple sensori-motor system. We...
Article
Full-text available
We present a model of hippocampal and frontal functions based on neuropsychology, brain imaging and neurophysiology. The type of memory register supporting the functions of these two systems and their relations is fundamental to the understanding of the nature of information processing they perform. In particular, a clear delineation must be drawn...
Conference Paper
Full-text available
We describe how a mobile robot controlled only by visual information can retrieve a particular goal location in an open environment. Our model does not need a precise map nor to learn all the possible positions in the environment. The system is a neural architecture inspired from neurobiological studies using the recognition of visual patterns call...
Conference Paper
Full-text available
In this paper we show that the environment topology can be “taken for free” and simplify the learning problems on autonomous robots. The key point is to preserve the coding of the sensory information all along the neural processing chain. First, we explain how it is possible to build a robot controller inspired from neurobiological studies that can...
Article
Fifteen alcoholics diagnosed according to DSM-III-R, who were detoxified for at least 2 weeks and showed no clinical withdrawal signs, were investigated with 16 channel EEG mapping during resting, manumotor and music perception conditions, and were compared with 13 control persons. Single photon emission computed tomography (SPECT) using hexa-methy...
Article
Full-text available
Nous présentons un système de navigation pour robot autonome dans un environnement ouvert. Le robot rejoint un objectif en associant des mouvements aux informations visuelles provenant de l'environnement. Il utilise un apprentissage simple et en ligne. Il ne crée aucune carte complexe de son environnement. Le méchanisme s'avère efficace et robuste,...
Conference Paper
Full-text available
In this paper, we will study how an autonomous robot can learn Perception-Action (PerAc) associations based on visual information in order to navigate in environments of growing complexity (number of shapes to be analyzed). The starting point is the fact that an association problem (with a delayed reinforcement signal is NPcomplete and so impossibl...
Article
A double-key version of Posner's covert orientation of visual attention test, which involves shifting of preparation for response from one side to another, was administered to 32 depressives and 32 controls to evidence retardation of mentation in depressives and compare it to symptom-rating scales. Results showed depressives' overall response times...
Article
Full-text available
Three neuropsychological tests (Rey's auditory verbal learning test, word fluency and signal detection test for words) were administered to 36 depressed patients (medicated and non-medicated) and 26 controls and compared to scale scores for depression severity and psychomotor retardation to examine how retardation was related to cognitive performan...