Mathias Quoy

Mathias Quoy
Université Paris-Seine, Université de Cergy-Pontoise, ENSEA, CNRS · ETIS UMR 8051

Professor

About

115
Publications
9,693
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1,354
Citations
Introduction
Mathias Quoy currently works at the ETIS Lab, UMR 8051 Université Paris-Seine, Université de Cergy-Pontoise, ENSEA, CNRS. Mathias Quoy does research in Computer Engineering, Artificial Intelligence and Artificial Neural Network. His current project is 'sensorimotor integration & perceptual binding.'

Publications

Publications (115)
Article
We propose that coding and decoding in the brain are achieved through digital computation using three principles: relative ordinal coding of inputs, random connections between neurons, and belief voting. Due to randomization and despite the coarseness of the relative codes, we show that these principles are sufficient for coding and decoding sequen...
Article
In order to keep trace of information and grow up, the infant brain has to resolve the problem about where old information is located and how to index new ones. We propose that the immature prefrontal cortex (PFC) uses its primary functionality of detecting hierarchical patterns in temporal signals as a second feature to organize the spatial orderi...
Article
Full-text available
Recurrent neural networks (RNNs) have been proved very successful at modeling sequential data such as language or motions. However, these successes rely on the use of the backpropagation through time (BPTT) algorithm, batch training, and the hypothesis that all the training data are available at the same time. In contrast, the field of developmenta...
Chapter
As a phenomenon in dynamical systems allowing autonomous switching between stable behaviors, chaotic itinerancy has gained interest in neurorobotics research. In this study, we draw a connection between this phenomenon and the predictive coding theory by showing how a recurrent neural network implementing predictive coding can generate neural traje...
Article
Full-text available
In this work, we build upon the Active Inference (AIF) and Predictive Coding (PC) frameworks to propose a neural architecture comprising a generative model for sensory prediction, and a distinct generative model for motor trajectories. We highlight how sequences of sensory predictions can act as rails guiding learning, control and online adaptation...
Preprint
Full-text available
As a phenomenon in dynamical systems allowing autonomous switching between stable behaviors, chaotic itinerancy has gained interest in neurorobotics research. In this study, we draw a connection between this phenomenon and the predictive coding theory by showing how a recurrent neural network implementing predictive coding can generate neural traje...
Preprint
Full-text available
In this work, we build upon the Active Inference (AIF) and Predictive Coding (PC) frameworks to propose a neural architecture comprising a generative model for sensory prediction, and a distinct generative model for motor trajectories. We highlight how sequences of sensory predictions can act as rails guiding learning, control and online adaptation...
Article
Full-text available
We propose a developmental model inspired by the cortico-basal system (CX-BG) for vocal learning in babies and for solving the correspondence mismatch problem they face when they hear unfamiliar voices, with different tones and pitches. This model is based on the neural architecture INFERNO standing for Iterative Free-Energy Optimization of Recurre...
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...
Preprint
Full-text available
In order to keep trace of information, the brain has to resolve the problem where information is and how to index new ones. We propose that the neural mechanism used by the prefrontal cortex (PFC) to detect structure in temporal sequences, based on the temporal order of incoming information, has served as second purpose to the spatial ordering and...
Preprint
Full-text available
In this article, we apply the Free-Energy Principle to the question of motor primitives learning. An echo-state network is used to generate motor trajectories. We combine this network with a perception module and a controller that can influence its dynamics. This new compound network permits the autonomous learning of a repertoire of motor trajecto...
Article
Full-text available
We present a framework based on iterative free-energy optimization with spiking neural networks for modeling the fronto-striatal system (PFC-BG) for the generation and recall of audio memory sequences. In line with neuroimaging studies carried out in the PFC, we propose a genuine coding strategy using the gain-modulation mechanism to represent abst...
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...
Article
Here, the authors introduce a novel system which incorporates the discriminative motion of oriented magnitude patterns (MOMP) descriptor into simple yet efficient techniques. The authors' descriptor both investigates the relations of the local gradient distributions in neighbours among consecutive image sequences and characterises information chang...
Conference Paper
Full-text available
Human working memory is capable to generate dynamically robust and flexible neuronal sequences for action planning, problem solving and decision making. However, current neurocomputational models of working memory find hard to achieve these capabilities since intrinsic noise is difficult to stabilize over time and destroys global synchrony. As part...
Article
Full-text available
The intra-parietal lobe coupled with the Basal Ganglia forms a working memory that demonstrates strong planning capabilities for generating robust yet flexible neuronal sequences. Neurocomputational models however, often fails to control long range neural synchrony in recurrent spiking networks due to spontaneous activity. As a novel framework base...
Conference Paper
In this paper, we present a novel descriptor for human action recognition, called Motion of Oriented Magnitudes Patterns (MOMP), which considers the relationships between the local gradient distributions of neighboring patches coming from successive frames in video. The proposed descriptor also characterizes the information changing across differen...
Conference Paper
Full-text available
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
The question whether newborns possess inborn social skills is a long debate in developmental psychology. Fetal behavioral and anatomical observations show evidences for the control of eye movements and facial behaviors during the third trimester of pregnancy whereas specific sub-cortical areas, like the superior colliculus (SC) and the striatum app...
Chapter
Full-text available
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...
Conference Paper
Full-text available
For low level behaviors, navigational trajectories can be encoded as attraction basin resulting from associations between visual based localization and directions to follow. The use of other sensory information such as contexts for modifying the behavior needs a specialized learning. In this paper, we propose a minimal model using multimodal contex...
Article
Abstract The so-called self-other correspondence problem in imitation demands to find the transformation that maps the motor dynamics of one partner to our owns. This requires a general purpose sensorimotor mechanism that transforms an external fixation-point (partner’s shoulder) reference frame to one’s own body-centred reference frame. We propose...
Conference Paper
Full-text available
In this paper, we study a robust multi modal compass for a vision based navigation system. The model mimics several aspects of the head direction cells found in the postsubiculum of the rat. Idiothetic information is recalibrated according to the learning of visual stimuli as-sociated to robust landmarks. The model is based on dynamic neural fields...
Article
One of the aims of Cart-ASUR project is to propose an indicator of urban sound quality based on perceptive and acoustic data. The originality of this project consists in using mobile phone technology to collect data. 60 persons had to assess about 20 locations in Paris at four or five homogenous periods (days, evening, night, summer, winter) with a...
Article
Full-text available
During development, infants learn to differentiate their motor behaviors relative to various contexts by exploring and identifying the correct structures of causes and effects that they can perform; these structures of actions are called task sets or internal models. The ability to detect the structure of new actions, to learn them and to select on...
Conference Paper
Full-text available
Trajectories can be encoded as attraction basin resulting from recruited associations between visually based localization and orientations to follow (low level behaviors). Navigation to different places according to some other multimodal information needs a particular learning. We propose a minimal model explaining such a behavior adaptation from n...
Conference Paper
Full-text available
We propose a developmental scenario for explaining neonatal imitation. We hypothesize that the early maturation of the superior colliculus (SC) at the fetal period may strongly contribute to the construction of the social brain. We underly two mechanisms in SC potentially important which are (1) spatial topological organization of the unisensory mo...
Article
Full-text available
The question whether newborns possess inborn social skills is a long debate in developmental psychology. Fetal behavioral and anatomical observations show evidences for the control of eye movements and facial behaviors during the third trimester of pregnancy whereas specific sub-cortical areas, like the superior colliculus (SC) and the striatum app...
Article
In order to minimize the duration of acoustic measurements and to characterize homogeneous areas from a temporal point of view, a series of six location measurements was carried out continuously during three months in Paris. Around fifty thousand samples of 5-min, 10-min, 15-min, 20-min, 30-min, and 1-h duration measurements were extracted for each...
Data
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
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...
Conference Paper
Full-text available
When a robot is brought into a new environment, it has a very limited knowledge of what surrounds it and what it can do. Either to navigate in the world, or to interact with humans, the robot must be able to learn complex states, using input information from sensors. For navigation task, visual information are commonly used for localisation. Other...
Article
Full-text available
The paper presents a novel experiment aiming at studying how an autonomous robot can develop an artwork appreciation through human-robot interaction. This experiment took place at the Quai Branly museum for 10 days and 4 hours a day. It is a first step of a long term project aiming at designing a robot as an art amateur and mediator. The robot's be...
Conference Paper
Full-text available
The purpose of this study is to develop a predictive model of urban sound quality from field survey data using multiple linear regressions and artificial neural networks (ANNs). In order to determine a sound quality indicator, 320 passers-by were asked to assess their environment mainly from an acoustic point of view but also from a global perspect...
Article
Full-text available
In this paper we present a biologically-inspired model of spatio-temporal learning in the hippocampus and prefrontal cortex which can be used in tasks requiring the behavior of the robot to be constrained by sensory and temporal information. In this model chains of sensory events are learned and associated with motor actions. The temporality of the...
Conference Paper
Full-text available
When a robot is brought into a new environment, it has a very limited knowledge of what surrounds it and what it can do. One way to build up that knowledge is through exploration but it is a slow process. Programming by demonstration is an efficient way to learn new things from interaction. A robot can imitate gestures it was shown through passive...
Article
Full-text available
Robots are expected to become reliable partners for working in human environments. One of the tasks that they could have to perform is collecting objects and gathering/sorting them for any purposes. In such a task the robot would have to explore its environment to discover objects of interest, navigate toward them, grasp them and navigate again to...
Article
Full-text available
Hippocampal "place cells" and the precession of their extracellularly recorded spiking during traversal of a "place field" are well-established phenomena. More recent experiments describe associated entorhinal "grid cell" firing, but to date only conceptual models have been offered to explain the potential interactions among entorhinal cortex (EC)...
Conference Paper
Full-text available
We propose a model of the hippocampus aimed at learning the timed association between subsequent sensory events. The properties of the neural network allow it to learn and predict the evolution of con- tinuous rate-coded signals as well as the occurrence of transitory events, using both spatial and non-spatial information. The system is able to pro...
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...
Conference Paper
Full-text available
The purpose of this study was to develop a predictive model of urban sound quality from field survey data using mul-tiple linear regressions and artificial neural networks (ANNs). In order to determine a soundscape pleasantness model, passers-by were asked to assess their environment mainly from an acoustic point of view but also from a global pers...
Article
Full-text available
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
Mathematical programming approaches, like linear programming (LP) or mix-integer programming (MIP) are widely used as an optimization tool, since they can compute the best possible configuration of a constrained system. However, the needed computing resources and time cannot always be figured out in advance, and happen to be beyond available resour...
Conference Paper
Full-text available
In order to minimize the duration of acoustic measurements and to characterize homogeneous areas in a temporal point of view, a series of measurements were carried out continuously at crossroads during 3 months in Paris. 27 000 samples of 5-min, 10-min, 15- min, 20-min, 1-h and 2-h were extracted. Each sample is characterized by 11 energy indicator...
Conference Paper
Full-text available
L'objectif de cette étude est d'établir un modèle prédictif de la qualité du paysage sonore en milieu urbain à partir d'enquêtes de terrain et au travers de deux méthodes d'analyses distinctes. Afin de déterminer un modèle d'agrément sonore nous avons élaboré un questionnaire que nous avons soumis à des passants et dans lequel nous leur avons deman...
Article
Full-text available
Starting from neurobiological hypotheses on the existence of place cells (PC) in the brain, the aim of this article is to show how little assumptions at both individual and social levels can lead to the emergence of non-trivial global behaviors in a multiagent system (MAS). In particular, we show that adding a simple, hebbian learning mechanism on...
Conference Paper
Full-text available
Linking perceptive features and acoustic measurements in natural environments requires measurements obtained during field studies. These measurements can take into account global indicators and indices devoted to different sources, and generally, locations such as markets, parks or streets are selected with regards to their use by city dwellers. Bu...
Article
Full-text available
Établir un lien entre caractéristiques perceptives et paramètres acoustiques nécessite de réaliser des mesures sur le terrain dans différents environnements sonores. Ces mesures peuvent tenir compte d’indicateurs globaux et d’indices spécifiques aux différentes sources sonores. Généralement, les lieux d’études comme les marchés, les parcs ou les ru...