Bayesian Model

2023-01-23_game-theory-and-the-brain

2022-11-21_flash-lag-effect

From the retina to action: Dynamics of predictive processing in the visual system

Laurent U Perrinet

Bayesian Modeling of Motion Perception using Dynamical Stochastic Textures

Jonathan Vacher, Andrew Isaac Meso, Laurent U Perrinet, Gabriel Peyré

The flash-lag effect as a motion-based predictive shift

Mina A Khoei, Guillaume S Masson, Laurent U Perrinet

Estimating and anticipating a dynamic probabilistic bias in visual motion direction

Chloé Pasturel, Jean-Bernard Damasse, Anna Montagnini, Laurent U Perrinet

Anticipating a moving target: role of vision and reinforcement

Anna Montagnini, Jean-Bernard Damasse, Laurent U Perrinet, Laurent Madelain

Eye tracking a self-moved target with complex hand-target dynamics

Fréderic Danion, Caroline Landelle, Anna Montagnini, Laurent U Perrinet, Laurent Madelain

Active inference, eye movements and oculomotor delays

Laurent U Perrinet, Rick A Adams, Karl Friston

Signature of an anticipatory response in area V1 as modeled by a probabilistic model and a spiking neural network

Bernhard a Kaplan, Mina A Khoei, Anders Lansner, Laurent U Perrinet

Signature of an anticipatory response in area V1 as modeled by a probabilistic model and a spiking neural network

Axonal delays and on-time control of eye movements

Anisotropic connectivity implements motion-based prediction in a spiking neural network

Bernhard a Kaplan, Anders Lansner, Guillaume S Masson, Laurent U Perrinet

Motion-based prediction and development of the response to an 'on the way' stimulus

Mina A Khoei, Giacomo Benvenuti, Frédéric Chavane, Laurent U Perrinet

Smooth Pursuit and Visual Occlusion: Active Inference and Oculomotor Control in Schizophrenia

Rick A Adams, Laurent U Perrinet, Karl Friston

Grabbing, tracking and sniffing as models for motion detection and eye movements

Motion-based prediction is sufficient to solve the aperture problem

Motion-based prediction is sufficient to solve the aperture problem

Guillaume S Masson, Laurent U Perrinet

Motion-based prediction is sufficient to solve the aperture problem

Laurent U Perrinet, Guillaume S Masson

Perceptions as Hypotheses: Saccades as Experiments

Karl Friston, Rick A Adams, Laurent U Perrinet, Michael Breakspear

Role of motion-based prediction in motion extrapolation

Mina A Khoei, Laurent U Perrinet, Guillaume S Masson

Propriétés émergentes d'un modèle de prédiction probabiliste utilisant un champ neural

Pursuing motion illusions: a realistic oculomotor framework for Bayesian inference

Amarender Bogadhi, Anna Montagnini, Pascal Mamassian, Laurent U Perrinet, Guillaume S Masson

Role of motion inertia in dynamic motion integration for smooth pursuit

Mina A Khoei, Laurent U Perrinet, Amarender Bogadhi, Anna Montagnini, Guillaume S Masson

Probabilistic models of the low-level visual system: the role of prediction in detecting motion

Models of low-level vision: linking probabilistic models and neural masses

A recurrent Bayesian model of dynamic motion integration for smooth pursuit

Amarender Bogadhi, Anna Montagnini, Pascal Mamassian, Laurent U Perrinet, Guillaume S Masson

Dynamical emergence of a neural solution for motion integration

Mina A Khoei, Laurent U Perrinet, Guillaume S Masson

Dynamical emergence of a neural solution for motion integration

Laurent U Perrinet, Guillaume S Masson

Probabilistic models of the low-level visual system: the role of prediction in detecting motion

Laurent U Perrinet

Decoding center-surround interactions in population of neurons for the ocular following response

Laurent U Perrinet, Nicole Voges, Jens Kremkow, Guillaume S Masson

Dynamics of distributed 1D and 2D motion representations for short-latency ocular following

Frédéric v Barthélemy, Laurent U Perrinet, Eric Castet, Guillaume S Masson

Decoding the population dynamics underlying ocular following response using a probabilistic framework

Laurent U Perrinet, Guillaume S Masson

Modeling spatial integration in the ocular following response to center-surround stimulation using a probabilistic framework

Laurent U Perrinet, Guillaume S Masson

What adaptive code for efficient spiking representations? A model for the formation of receptive fields of simple cells

Laurent U Perrinet

Dynamical Neural Networks: modeling low-level vision at short latencies

Laurent U Perrinet

Bayesian modeling of dynamic motion integration

Anna Montagnini, Pascal Mamassian, Laurent U Perrinet, Eric Castet, Guillaume S Masson

Modeling spatial integration in the ocular following response using a probabilistic framework

Laurent U Perrinet, Guillaume S Masson

Visual tracking of ambiguous moving objects: A recursive Bayesian model

Anna Montagnini, Pascal Mamassian, Laurent U Perrinet, Guillaume S Masson

Bayesian modeling of dynamic motion integration

Anna Montagnini, Pascal Mamassian, Laurent U Perrinet, Eric Castet, Guillaume S Masson

Input-output transformation in the visuo-oculomotor loop: modeling the ocular following response to center-surround stimulation in a probabilistic framework

Laurent U Perrinet, Frédéric v Barthélemy, Guillaume S Masson

Input-output transformation in the visuo-oculomotor loop: modeling the ocular following response to center-surround stimulation in a probabilistic framework

Dynamics of motion representation in short-latency ocular following: A two-pathways Bayesian model

Laurent U Perrinet, Frédéric v Barthélemy, Eric Castet, Guillaume S Masson

Feature detection using spikes : the greedy approach

Laurent U Perrinet