Bayesian-Modelling

Artificial neural networks and machine learning applied to the understanding of biological vision

Foveated Retinotopy Improves Classification and Localization in CNNs

Jean-Nicolas Jérémie, Emmanuel Daucé, Laurent U Perrinet

2026-01-29-emergences

Foveal Retinotopy and Dual Pathways: A Computational Model for Active Visual Search

Jean-Nicolas Jérémie

Soutenance de Jean-Nicolas Jérémie "Foveal Retinotopy and Dual Pathways: A Computational Model for Active Visual Search"

Artificial neural networks and machine learning applied to the understanding of biological vision

2025-03-11-phd-program-sparse-representations

2025-02-11-neuromath

How and why foveated retinotopy provides efficient vision

Integrating the What and Where Visual Pathways to Improve CNN Categorisation

Jean-Nicolas Jérémie, Emmanuel Daucé, Laurent U Perrinet

Artificial neural networks and machine learning applied to the understanding of biological vision

PhD thesis 'Focus of attention: a sensory-motor task for energy reduction in spiking neural networks'

2024-04-17-phd-program-sparse-representations

2023-11-07-snufa.md

Emergences (2023 / 2027)

2023-09-27_icann.md

Cortical recurrence supports resilience to sensory variance in the primary visual cortex

Hugo Ladret, Nelson Cortes, Lamyae Ikan, Frédéric Chavane, Christian Casanova, Laurent U Perrinet

Artificial neural networks and machine learning applied to the understanding of biological vision

Artificial neural networks and machine learning applied to the understanding of biological vision

Resilience to sensory uncertainty in the primary visual cortex

Hugo Ladret, Nelson Cortes, Lamyae Ikan, Frédéric Chavane, Christian Casanova, Laurent U Perrinet

Learning heterogeneous delays of spiking neurons for motion detection

Antoine Grimaldi, Laurent U Perrinet

Game theory and brain strategies

Learning heterogeneous delays of spiking neurons for motion detection

Antoine Grimaldi, Camille Besnainou, Hugo Ladret, Laurent U Perrinet

Decoding spiking motifs using neurons with heterogeneous delays

Antoine Grimaldi, Camille Besnainou, Hugo Ladret, Laurent U Perrinet

Retinotopic mapping improves the reliability of image classification

Réseaux de neurones artificiels et apprentissage machine appliqués à la compréhension de la vision

Statistics of the sparse representations of natural images

ANR ACES (2022/2026)

Visual search as active inference

Emmanuel Daucé, Laurent U Perrinet

Modelling Complex-cells and topological structure in the visual cortex of mammals using Sparse Predictive Coding

Angelo Franciosini, Victor Boutin, Laurent U Perrinet

Visual search as active inference

A dual foveal-peripheral visual processing model implements efficient saccade selection

Emmanuel Daucé, Pierre Albigès, Laurent U Perrinet

ANR PRIOSENS (2021/2025)

From the retina to action: Understanding visual processing

Modelling Complex-cells and topological structure in the visual cortex of mammals using Sparse Predictive Coding

Angelo Franciosini, Victor Boutin, Laurent U Perrinet

Effect of top-down connections in Hierarchical Sparse Coding

Victor Boutin, Angelo Franciosini, Franck Ruffier, Laurent U Perrinet

Humans adapt their anticipatory eye movements to the volatility of visual motion properties

Chloé Pasturel, Anna Montagnini, Laurent U Perrinet

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

Laurent U Perrinet

Learning where to look: a foveated visuomotor control model

Should I stay or should I go? Humans adapt to the volatility of visual motion properties, and know about it

2019-05-20: Symposium on Active Inference at NeuroFrance 2019

Should I stay or should I go? Adaption of human observers to the volatility of visual inputs

From the retina to action: Understanding visual processing

From the retina to action: Predictive processing in the visual system

A hierarchical, multi-layer convolutional sparse coding algorithm based on predictive coding

Angelo Franciosini, Victor Boutin, Laurent U Perrinet

Top-down connection in Hierarchical Sparse Coding

Victor Boutin, Angelo Franciosini, Franck Ruffier, Laurent U Perrinet

Bayesian Modeling of Motion Perception using Dynamical Stochastic Textures

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

Principles and psychophysics of Active Inference in anticipating a dynamic, switching probabilistic bias

2018-04-05 : *Probabilities and Optimal Inference to understand the Brain* Workshop

2018-03-26 : PhD Program: course in Computational Neuroscience

Estimating and anticipating a dynamic probabilistic bias in visual motion direction

Estimating and anticipating a dynamic probabilistic bias in visual motion direction

Laurent U Perrinet, Chloé Pasturel, Anna Montagnini

Estimating and anticipating a dynamic probabilistic bias in visual motion direction

Chloé Pasturel, Anna Montagnini, Laurent U Perrinet

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

Mina A Khoei, Guillaume S Masson, Laurent U Perrinet

Tutorial: Active inference for eye movements: Bayesian methods, neural inference, dynamics

Estimating and anticipating a dynamic probabilistic bias in visual motion direction

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

Eye movements as a model for active inference

ANR Horizontal-V1 (2017/2021)

ANR PredictEye (2018/2020)

PhD ICN (2017 / 2021)

Testing the odds of inherent vs. observed overdispersion in neural spike counts

Wahiba Taouali, Giacomo Benvenuti, Pascal Wallisch, Frédéric Chavane, Laurent U Perrinet

Compensation of oculomotor delays in the visual system's network

Laurent U Perrinet, Rick A Adams, Karl Friston

Effects of motion predictability on anticipatory and visually-guided eye movements: a common prior for sensory processing and motor control?

Anna Montagnini, Jean-Bernard Damasse, Laurent U Perrinet, Guillaume S Masson

Motion-based prediction with neuromorphic hardware

Sparse Models for Computer Vision

Laurent U Perrinet

Motion-based prediction with neuromorphic hardware

Anticipatory smooth eye movements and reinforcement

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

Sparse Coding Of Natural Images Using A Prior On Edge Co-Occurences

Laurent U Perrinet, James A Bednar

Edge co-occurrences can account for rapid categorization of natural versus animal images

Laurent U Perrinet, James A Bednar

On overdispersion in neuronal evoked activity

Wahiba Taouali, Giacomo Benvenuti, Pascal Wallisch, Frédéric Chavane, Laurent U Perrinet

Active inference, eye movements and oculomotor delays

Laurent U Perrinet, Rick A Adams, Karl Friston

Une Approche Computationnelle de La Dépendance Au Mouvement Du Codage de La Position Dans La Système Visuel

Mina Aliakbari Khoei

Motion-based prediction model for flash lag effect

Mina A Khoei, Laurent U Perrinet, Guillaume S Masson

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

WP5 - Demo 1.3 : Spiking model of motion-based prediction

Demo 1, Task4: Implementation of models showing emergence of cortical fields and maps

Motion-based prediction explains the role of tracking in motion extrapolation

Mina A Khoei, Guillaume S Masson, Laurent U Perrinet

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

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

Active inference, eye movements and oculomotor delays

Laurent U Perrinet, Rick A Adams, Karl Friston

Active inference, eye movements and oculomotor delays

Laurent U Perrinet, Rick A Adams, Karl Friston

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

Rick A Adams, Laurent U Perrinet, Karl Friston

Edge statistics in natural images versus laboratory animal environments: implications for understanding lateral connectivity in V1

Apparent motion in V1 - Probabilistic approaches

Edge statistics in natural images versus laboratory animal environments: implications for understanding lateral connectivity in V1

Motion-based prediction is sufficient to solve the aperture problem

Active inference, smooth pursuit and oculomotor delays

Laurent U Perrinet, Rick A Adams, Karl Friston

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

Edge statistics in natural images versus laboratory animal environments: implications for understanding lateral connectivity in V1

Edge statistics in natural images versus laboratory animal environments: implications for understanding lateral connectivity in V1

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

Edge statistics in natural images versus laboratory animal environments: implications for understanding lateral connectivity in V1

Laurent U Perrinet, David Fitzpatrick, James A Bednar

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

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

Laurent U Perrinet

Decoding low-level neural information to track visual motion

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

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