Visual Neuroscience

Topo Neurosciences Computationnelles

L’intelligence du regard

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

Foveated Retinotopy in CNNs. We represent Left an input image and how it is transformed by foveated retinotopy. We show below a …

🧠 Excited to share our latest research led by Alexandre Lainé and presented this summer at AREADNE 2026! “Population decoding of …

By construction, deep convolutional networks treat all pixels equally. Result: they are energy-hungry, fragile to rotations or zooms, …

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

La vibration des apparences

When Cortical Neurons Talk Sideways: Beyond Feedforward Visual Processing

In this seminar we will challenge the traditional understanding of neuronal connectivity in primary visual cortex. While current …

The retinas of many animals, including humans, have a specialized area of high visual acuity called the fovea, while peripheral regions …

🧠 Excited to share our latest research led by Alexandre Lainé and presented this summer at CNS2025 in beautiful Firenze, Italy! …

Both biological and artificial neural networks inherently balance their performance with their operational cost, which balances their …

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

Dear colleagues, Applications are welcome for a fully funded PhD position Focus of attention: a sensory-motor task for energy reduction …

Artificial neural networks applied to the understanding of biological vision

While foveated vision, a trait shared by many animals including humans, is a major contributor to biological visual performance, it has …

Interactions between machine learning, artificial neural networks and our understanding of biological vision

Aleatoric uncertainty characterizes the variability of features found in natural images, and echoes the epistemic uncertainty …

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

Our daily endeavors occur in a complex visual environment, whose intrinsic variability shapes the way we integrate information to make …

Game theory and brain strategies [2023-01-23] Atelier jeu et cerveau …

Rétinotopie. L’image du tableau “Les Ambassadeurs” de Hans Holbein le Jeune peut être représentée sur une grille régulière représentée …

Neurons in the primary visual cortex are selective to orientation with various degrees of selectivity to the spatial phase, from high …

This poster is presented in the following paper (published in Nature Comm Biology): Hugo Ladret, Nelson Cortes, Lamyae Ikan, Frédéric …

This work extends to natural scenes a previous work on visual search on a simplified task formulated in Emmanuel Daucé, Pierre …

On a daily basis, the primary visual cortex (V1) detects oriented elements from sensory inputs made of orientation distributions. To …

Visual search, that is, the simultaneous localization and detection of a visual target of interest, is a vital task. Applied to the …

Follows a previous work A dual foveal-peripheral visual processing model implements efficient saccade selection Emmanuel Daucé, Pierre …

for visual search see: A dual foveal-peripheral visual processing model implements efficient saccade selection Emmanuel Daucé, Pierre …

In most mammals, the primary visual cortex (V1) processes complex mixtures of orientations to construct an accurate neural …

Horizontal connections in the primary visual cortex of carnivores, ungulates and primates organize on a near-regular lattice. Given the …

Angelo Franciosini (Equipe NeOpTo) a soutenu sa thèse de doctorat intitulée: SDPC : a sparse and predictive model of the early visual system le Mardi 28 septembre 2021 à 13h à 15h30

The primary visual cortex (V1) processes complex mixtures of orientations to build neural representations of our visual environment. It …

The primary visual cortex (V1) processes complex mixtures of orientations to build neural representations of our visual environment. It …

The primary visual cortex (V1) processes complex mixtures of orientations to build neural representations of our everyday visual …

Cells in the primary visual cortex of mammals (V1) have historically been divided into two classes: simple and complex. Simple cells …

In computer vision, the visual search task consists in extracting a scarce and specific visual information (the target) from a large …

Processing of naturalistic motion in early vision

Cells in the primary visual cortex of mammals (V1) have historically been divided into two classes: simple and complex. Simple cells …

What are the neural mechanisms underlying motion integration of translating objects? Visual motion integration is generally conceived …

Within the central nervous system, visual areas are essential in transforming the raw luminous signal into a representation which …

Background: The primary visual cortex (V1) is a key component of the visual system that builds some of the first levels of coherent …

When objects are in motion, the local orientation of their contours and the direction of motion are two essential components of visual …

In computer vision, the visual search task consists in extracting a scarce and specific visual information (the target) from a large …

Traveling waves have recently been observed in different animal species, brain areas and behavioral states. However, it is still unclear what are their functional roles. In the case of cortical visual processing, waves propagate across retinotopic maps and can hereby generate interactions between spatially and temporally separated instances of feedforward driven activity. Such interactions could participate in processing long-range apparent motion stimuli, an illusion for which no clear neuronal mechanisms have yet been proposed. Using this paradigm in awake monkeys, we show that suppressive traveling waves produce to a spatio-temporal normalization of apparent motion stimuli. Our study suggests that cortical waves shape the representation of illusory moving stimulus within retinotopic maps for an straightforward read-out by downstream areas.

Sparse coding holds the idea that signals can be concisely described as a linear mixture of few components (called atoms) picked from a …

A key property of the neurons in the primary visual cortex (V1) is their selectivity to oriented stimuli in the visual field. …

It is widely assumed that visual processing follows a forward sequence of processing steps along a hierarchy of laminar sub-populations …

The selectivity of the visual system to oriented patterns is very well documented in a wide range of species, especially in mammals. In …

Due to its inherent neural delays, the visual system has an outdated access to sensory information about the current position of moving …

La vision utilise un faisceau d’informations de différentes qualités pour atteindre une perception unifiée du monde environnant. …

ANR BalaV1: Balanced states in area V1 (2013–2016)

Connectivité Horizontale et Prédiction de Cohérences dans l’Intégration de Contour et Mouvement dans le Cortex Visuel Primaire

ANR TRAJECTORY (2016/2019).

L’installation ‘‘Elasticité dynamique’’ agit comme un filtre et génère de nouveaux espaces démultipliés, comme un empilement quasi infini d’horizons. Par principe de réflexion, la pièce absorbe l’image de l’environnement et accumule les points de vue ; le mouvement permanent requalifie continuellement ce qui est regardé et entendu.

À la Fondation Vasarely à Aix-en-Provence, Étienne Rey a choisi d’installer dans la salle des Intégrations architectoniques un ballet visuel hypnotique.

Tropique is an immersive installation which puts in link the perception of the space connected to the movement, to the light and to the sound.

Natural scenes generally contain objects in motion. The local orientation of their contours and the direction of motion are two …

Natural scenes generally contain objects in motion. The local orientation of their contours and the direction of motion are two …

Neurons in the primary visual cortex are known for responding vigorously but with high variability to classical stimuli such as …

Making a judgment about the semantic category of a visual scene, such as whether it contains an animal, is typically assumed to involve …

Analysis and interpretation of a visual scene to extract its category, such as whether it contains an animal, is typically assumed to …

As it is confronted to inherent neural delays, how does the visual system create a coherent representation of a rapidly changing …

The question how the visual system is able to create a coherent representation of a rapidly changing environment in the presence of …

see a follow-up: Laurent U Perrinet, James A Bednar (2015). Edge co-occurrences can account for rapid categorization of natural versus …

Predictive coding hypothesizes that the brain explicitly infers upcoming sensory input to establish a coherent representation of the …

Oriented edges in images of natural scenes tend to be aligned in collinear or co-circular arrangements, with lines and smooth curves …

Oriented edges in images of natural scenes tend to be aligned in collinear or co-circular arrangements, with lines and smooth curves …

Oriented edges in images of natural scenes tend to be aligned in collinear or co-circular arrangements, with lines and smooth curves …

Oriented edges in images of natural scenes tend to be aligned in collinear or co-circular arrangements, with lines and smooth curves …

Oriented edges in images of natural scenes tend to be aligned in collinear or co-circular arrangements, with lines and smooth curves …

Neurons in the input layer of primary visual cortex in primates develop edge-like receptive fields. One approach to understanding the …

Short presentation of a large moving pattern elicits an ocular following response that exhibits many of the properties attributed to …

The primary visual cortex (V1) is one of the most studied cortical area in the brain. Together with the retina and the lateral …

Computational Neuroscience: From Representations to Behavior, the Second NeuroComp Marseille Workshop.

Computational Neuroscience is a synthetic, inter-disciplinary approach aiming at understanding cognition by analyzing the mechanisms …

related publications @ FENS 2006, @ NeuroComp 2008 and @ AREADNE 2008

If modern computers are sometimes superior to cognition in some specialized tasks such as playing chess or browsing a large database, …

In the primary visual cortex (V1), single cell responses to simple visual stimuli (gratings) are usually dense but with a high …

I will illustrate in this talk how computational neuroscience may inspire and be inspired by mathematical image processing. Focusing on …

Meanwhile biorthogonal wavelets got a very popular image processing tool, alternative multiresolution transforms have been proposed for …

I will illustrate in this talk how computational neuroscience may inspire and be inspired by mathematical image processing. Focusing on …

We describe the theoretical formulation of a learning algorithm in a model of the primary visual cortex (V1) and present results of the …

relies on log-Gabor filters: Sylvain Fischer, Filip Šroubek, Laurent U Perrinet, Rafael Redondo, Gabriel Cristóbal (2007). …

We describe the theoretical formulation of a learning algorithm in a model of the primary visual cortex (V1) and present results of the …

Computations in a cortical column are characterized by the dynamical, event-based nature of neuronal signals and are structured by the …

We present a biologically plausible model of simple cortical cells as 1) a linear transform representing edges and 2) a non-linear …

Efficient sparse coding of overcomplete transforms remains still anopen problem. Different methods have been proposed in theliterature, …

Low-level perceptual computations may be understood in terms of efficient codes (Simoncelli and Olshausen, 2001, Annual Review of …