Paper-Conference

Working Memory in Recurrent Spiking Neural Networks With Heterogeneous Synaptic Delays
Optimal Transport Theory to extract Spiking Motifs
Whether cortical neurons encode information through firing rates or precise spike timing remains a central question in neuroscience. …
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Working Memory in Recurrent Spiking Neural Networks Using Heterogeneous Synaptic Delays
Working memory — the ability to store and retrieve precise temporal patterns of neural activity —– remains a fundamental …
2026-04-16 Computational Neuroscience
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Learning Working Memory in Recurrent Spiking Neural Networks Using Heterogeneous Delays
Dans l’intelligence du regard : l’art révèle la diversité de notre vision
La vision reste un paradoxe : comment un processus aussi complexe qu’apprendre à « faire sens de nos sens » peut-il être si simple à …
2026-04-11 Computational Neuroscience
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Dans l’intelligence du regard : l’art révèle la diversité de notre vision
Spiking neural nets

This repository contains all the material for this practical course about the “Introduction to SNN torch”.

2026-03-24 Computational Neuroscience
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Artificial neural networks and machine learning applied to the understanding of biological vision
Visual areas are essential in transforming the raw luminous signal into a representation which efficiently conveys information about …
2026-03-05 Computational Neuroscience
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Recréer des réseaux neuronaux pour améliorer la compréhension de notre cerveau

Rendez-vous ce mardi 10 février 2026 / 9h-10h30 pour plonger dans le monde fascinant des neurosciences.

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[BIOMIMÉTISME & NEUROSCIENCES] Recréer des réseaux neuronaux pour améliorer la compréhension de notre cerveau.

2026-02-10 Computational Neuroscience
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Recréer des réseaux neuronaux pour améliorer la compréhension de notre cerveau
Al for visual processing and energy-efficient algorithms
2026-02-03 NeuroAI & Machine Learning
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Al for visual processing and energy-efficient algorithms
Neurosciences and sparsity
Sparse representations in biological vision applied to the effciency of machine learning.
2026-01-29 Computational Neuroscience
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Lab Tour for Art - Perception Collaboration
By construction, deep convolutional networks treat all pixels equally. Result: they are energy-hungry, fragile to rotations or zooms, …
2026-01-01 Computational Neuroscience
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Lab Tour for Art - Perception Collaboration
Physiological state Monitoring: a Riemannian Geometry based-model
This study investigates the use of Riemannian geometry to detect and monitor physiological states such as mental workload (MWL) from an …
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Population decoding of visual motion direction

🧠 Excited to share our latest research led by Alexandre Lainé and presented this summer at AREADNE 2026!

“Population decoding of visual motion direction”

Our work explores how populations of neurons in the primary visual cortex (V1) of marmoset monkeys encode visual motion direction, with a particular focus on understanding how uncertainty influences this neural decoding process. Key highlights:

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A New Look for Convolutional Deep Networks
By construction, deep convolutional networks treat all pixels equally. Result: they are energy-hungry, fragile to rotations or zooms, …
2025-12-12 NeuroAI & Machine Learning
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A New Look for Convolutional Deep Networks
By construction, deep convolutional networks treat all pixels equally. Result: they are energy-hungry, fragile to rotations or zooms, …
2025-12-02 NeuroAI & Machine Learning
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Detection of spiking motifs of arbitrary length in neural activity using bounded synaptic delays
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Mislocalization by Design: The Flash-Lag Effect as Prediction
Why do we sometimes misjudge where visual objects are? This talk explores how predictive processing may cause systematic perceptual …
2025-10-16 NeuroAI & Machine Learning
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Conférence immersive : La vision, réalité ou perception ?
Ouvrez grand les yeux… mais méfiez-vous de ce qu’ils vous montrent. Cette conférence immersive vous emmène dans un voyage fascinant au …
2025-06-12 Computational Neuroscience
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Conférence immersive : La vision, réalité ou perception ?
Ciné-Sciences : Ouvrez grand les yeux
Ouvrez grand les yeux… mais méfiez-vous de ce qu’ils vous montrent. Cette séance cinéma vous emmène dans un voyage fascinant au cœur du …
2025-06-10 Computational Neuroscience
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Ciné-Sciences : Ouvrez grand les yeux
Robust Unsupervised Learning of Spike Patterns with Optimal Transport Theory
Temporal sequences are an important feature of neural information processing in biology. Neurons can fire a spike with millisecond …
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Robust Unsupervised Learning of Spike Patterns with Optimal Transport Theory
Qu'est-ce que les Neurosciences peuvent apporter à l'Intelligence Artificielle ?
L’intelligence artificielle, plus précisément l’apprentissage profond, a fait d’énormes progrès ces dernières années. …
2025-02-14 NeuroAI & Machine Learning
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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 theory suggests that neurons connect preferentially to others with similar orientation preferences, I will present evidence for a more complex connectivity pattern based on a distance-dependent rule: short-range connections show a like-to-like bias, while long-range connections connect more widely. This revised model better explains how the visual cortex processes complex stimuli and accounts for observed variations in neuronal interactions at different scales.

2025-02-11 NeuroAI & Machine Learning
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How and why foveated retinotopy provides efficient vision
The retinas of many animals, including humans, have a specialized area of high visual acuity called the fovea, while peripheral regions …
2025-01-08 NeuroAI & Machine Learning
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Classification of Mental Workload Spatial Effects using Riemannian Manifold
This study investigates the use of Riemannian geometry to classify mental workload from an EEG dataset collected in an aeronautical …
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Classification of Mental Workload Spatial Effects using Riemannian Manifold
Integrating the What and Where Visual Pathways to Improve CNN Categorisation
Convolutional Neural Networks (CNNs) have been widely used for categorisation tasks over the past decades. Many studies have attempted …
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Integrating the What and Where Visual Pathways to Improve CNN Categorisation
Population decoding of visual motion direction in V1 marmoset monkey : effects of uncertainty

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

“Population decoding of visual motion direction in V1 marmoset monkey: effects of uncertainty”

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Population decoding of visual motion direction in V1 marmoset monkey : effects of uncertainty
NeuroAI: interactions multiples entre Neurosciences et Intelligence artificielle
  • présentation de 15:50:00 à 16:20:00
2024-11-18 NeuroAI & Machine Learning
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Robots aériens agiles bio-mimetiques pour le vol en conditions réelles: Enjeux pour l'IA embarqué
2024-09-09 NeuroAI & Machine Learning
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An open-source vision-science tool for the auto-regressive generation of dynamic stochastic textures Motion Clouds
Motion Clouds are a generative model for naturalistic visual stimulation that offer full parametric control and more naturalism than …
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Diverse Neuronal Responses to Visual Precision in Cat Cortical Area 21a: Unraveling the Complexity of Orientation Processing
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Retinotopy in CNN's implements Efficient Visual Search
Retinotopy in CNN's implements Efficient Visual Search
Retinotopy in CNN's implements Efficient Visual Search
While foveated vision, a trait shared by many animals including humans, is a major contributor to biological visual performance, it has …
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Retinotopy in CNN's implements Efficient Visual Search