Inproceedings

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 …
Last updated on 2025-05-26 Biological Neuroscience, Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
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Artificial neural networks and machine learning applied to the understanding of biological vision
La vibration des apparences
Le travail d’Étienne Rey met en relation des phénomènes naturels et physiques avec notre perception. Ses œuvres se révèlent et se …
2025-04-18 Computational Neuroscience, NeuroAI & Machine Learning
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La vibration des apparences
NeuroSchool PhD Program in Neuroscience: Sparse representations
Sparse coding is a technique used in signal processing and machine learning to represent data in a more concise and efficient manner. …
2025-03-11 Computational Neuroscience, NeuroAI & Machine Learning
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Accurate Detection of Spiking Motifs in Neurobiological Data by Learning Heterogeneous Delays of a Spiking Neural Network
Recently, there has been an increase in interest in exploring the hypothesis that neural activity conveys information through precise …
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Accurate Detection of Spiking Motifs in Neurobiological Data by Learning Heterogeneous Delays of a Spiking Neural Network
Self-Supervised Learning of Spiking Motifs in Neurobiological Data
Timing is essential for neural processing, but evidence for such temporal precision is still lacking. We have developed a theoretical …
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Self-Supervised Learning of Spiking Motifs in Neurobiological Data
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 …
Last updated on 2024-05-13 Biological Neuroscience, Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
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Sparse representations
Sparse coding is a technique used in signal processing and machine learning to represent data in a more concise and efficient manner. …
2024-04-17 Computational Neuroscience, Computer Vision, NeuroAI & Machine Learning
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Artificial neural networks applied to the understanding of biological vision
2024-04-10 Computational Neuroscience, NeuroAI & Machine Learning
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Analyser de larges volumes de données neurobiologiques, vers une approche biomimétique
Related papers A Robust Event-Driven Approach to Always-on Object Recognition Antoine Grimaldi, Victor Boutin, Sio-Hoi Ieng, Ryad …
2024-03-27 Computational Neuroscience, NeuroAI & Machine Learning
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Analyser de larges volumes de données neurobiologiques, vers une approche biomimétique
Event-based vision
Event-based cameras mimic the way biological retinas process visual information: each pixel independently reports brightness changes as …
2023-12-14 Computational Neuroscience, Computer Vision, NeuroAI & Machine Learning
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Event-based vision
Event-based cameras mimic the way biological retinas process visual information: each pixel independently reports brightness changes as …
Last updated on 2023-11-29 Computational Neuroscience, Computer Vision, NeuroAI & Machine Learning
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Event-based vision
The biological retina represents changes in light intensity and communicates them to the brain by means of spikes. Similarly, …
2023-12-01 Computational Neuroscience, Computer Vision, NeuroAI & Machine Learning
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Event-based vision
Accurate Detection of Spiking Motifs by Learning Heterogeneous Delays of a Spiking Neural Network
Poster Session at https://snufa.net/2023/ https://snufa.net/2023/abstracts/laurent-perrinet-accurate.html code: …
Last updated on 2023-09-10 Computational Neuroscience, NeuroAI & Machine Learning
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Time-to-Contact Map by Joint Estimation of Up-to-Scale Inverse Depth and Global Motion using a Single Event Camera
Event cameras asynchronously report brightness changes with a temporal resolution in the order of microseconds, which makes them …
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Time-to-Contact Map by Joint Estimation of Up-to-Scale Inverse Depth and Global Motion using a Single Event Camera
Accurate Detection of Spiking Motifs by Learning Heterogeneous Delays of a Spiking Neural Network
Hybrid Session, Room 2 Chair: Sander Bohté, Sebastian Otte read the proceedings The code is available on GitHub see accompanying …
Last updated on 2023-09-10 Computational Neuroscience, NeuroAI & Machine Learning
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Accurate Detection of Spiking Motifs by Learning Heterogeneous Delays of a Spiking Neural Network
Recently, interest has grown in exploring the hypothesis that neural activity conveys information through precise spiking motifs. To …
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Retinotopy improves the categorisation and localisation of visual objects in CNNs
as was presented at the 32nd International Conference on Artificial Neural Networks (ICANN 2023) in Heraklion (Greece). this …
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Retinotopy improves the categorisation and localisation of visual objects in CNNs
Event-based vision
Event-based cameras mimic the way biological retinas process visual information: each pixel independently reports brightness changes as …
Last updated on 2023-09-05 Computational Neuroscience, Computer Vision, NeuroAI & Machine Learning
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Interactions between machine learning, artificial neural networks and our understanding of biological vision
Last updated on 2023-05-10 Computational Neuroscience, NeuroAI & Machine Learning
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Convolutional Sparse Coding is improved by heterogeneous uncertainty modeling
Aleatoric uncertainty characterizes the variability of features found in natural images, and echoes the epistemic uncertainty …
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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 …
Last updated on 2023-03-29 Biological Neuroscience, Computational Neuroscience, NeuroAI & Machine Learning, Theoretical 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 …
Last updated on 2023-03-29 Biological Neuroscience, Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
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Resilience to sensory uncertainty in the primary visual cortex
Our daily endeavors occur in a complex visual environment, whose intrinsic variability shapes the way we integrate information to make …
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Learning heterogeneous delays of spiking neurons for motion detection
The response of a biological neuron depends largely on the precise timing of presynaptic spikes that reach the basal dendritic tree. …
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Game theory and brain strategies
workshop organisé par les étudiants du master de sciences cognitives les 23 et 24 janvier 2023.
Last updated on 2023-01-24 Computational Neuroscience, NeuroAI & Machine Learning
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Game theory and brain strategies
Retinotopy improves the categorisation and localisation of visual objects in CNNs
as was presented at the Computational Cognitive Neuroscience Society Meeting 2023 in Oxford see a follow-up presentation in: …
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Learning heterogeneous delays of spiking neurons for motion detection
The response of a biological neuron depends largely on the precise timing of presynaptic spikes that reach the basal dendritic tree. …
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Detection of precise spiking motifs using spike-time dependent weight and delay plasticity
The spiking response of a biological neuron depends on the precise timing of afferent spikes. This temporal aspect of the neuronal code …
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Learning heterogeneous delays of spiking neurons for motion detection
for a follow-up, check out Antoine Grimaldi, Camille Besnainou, Hugo Ladret, Laurent U Perrinet (2022). Learning heterogeneous delays …
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Recurrent cortical connectivity in the primary visual cortex supports robust encoding of natural sensory inputs
This poster is presented in the following paper (published in Nature Comm Biology): Hugo Ladret, Nelson Cortes, Lamyae Ikan, Frédéric …
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Ultra-rapid visual search in natural images using active deep learning
This work extends to natural scenes a previous work on visual search on a simplified task formulated in Emmanuel Daucé, Pierre …
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Ultra-rapid visual search in natural images using active deep learning
A resilient neural code in V1 to process natural images
On a daily basis, the primary visual cortex (V1) detects oriented elements from sensory inputs made of orientation distributions. To …
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A resilient neural code in V1 to process natural images
Decoding spiking motifs using neurons with heterogeneous delays
The response of a biological neuron depends largely on the precise timing of presynaptic spikes that reach the basal dendritic tree. …
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Ultra-rapid visual search in natural images using active deep learning
Visual search, that is, the simultaneous localization and detection of a visual target of interest, is a vital task. Applied to the …
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Ultra-rapid visual search in natural images using active deep learning
Which sparsity problem does the brain solve?
Experimental evidence suggests that activity in sensory cortices is sparse in that only few neurons out of a large pool that could …
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Learning heterogeneous delays of Spiking Neurons for motion detection
for a follow-up, check out Learning heterogeneous delays of spiking neurons for motion detection Antoine Grimaldi, Camille Besnainou, …
Last updated on 2022-05-20 NeuroAI & Machine Learning
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Retinotopic mapping improves the reliability of image classification
Follows a previous work A dual foveal-peripheral visual processing model implements efficient saccade selection Emmanuel Daucé, Pierre …
Last updated on 2022-05-20 Biological Neuroscience, Computer Vision, Visual Neuroscience
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Contributions of neuroscience to the detection and localization of objects in visual inputs
for visual search see: A dual foveal-peripheral visual processing model implements efficient saccade selection Emmanuel Daucé, Pierre …
Last updated on 2022-06-16 Biological Neuroscience, NeuroAI & Machine Learning, Visual Neuroscience
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Polychrony detection using heterogeneous delays
Follow this future presentations Learning heterogeneous delays of Spiking Neurons for motion detection PDF Cite URL followed-up as a …
2022-05-19 NeuroAI & Machine Learning
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Réseaux de neurones artificiels et apprentissage machine appliqués à la compréhension de la vision
Visual areas are essential in transforming the raw luminous signal into a representation which efficiently conveys information about …
2022-03-23 Biological Neuroscience, Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
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Statistics of the sparse representations of natural images
In most mammals, the primary visual cortex (V1) processes complex mixtures of orientations to construct an accurate neural …
Last updated on 2021-10-12 Behavioural Neuroscience, Biological Neuroscience, Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience, Visual Neuroscience
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Des illusions aux hallucinations visuelles: une porte sur la perception
Les illusions visuelles sont des créations d’artistes, de scientifiques et plus récemment, grâce aux réseaux sociaux, du grand …
2022-01-12 Behavioural Neuroscience, NeuroAI & Machine Learning
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What You See Is What You Transform: Foveated Spatial Transformers as a Bio-Inspired Attention Mechanism
Convolutional Neural Networks have been considered the go-to option for object recognition in computer vision for the last couple of …
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What You See Is What You Transform: Foveated Spatial Transformers as a Bio-Inspired Attention Mechanism
Decoding orientation distributions from noisy observations in V1
This poster is presented in the following paper (published in Nature Comm Biology): Hugo Ladret, Nelson Cortes, Lamyae Ikan, Frédéric …
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Ultra-fast categorization of images containing animals in vivo and in computo
see a follow-up in: Jean-Nicolas Jérémie, Laurent U Perrinet (2023). Ultra-Fast Image Categorization in biology and in neural models. …
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Ultra-fast categorization of images containing animals in vivo and in computo
From event-based computations to a bio-plausible Spiking Neural Network
We propose a neuromimetic online classifier for always-on digit recognition. To achieve this, we extend an existing event-based …
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Simulating anticipatory activity in a 1D Spiking Neural Network Model
poster number: 94 scheduled on Wednesday, Sep 22, 18:00 CEST. …
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Dynamical processing of orientation precision in the primary visual cortex
The primary visual cortex (V1) processes complex mixtures of orientations to build neural representations of our visual environment. It …
Last updated on 2021-07-12 NeuroAI & Machine Learning, Theoretical Neuroscience, Visual Neuroscience
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A homeostatic gain control mechanism to improve event-driven object recognition
We propose a neuromimetic architecture able to perform pattern recognition. To achieve this, we extended the existing event-based …
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Pooling in a predictive model of V1 explains functional and structural diversity across species
In this talk, I will present the following paper : Pooling in a predictive model of V1 explains functional and structural diversity …
Last updated on 2021-06-14 NeuroAI & Machine Learning, Theoretical Neuroscience
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Dynamical processing of orientation precision in the primary visual cortex
The primary visual cortex (V1) processes complex mixtures of orientations to build neural representations of our visual environment. It …
Last updated on 2021-07-12 Computational Neuroscience, NeuroAI & Machine Learning, Visual Neuroscience
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A robust bio-inspired approach to event-driven object recognition
We propose a neuromimetic architecture able to perform online pattern recognition. To achieve this, we extended the existing …
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Modulation of orientation selectivity by orientation precision
The primary visual cortex (V1) processes complex mixtures of orientations to build neural representations of our everyday visual …
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Visual search as active inference
a follow-up of: Emmanuel Daucé, Pierre Albigès, Laurent U Perrinet (2020). A dual foveal-peripheral visual processing model implements …
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Modelling Complex-cells and topological structure in the visual cortex of mammals using Sparse Predictive Coding
Cells in the primary visual cortex of mammals (V1) have historically been divided into two classes: simple and complex. Simple cells …
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Understanding natural vision using deep predictive coding
Building models which efficiently process images is a great source of inspiration to better understand the processes which underly our …
2020-09-25 Biological Neuroscience, Computational Neuroscience, Computer Vision, NeuroAI & Machine Learning, Theoretical Neuroscience
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Visual search as active inference
Visual search is an essential cognitive ability, offering a prototypical control problem to be addressed with Active Inference. Under a …
2020-09-14 NeuroAI & Machine Learning, Theoretical Neuroscience
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From the retina to action: Understanding visual processing
Visual areas are essential in transforming the raw luminous signal into a representation which efficiently conveys information about …
2020-04-03 Biological Neuroscience, Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
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Modelling Complex-cells and topological structure in the visual cortex of mammals using Sparse Predictive Coding
Cells in the primary visual cortex of mammals (V1) have historically been divided into two classes: simple and complex. Simple cells …
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Des illusions aux hallucinations visuelles: une porte sur la perception
Les illusions visuelles sont des créations d’artistes, de scientifiques et plus récemment, grâce aux réseaux sociaux, du grand …
2020-01-20 Behavioural Neuroscience, NeuroAI & Machine Learning
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Learning dynamics in a neural network model of the primary visual cortex
Background: The primary visual cortex (V1) is a key component of the visual system that builds some of the first levels of coherent …
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A dynamic model for decoding direction and orientation in macaque primary visual cortex
When objects are in motion, the local orientation of their contours and the direction of motion are two essential components of visual …
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Learning where to look: a foveated visuomotor control model
In computer vision, the visual search task consists in extracting a scarce and specific visual information (the target) from a large …
2019-07-15 Behavioural Neuroscience, Biological Neuroscience, Computational Neuroscience, Computer Vision, NeuroAI & Machine Learning, Theoretical Neuroscience, Visual Neuroscience
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Should I stay or should I go? Adaption of human observers to the volatility of visual inputs
Animal behavior has to constantly adapt to changes, for instance when unexpectedly switching the state of an environmental context. For …
2019-04-05 Behavioural Neuroscience, NeuroAI & Machine Learning
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From the retina to action: Understanding visual processing
Visual areas are essential in transforming the raw luminous signal into a representation which efficiently conveys information about …
2019-04-03 Behavioural Neuroscience, Biological Neuroscience, Computational Neuroscience, NeuroAI & Machine Learning, Theoretical Neuroscience
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Sparse Deep Predictive Coding captures contour integration capabilities of the early visual system
Both neurophysiological and psychophysical experiments have pointed out the crucial role of recurrent and feedback connections to …
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Rencontre avec les collégiens marseillais
Le jeudi 10 janvier 2019, je suis venu échanger au côté de Serge Dentin autour de films traitant du rapport fiction/réel, des illusion …
2019-01-10 Computational Neuroscience, NeuroAI & Machine Learning
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A hierarchical, multi-layer convolutional sparse coding algorithm based on predictive coding
Sparse coding holds the idea that signals can be concisely described as a linear mixture of few components (called atoms) picked from a …
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Modelling Complex Cells of Early Visual Cortex using Predictive Coding
see a follow-up in: Victor Boutin, Angelo Franciosini, Frédéric Chavane, Franck Ruffier, Laurent U Perrinet (2021). Sparse Deep …
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Orientation selectivity to synthetic natural patterns in a cortical-like model of the cat primary visual cortex
A key property of the neurons in the primary visual cortex (V1) is their selectivity to oriented stimuli in the visual field. …
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Sparse Deep Predictive Coding to model visual object recognition
see a follow-up in: Victor Boutin, Angelo Franciosini, Frédéric Chavane, Franck Ruffier, Laurent U Perrinet (2021). Sparse Deep …
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Sparse Deep Predictive Coding to model visual object recognition
Top-down connection in Hierarchical Sparse Coding
The brain has to solve inverse problems to correctly interpret sensory data and infer the set of causes that generated the sensory …
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La modélisation biomorphique de la perception visuelle
in “La modélisation de la genèse physico-mathématique du vivant” BIOMORPHISME ET CREATION ARTISTIQUE – Session 3 Date 11 …
2018-10-11 Behavioural Neuroscience, NeuroAI & Machine Learning
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Intervention fête de la science 2018
FÊTE DE LA SCIENCE 2018 : Alcazar / MERLAN L’Association Polly Maggoo http://www.pollymaggoo.org/ met en place tout le long de …
2018-10-10 Computational Neuroscience
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A low-cost, accessible eye tracking framework
Recording eye movements is a technique that attracts an increasing number of scientists, but also in the general public. Indeed, this …
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ANEMO: Quantitative tools for the ANalysis of Eye MOvements
see a write-up in Chloé Pasturel, Anna Montagnini, Laurent U Perrinet (2020). Humans adapt their anticipatory eye movements to the …
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ANEMO: Quantitative tools for the ANalysis of Eye MOvements
Estimating and anticipating a dynamic probabilistic bias in visual motion direction
Humans are able to accurately track a moving object with a combination of saccades and smooth eye movements. These movements allow …
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Estimating and anticipating a dynamic probabilistic bias in visual motion direction
Humans are able to accurately track a moving object with a combination of saccades and smooth eye movements. These movements allow …
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From biological vision to unsupervised hierarchical sparse coding
The formation of connections between neural cells is essentially emerging from an unsupervised learning process. During the development …
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M2APix: a bio-inspired auto-adaptive visual sensor for robust ground height estimation
This paper presents for the first time the embedded stand-alone version of the bio-inspired M2APix (Michaelis-Menten auto-adaptive …
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On the Origins of Hierarchy in Visual Processing
It is widely assumed that visual processing follows a forward sequence of processing steps along a hierarchy of laminar sub-populations …
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Selectivity to oriented patterns of different precisions
The selectivity of the visual system to oriented patterns is very well documented in a wide range of species, especially in mammals. In …
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Selectivity to oriented patterns of different precisions
Speed uncertainty and motion perception with naturalistic random textures
It is still not fully understood how visual system integrates motion energy across different spatial and temporal frequencies to build …
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Unsupervised Hierarchical Sparse Coding algorithm inspired by Biological Vision
The brain has to solve inverse problems to correctly interpret sensory data and infer the set of causes that generated the sensory …
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Participation au jury
FESTIVAL INTERFÉRENCES​ Cinéma Documentaire et Débat Public FESTIVAL INTERFÉRENCES​ Le collectif Scènes Publiques composé de citoyens, …
2017-11-17 Computational Neuroscience, NeuroAI & Machine Learning
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Controlling an aerial robot with human gestures using bio-inspired algorithm
Improve performances of existing recognition computer vision algorithms with biological concepts. The gain are expected in the …
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Dynamic modulation of volatility by reward contingencies: effects on anticipatory smooth eye movement
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Efficient learning of sparse image representations using homeostatic regulation
One core advantage of sparse representations is the efficient coding of complex signals using compact codes. For instance, it allows …
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Efficient learning of sparse image representations using homeostatic regulation
One core advantage of sparse representations is the efficient coding of complex signals using compact codes. For instance, it allows …
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Estimating and anticipating a dynamic probabilistic bias in visual motion direction
see a write-up in Chloé Pasturel, Anna Montagnini, Laurent U Perrinet (2020). Humans adapt their anticipatory eye movements to the …
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Expériences autour de la perception de la forme en art et science
La vision utilise un faisceau d’informations de différentes qualités pour atteindre une perception unifiée du monde environnant. …
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Expériences autour de la perception de la forme en art et science
How the dynamics of human smooth pursuit is influenced by speed uncertainty
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Voluntary tracking the moving clouds : Effects of speed variability on human smooth pursuit
The properties of motion processing for driving smooth eye movements have bee investigated using simple, artificial stimuli such as …
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Participation au jury et entretien avec Clara Delmon
RENCONTRES INTERNATIONALES SCIENCES & CINÉMAS cinéma les Variétés …
2016-11-20 Computational Neuroscience, NeuroAI & Machine Learning
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Biologically-inspired characterization of sparseness in natural images
Natural images follow statistics inherited by the structure of our physical (visual) environment. In particular, a prominent facet of …
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Operant reinforcement versus reward expectancy: effects on anticipatory eye movements
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Les illusions visuelles, un révélateur du fonctionnement de notre cerveau
Les illusions visuelles sont des créations d’artistes, de scientifiques et plus récemment, grâce aux réseaux sociaux, du grand …
2016-04-28 Behavioural Neuroscience, NeuroAI & Machine Learning
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Les illusions visuelles, un révélateur du fonctionnement de notre cerveau
Les illusions visuelles, un révélateur du fonctionnement de notre cerveau
Ce lundi 25 avril de 9h à 12h, je suis venu échanger au côté de Serge Dentin autour de films traitant du rapport fiction/réel, des …
2016-04-25 Behavioural Neuroscience, NeuroAI & Machine Learning
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A dynamic model for decoding direction and orientation in macaque primary visual cortex
Natural scenes generally contain objects in motion. The local orientation of their contours and the direction of motion are two …
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A dynamic model for decoding direction and orientation in macaque primary visual cortex
Natural scenes generally contain objects in motion. The local orientation of their contours and the direction of motion are two …
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