Spiking-Neural-Networks

Laurent U Perrinet

Working Memory in Recurrent Spiking Neural Networks With Heterogeneous Synaptic Delays

Laurent U Perrinet

Detection of spiking motifs of arbitrary length in neural activity using bounded synaptic delays

Thomas Kronland-Martinet, Stéphane Viollet, Laurent U Perrinet

Working Memory in SNNs

Working Memory in Recurrent Spiking Neural Networks Using Heterogeneous Synaptic Delays

Working Memory in SNNs

Learning Working Memory in Recurrent Spiking Neural Networks Using Heterogeneous Delays

Laurent U Perrinet

Spiking neural nets

2026-03-05-ue-natural-cognition

2026-02-10-biomplus

2026-02-03-ai-and-neuroscience-day

2026-01-29-emergences

Open PhD Position in Computational & Systems Neuroscience : 'Neuromodulatory control of predictive processing in visual cortical circuits'

Working Memory with Polychronous Chains

Laurent U Perrinet

Detection of spiking motifs of arbitrary length in neural activity using bounded synaptic delays

Thomas Kronland-Martinet, Stéphane Viollet, Laurent U Perrinet

2025-05-26-master-m-4-nc

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

2025-02-14-supaero

2025-02-11-neuromath

2024-11-18-journee-biomometisme

A Robust Event-Driven Approach to Always-on Object Recognition

Antoine Grimaldi, Victor Boutin, Sio-Hoi Ieng, Ryad Benosman, Laurent U Perrinet

2024-09-09-agileneurobot-anr

Accurate Detection of Spiking Motifs in Neurobiological Data by Learning Heterogeneous Delays of a Spiking Neural Network

Laurent U Perrinet

Self-Supervised Learning of Spiking Motifs in Neurobiological Data

Adrien Fois, Laurent U Perrinet

Soutenance de thèse Antoine Grimaldi

2024-05-13-master-m-4-nc

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

2024-04-10-ue-neurosciences-computationnelles

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

2024-03-27-emergences.md

2024-02-05-udem.md

Alexandre Lainé

2023-12-14-jraf.md

2023-12-01-biocomp.md

Accurate Detection of Spiking Motifs by Learning Heterogeneous Delays of a Spiking Neural Network

2023-11-07-snufa.md

Réseaux de Neurones Impulsionnels Pour La Vision Embarquée Basée Sur Les Événements

Emergences (2023 / 2027)

Accurate Detection of Spiking Motifs by Learning Heterogeneous Delays of a Spiking Neural Network

2023-09-27_icann.md

Accurate Detection of Spiking Motifs by Learning Heterogeneous Delays of a Spiking Neural Network

Laurent U Perrinet

Learning heterogeneous delays in a layer of spiking neurons for fast motion detection

Antoine Grimaldi, Laurent U Perrinet

2023-09-08_fresnel.md

2023-05-10-phd-program_neurosciences-computationnelles.md

Convolutional Sparse Coding is improved by heterogeneous uncertainty modeling

Hugo Ladret, Laurent U Perrinet

Postdoc position "Accurate detection of precise spiking motifs in neurobiological data"

2023-04-05-ue-neurosciences-computationnelles

2023-04-03-master-m-4-nc

Learning heterogeneous delays of spiking neurons for motion detection

Antoine Grimaldi, Laurent U Perrinet

Precise spiking motifs in neurobiological and neuromorphic data

Antoine Grimaldi, Amélie Gruel, Camille Besnainou, Jean-Nicolas Jérémie, Jean Martinet, Laurent U Perrinet

Learning heterogeneous delays of spiking neurons for motion detection

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

Detection of precise spiking motifs using spike-time dependent weight and delay plasticity

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

Polychronies (2022 / 2025)

Learning heterogeneous delays of spiking neurons for motion detection

Antoine Grimaldi, Laurent U Perrinet

Ultra-rapid visual search in natural images using active deep learning

Jean-Nicolas Jérémie, Emmanuel Daucé, Laurent U Perrinet

Decoding spiking motifs using neurons with heterogeneous delays

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

Ultra-rapid visual search in natural images using active deep learning

Jean-Nicolas Jérémie, Emmanuel Daucé, Laurent U Perrinet

Learning heterogeneous delays of Spiking Neurons for motion detection

2022-03-23_UE-neurosciences-computationnelles

From event-based computations to a bio-plausible Spiking Neural Network

Antoine Grimaldi, Victor Boutin, Sio-Hoi Ieng, Ryad Benosman, Laurent U Perrinet

Simulating anticipatory activity in a 1D Spiking Neural Network Model

Alberto Arturo Vergani, Laurent U Perrinet

ANR AgileNeuRobot (2021/2025)

PhD offer "Ultra-fast vision using Spiking Neural Networks"

Anticipatory Responses along Motion Trajectories in Awake Monkey Area V1

Giacomo Benvenuti, Sandrine Chemla, Arjan Boonman, Laurent U Perrinet, Guillaume S Masson, Frédéric Chavane

Learning dynamics in a neural network model of the primary visual cortex

Hugo Ladret, Laurent U Perrinet

Postdoc position on Visual computations using Spatio-temporal Diffusion Kernels and Traveling Waves

APROVIS3D (2019/2023)

SpikeAI: laureat du Défi Biomimétisme (2019)

Kiana Mansour-Pour

Modelling spiking neural networks using Brian, Nest and pyNN

An adaptive homeostatic algorithm for the unsupervised learning of visual features

Laurent U Perrinet

Orientation selectivity to synthetic natural patterns in a cortical-like model of the cat primary visual cortex

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

Selectivity to oriented patterns of different precisions

Hugo Ladret, Laurent U Perrinet

Efficient learning of sparse image representations using homeostatic regulation

Victor Boutin, Franck Ruffier, Laurent U Perrinet

Efficient learning of sparse image representations using homeostatic regulation

Victor Boutin, Franck Ruffier, Laurent U Perrinet

Modelling the dynamics of cognitive processes: from the Bayesian brain to particles

ANR CausaL (2018/2020)

ANR Horizontal-V1 (2017/2021)

ANR REM (2013/2016)

DOC2AMU (2016/2019)

Elasticité dynamique

Proverbes Et Citations

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

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

Push-Pull Receptive Field Organization and Synaptic Depression: Mechanisms for Reliably Encoding Naturalistic Stimuli in V1

Jens Kremkow, Laurent U Perrinet, Cyril Monier, Jose-Manuel Alonso, Ad M Aertsen, Yves Frégnac, Guillaume S Masson

On overdispersion in neuronal evoked activity

Wahiba Taouali, Giacomo Benvenuti, Pascal Wallisch, Frédéric Chavane, 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

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

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

Complex dynamics in recurrent cortical networks based on spatially realistic connectivities

Nicole Voges, Laurent U Perrinet

Motion-based prediction is sufficient to solve the aperture problem

Laurent U Perrinet, Guillaume S Masson

2010-06-22 : CodeJamNr4

Functional consequences of correlated excitatory and inhibitory conductances in cortical networks

Jens Kremkow, Laurent U Perrinet, Guillaume S Masson, Ad M Aertsen

Diffraction monochromatique, spectre audiographique