Spiking-Neural-Networks

PyNN: A Common Interface for Neuronal Network Simulators
Andrew P Davison, Daniel Bruderle, Jochen Eppler, Jens Kremkow, Eilif Muller, Dejan Pecevski, Laurent U Perrinet, Pierre Yger
PDF Cite Project DOI URL HAL
What adaptive code for efficient spiking representations? A model for the formation of receptive fields of simple cells
Laurent U Perrinet
PDF Cite
What efficient code for adaptive spiking representations?
Cite URL
PyNN: towards a universal neural simulator API in Python
Andrew P Davison, Pierre Yger, Jens Kremkow, Laurent U Perrinet, Eilif Muller
Cite Project DOI URL
Contrast sensitivity adaptation in a virtual spiking retina and its adequation with mammalians retinas
Adrien Wohrer, Guillaume S Masson, Laurent U Perrinet, Pierre Kornprobst, Thierry Vieville
Cite
Dynamical contrast gain control mechanisms in a layer 2/3 model of the primary visual cortex
Laurent U Perrinet, Jens Kremkow
Cite
Efficient representation of natural images using local cooperation
Sylvain Fischer, Rafael Redondo, Laurent U Perrinet, Gabriel Cristóbal
Cite
Coding static natural images using spiking event times: do neurons cooperate?
Laurent U Perrinet, Manuel Samuelides, Simon Thorpe
PDF Cite DOI URL arXiv
Feature detection using spikes : the greedy approach
Laurent U Perrinet
Cite DOI URL arXiv
Finding Independent Components using spikes : a natural result of Hebbian learning in a sparse spike coding scheme
Laurent U Perrinet
Cite DOI URL
Coherence detection in a spiking neuron via Hebbian learning
Laurent U Perrinet, Manuel Samuelides
PDF Cite DOI URL
Sparse Image Coding Using an Asynchronous Spiking Neural Network
Laurent U Perrinet, Manuel Samuelides
Cite
2020-12-10_agileneurobot_anr
2022-07-01_grimaldi-22-areadne
Project