Computational Neuroscience

Sparse Gabor wavelets by local operations
Efficient sparse coding of overcomplete transforms remains still anopen problem. Different methods have been proposed in theliterature, …
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Dynamics of motion representation in short-latency ocular following: A two-pathways Bayesian model
The integration of information is essential to measure the exact 2D motion of a surface from both local ambiguous 1D motion produced by …
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Efficient representation of natural images using local cooperation
Low-level perceptual computations may be understood in terms of efficient codes (Simoncelli and Olshausen, 2001, Annual Review of …
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Efficient Source Detection Using Integrate-and-Fire Neurons
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Efficient Source Detection Using Integrate-and-Fire Neurons
Coding static natural images using spiking event times: do neurons cooperate?
To understand possible strategies of temporal spike coding in the central nervous system, we study functional neuromimetic models of …
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Coding static natural images using spiking event times: do neurons cooperate?
Feature detection using spikes : the greedy approach
A goal of low-level neural processes is to build an efficient code extracting the relevant information from the sensory input. It is …
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Feature detection using spikes : the greedy approach
Sparse spike coding in an asynchronous feed-forward multi-layer neural network using matching pursuit
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Finding Independent Components using spikes : a natural result of Hebbian learning in a sparse spike coding scheme
To understand possible strategies of temporal spike coding in the central nervous system, we study functional neuromimetic models of …
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Comment déchiffrer le code impulsionnel de la vision ? Étude du flux parallèle, asynchrone et épars dans le traitement visuel ultra-rapide
Le jury était consistué (de gauche à droite) de Jeanny Hérault (Rapporteur), Michel Imbert (Président), Yves Burnod (Rapporteur, absent de la photo), Manuel Samuelides (Directeur de thèse) et Simon Thorpe (Co-directeur de thèse).
Le jury était consistué (de gauche à droite) de Jeanny Hérault (Rapporteur), Michel Imbert (Président), Yves Burnod (Rapporteur, absent de la photo), Manuel Samuelides (Directeur de thèse) et Simon Thorpe (Co-directeur de thèse).
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Emergence of filters from natural scenes in a sparse spike coding scheme
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Emergence of filters from natural scenes in a sparse spike coding scheme
Coherence detection in a spiking neuron via Hebbian learning
It is generally assumed that neurons in the central nervous system communicate through temporal firing patterns. As a first step, we …
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Coherence detection in a spiking neuron via Hebbian learning
Sparse Image Coding Using an Asynchronous Spiking Neural Network
*Progressive reconstruction of a static image using spikes in a Laplacian pyramid.*
Progressive reconstruction of a static image using spikes in a Laplacian pyramid.
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Visual Strategies for Sparse Spike Coding
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Visual Strategies for Sparse Spike Coding
Network of integrate-and-fire neurons using Rank Order Coding A: how to implement spike timing dependant plasticity
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Network of integrate-and-fire neurons using Rank Order Coding B: spike timing dependant plasticity and emergence of orientation selectivity
Rank Order Coding is an alternative to conventional rate coding schemes that uses the order in which a neuron’s inputs fire to …
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A generative model for Spike Time Dependent Hebbian Plasticity
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Apprentissage hebbien d'un reseau de neurones asynchrone a codage par rang

Travail de master sur la STDP.

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