Spike

Testing the odds of inherent vs. observed overdispersion in neural spike counts
The repeated presentation of an identical visual stimulus in the receptive field of a neuron may evoke different spiking patterns at …
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Anisotropic connectivity implements motion-based prediction in a spiking neural network
Predictive coding hypothesizes that the brain explicitly infers upcoming sensory input to establish a coherent representation of the …
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Adaptive Sparse Spike Coding : applications of Neuroscience to the compression of natural images
If modern computers are sometimes superior to cognition in some specialized tasks such as playing chess or browsing a large database, …
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Adaptive Sparse Spike Coding : applications of Neuroscience to the compression of natural images
What adaptive code for efficient spiking representations? A model for the formation of receptive fields of simple cells
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What adaptive code for efficient spiking representations? A model for the formation of receptive fields of simple cells
Dynamical Neural Networks: modeling low-level vision at short latencies
The machinery behind the visual perception of motion and the subsequent sensori-motor transformation, such as in ocular following …
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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
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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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