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 each trial. Probabilistic methods are essential to understand the functional role of this variance within the neural …

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 world. Although it is becoming generally accepted, it is not clear on which level spiking neural networks may …

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, they can't beat the efficiency of biological vision for such simple tasks as recognizing a relative or following an …

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 response (OFR), is confronted to uncertainties which are efficiently resolved in the primate's visual system. We may …

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 visual processing for static images. We will first present the retinal model which was introduced by Van Rullen and …

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 believed that this is implemented in cortical areas by elementary inferential computations dynamically extracting the …

Comment déchiffrer le code impulsionnel de la vision ? Étude du flux parallèle, asynchrone et épars dans le traitement visuel ultra-rapide

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 will study the learning of a layer of realistic neurons in the particular case where the relevant messages are formed …