Coding Decoding

A dynamic model for decoding direction and orientation in macaque primary visual cortex
When objects are in motion, the local orientation of their contours and the direction of motion are two essential components of visual …
PDF Cite URL
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 …
Cite DOI URL HAL
A dynamic model for decoding direction and orientation in macaque primary visual cortex
Natural scenes generally contain objects in motion. The local orientation of their contours and the direction of motion are two …
Cite DOI URL
A dynamic model for decoding direction and orientation in macaque primary visual cortex
Natural scenes generally contain objects in motion. The local orientation of their contours and the direction of motion are two …
PDF Cite DOI
Sparse Coding Of Natural Images Using A Prior On Edge Co-Occurences
Oriented edges in images of natural scenes tend to be aligned in co-linear or co-circular arrangements, with lines and smooth curves …
Cite DOI URL
On overdispersion in neuronal evoked activity
The repeated presentation of an identical visual stimulus in the receptive field of a neuron may evoke different spiking patterns at …
Cite
A Simple Model of Orientation Encoding Accounting For Multivariate Neural Noise
Cite
A Simple Model of Orientation Encoding Accounting For Multivariate Neural Noise
Cite
Role of homeostasis in learning sparse representations
Neurons in the input layer of primary visual cortex in primates develop edge-like receptive fields. One approach to understanding the …
PDF Cite DOI Hal Code URL arXiv
Role of homeostasis in learning sparse representations
Functional consequences of correlated excitatory and inhibitory conductances in cortical networks
Neurons in the neocortex receive a large number of excitatory and inhibitory synaptic inputs. Excitation and inhibition dynamically …
PDF Cite DOI URL
Functional consequences of correlated excitatory and inhibitory conductances in cortical networks
Probabilistic models of the low-level visual system: the role of prediction in detecting motion
Sensory informations such as visual images are inherently variable. We use probabilistic models to describe how the low-level visual …
Cite URL
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, …
Cite arXiv
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
PDF Cite
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 …
PDF Cite DOI
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 …
Cite DOI URL arXiv
Feature detection using spikes : the greedy approach
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 …
PDF Cite DOI URL
Coherence detection in a spiking neuron via Hebbian learning