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 …
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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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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 …
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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 …
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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 …
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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 …
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A Simple Model of Orientation Encoding Accounting For Multivariate Neural Noise
see a follow-up in this publication
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A Simple Model of Orientation Encoding Accounting For Multivariate Neural Noise
see a follow-up in this publication
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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 …
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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 …
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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 …
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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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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
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