Within the central nervous system, visual areas are essential in transforming the raw luminous signal into a representation which efficiently conveys information about the environment. This process is constrained by the necessity of being robust and …
*Background*: The primary visual cortex (V1) is a key component of the visual system that builds some of the first levels of coherent visual representations from sparse visual inputs. While the study of its dynamics has been the focus of many …
Traveling waves have recently been observed in different animal species, brain areas and behavioral states. However, it is still unclear what are their functional roles. In the case of cortical visual processing, waves propagate across retinotopic maps and can hereby generate interactions between spatially and temporally separated instances of feedforward driven activity. Such interactions could participate in processing long-range apparent motion stimuli, an illusion for which no clear neuronal mechanisms have yet been proposed. Using this paradigm in awake monkeys, we show that suppressive traveling waves produce to a spatio-temporal normalization of apparent motion stimuli. Our study suggests that cortical waves shape the representation of illusory moving stimulus within retinotopic maps for an straightforward read-out by downstream areas.
The formation of structure in the visual system, that is, of the connections between cells within neural populations, is by large an unsupervised learning process: the emergence of this architecture is mostly self-organized. In the primary visual …
A key property of the neurons in the primary visual cortex (V1) is their selectivity to oriented stimuli in the visual field. Orientation selectivity allows the segmentation of objects in natural visual scenes, which is the first step in building …
The selectivity of the visual system to oriented patterns is very well documented in a wide range of species, especially in mammals. In particular, neurons of the primary visual cortex are anatomically grouped by their preference to a given oriented …
Neurons in the primary visual cortex are known for responding vigorously but with high variability to classical stimuli such as drifting bars or gratings. By contrast, natural scenes are encoded more efficiently by sparse and temporal precise spiking …
We study cortical network dynamics for a spatially embedded network model. It represents, in terms of spatial scale, a large piece of cortex allowing for long-range connections, resulting in a rather sparse connectivity. The spatial embedding also …
We describe the theoretical formulation of a learning algorithm in a model of the primary visual cortex (V1) and present results of the efficiency of this algorithm by comparing it to the SparseNet algorithm [1]. As the SparseNet algorithm, it is …
Efficient sparse coding of overcomplete transforms remains still anopen problem. Different methods have been proposed in theliterature, but most of them are limited by a heavy computationalcost and by difficulties to find the optimal solutions. We …
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 …
Progressive reconstruction of a static image using spikes in a Laplacian pyramid.