Receptive profiles of V1 cortical cells are very heterogeneous and act by differentiating the stimulus image as operators changing from point to point. A lightness and color constancy image can be reconstructed as the solution of the associated inverse problem, that is a Poisson equation with heterogeneous differential operators. At the neural level the weights of short range connectivity constitute the fundamental solution of the Poisson problem adapted point by point. A first demonstration of convergence of the result towards homogeneous reconstructions is proposed by means of homogenisation techniques.Comment: 34 pages, 13 figure
International audienceA fundamental challenge for the theoretical study of neuronal networks is to m...
In this note we consider the perfect integrator driven by Poisson process input. We derive its equil...
Contains fulltext : 222432.pdf (Publisher’s version ) (Open Access)We present a hi...
Receptive profiles of V1 cortical cells are very heterogeneous and act by differentiating the stimul...
Exploiting data invariances is crucial for efficient learning in both artificial and biological neur...
<p>(<b>a</b>) Input-response curve of a heterogeneous (blue) and homogeneous (red) population for pu...
Learned iterative reconstruction algorithms for inverse problems offer the flexibility to combine an...
The variability of neuronal responses is proportional to the mean in many brain areas, which suggest...
We present an integrative formalism of mutual information expansion, the general Poisson exact break...
The recent paper by Pokorny and Smith [J. Opt. Sec. Am. A 14, 2477 (1997)] describes psychophysical ...
<p>(A) Mean Fano factor of the neural population in 15 ms windows is shown in black. Gray curves sho...
To lay groundwork for better testing theories of cortical function that may depend on interactions b...
AbstractNeuronal populations in the primary visual cortex (V1) of mammals exhibit contrast normaliza...
International audienceThe CNS, like all complex systems, features a large variety of spatial and tem...
The capacity defines the ultimate fidelity limits of information transmission by any system. We deri...
International audienceA fundamental challenge for the theoretical study of neuronal networks is to m...
In this note we consider the perfect integrator driven by Poisson process input. We derive its equil...
Contains fulltext : 222432.pdf (Publisher’s version ) (Open Access)We present a hi...
Receptive profiles of V1 cortical cells are very heterogeneous and act by differentiating the stimul...
Exploiting data invariances is crucial for efficient learning in both artificial and biological neur...
<p>(<b>a</b>) Input-response curve of a heterogeneous (blue) and homogeneous (red) population for pu...
Learned iterative reconstruction algorithms for inverse problems offer the flexibility to combine an...
The variability of neuronal responses is proportional to the mean in many brain areas, which suggest...
We present an integrative formalism of mutual information expansion, the general Poisson exact break...
The recent paper by Pokorny and Smith [J. Opt. Sec. Am. A 14, 2477 (1997)] describes psychophysical ...
<p>(A) Mean Fano factor of the neural population in 15 ms windows is shown in black. Gray curves sho...
To lay groundwork for better testing theories of cortical function that may depend on interactions b...
AbstractNeuronal populations in the primary visual cortex (V1) of mammals exhibit contrast normaliza...
International audienceThe CNS, like all complex systems, features a large variety of spatial and tem...
The capacity defines the ultimate fidelity limits of information transmission by any system. We deri...
International audienceA fundamental challenge for the theoretical study of neuronal networks is to m...
In this note we consider the perfect integrator driven by Poisson process input. We derive its equil...
Contains fulltext : 222432.pdf (Publisher’s version ) (Open Access)We present a hi...