NeuralEnsemble (http://neuralensemble.org) is a multilateral effort to coordinate and organise neuroscience software development efforts based around the Python programming language into a larger, meta-simulator software system. To this end, …
Based on Nicole Voges, Laurent U Perrinet (2010). Phase space analysis of networks based on biologically realistic parameters. Journal of Physiology-Paris. PDF Cite DOI see follow-up : Nicole Voges, Laurent U Perrinet (2012).
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 …
In the primary visual cortex (V1), single cell responses to simple visual stimuli (gratings) are usually dense but with a high trial-by-trial variability. In contrast, when exposed to full field natural scenes, the firing patterns of these neurons …
The machinery behind the visual perception of motion and the subsequent sensorimotor transformation, such as in Ocular Following Response (OFR), is confronted to uncertainties which are efficiently resolved in the primate's visual system. We may …
Based on Nicole Voges, Laurent U Perrinet (2010). Phase space analysis of networks based on biologically realistic parameters. Journal of Physiology-Paris. PDF Cite DOI see follow-up : Nicole Voges, Laurent U Perrinet (2012).
When the visual information about an object's motion differs at the local level, the visuomotor system needs to integrate information across time to solve this ambiguity and converge to the final motion solution. For an oblique line moving …
I will illustrate in this talk how computational neuroscience may inspire and be inspired by mathematical image processing. Focusing on efficiently representing natural images in the primary visual cortex, we derive an event-based adaptive algorithm …
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 …
Trends in programming language development and adoption point to Python as the high-level systems integration language of choice. Python leverages a vast developer-base external to the neuroscience community, and promises leaps in simulation …
Perceptual and oculomotor data demonstrate that, when the visual information about an object's motion differs on the local (edge-related) and global levels, the local 1D motion cues dominate initially, whereas 2D information takes progressively over …
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 (Olshausen, 1996). As the SparseNet …
The quality of the representation of an object's motion is limited by the noise in the sensory input as well as by an intrinsic ambiguity due to the spatial limitation of the visual motion analyzers (aperture problem). Perceptual and oculomotor data …
Computations in a cortical column are characterized by the dynamical, event-based nature of neuronal signals and are structured by the layered and parallel structure of cortical areas. But they are also characterized by their efficiency in terms of …
The quality of the representation of an object's motion is limited by the noise in the sensory input as well as by an intrinsic ambiguity due to the spatial limitation of the visual motion analyzers (aperture problem). Perceptual and oculomotor data …
We present a biologically plausible model of simple cortical cells as 1) a linear transform representing edges and 2) a non-linear iterative stage of inhibition and facilitation between neighboring coefficients. The linear transform is a complex …
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 …
The integration of information is essential to measure the exact 2D motion of a surface from both local ambiguous 1D motion produced by elongated edges and local non-ambiguous 2D motion from features such as corners, end-points or texture elements. …
Low-level perceptual computations may be understood in terms of efficient codes (Simoncelli and Olshausen, 2001, Annual Review of Neuroscience 24 1193-216). Following this argument, we explore models of representation for natural static images as a …