Abstract
The retina encodes visual scenes by trains of action potentials that are sent to the brain via the optic nerve. In this paper, we describe a new free access user-end software allowing to better understand this coding. It is called PRANAS (https://pranas.inria.fr), standing for Platform for Retinal ANalysis And Simulation. PRANAS targets neuroscientists and modelers by providing a unique set of retina-related tools. PRANAS integrates a retina simulator allowing large scale simulations while keeping a strong biological plausibility and a toolbox for the analysis of spike train population statistics. The statistical method (entropy maximization under constraints) takes into account both spatial and temporal correlations as constraints, allowing to analyze the effects of memory on statistics. PRANAS also integrates a tool computing and representing in 3D (time-space) receptive fields. All these tools are accessible through a friendly graphical user interface. The most CPU-costly of them have been implemented to run in parallel.
Highlights
The retina is one of the most developed sensing devices (Gollisch and Meister, 2010; Masland, 2011, 2012)
The role of spatiotemporal correlations in population coding raises up deep theoretical and practical questions that are far from being answered (Rieke et al, 1996; Cessac and Palacios, 2012), for the visual information transmitted from the retina to the visual cortex
In this paper we present a new Platform for Retinal ANalysis And Simulation called PRANAS
Summary
The retina is one of the most developed sensing devices (Gollisch and Meister, 2010; Masland, 2011, 2012). The role of spatiotemporal correlations in population coding raises up deep theoretical and practical questions that are far from being answered (Rieke et al, 1996; Cessac and Palacios, 2012), for the visual information transmitted from the retina to the visual cortex To address these questions and make progress in their understanding, one needs to develop joint modeling and experimental studies with efficient software to analyse data. In PRANAS, we are interested in this third class of models because they allow to explore several aspects of retinal image processing such as (i) understanding how to reproduce accurately the statistics of the spiking activity at the population level (Nasser et al, 2013a), (ii) reconciling connectomics and simple computational rules for visual motion detection (Kim et al, 2014), and (iii) investigating how such canonical microcircuits can implement the different retinal processing modules cited in e.g., Gollisch and Meister (2010).
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