Neural field simulator: fast computation and 3D-visualization

Eric Nichols 1, * Axel Hutt 1
* Corresponding author
1 NEUROSYS - Analysis and modeling of neural systems by a system neuroscience approach
Inria Nancy - Grand Est, LORIA - AIS - Department of Complex Systems, Artificial Intelligence & Robotics
Résumé : This work presents a simulator that facilitates dynamic neural field (DNF) calculations obeying models of the type ∂V (x, t) / ∂t = −V (x, t) + ∫ K(x − y) S[V (y, t −(x − y)/c] dy + I (x, t) involving axonal finite transmission speed c. The underlying numerical computation method [1] utilizes a Fast Fourier Transform in space. Motivation for the work arises from a need for a visualization tool that is useful to the largest number of DNF researchers, allows for the tailoring of code and has fast while visually appealing output. The simulator can operate on all major operating systems and the wxWindows library is used to provide a native cross-platform look and feel. It is open source and enables researchers to modify the simulator in any beneficial way. Output of data in 3 dimensions is provided by PyOpenGL which brings the speed and graphical detail of low-level OpenGL to the agile Python language.
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Submitted on : Monday, July 8, 2013 - 1:10:22 PM
Last modification on : Tuesday, December 18, 2018 - 4:40:21 PM
Long-term archiving on : Wednesday, October 9, 2013 - 4:22:16 AM

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Eric Nichols, Axel Hutt. Neural field simulator: fast computation and 3D-visualization. Twenty Second Annual Computational Neuroscience Meeting : CNS 2013, Jul 2013, Paris, France. 14 (Suppl 1), pp.179, 2013, ⟨10.1186/1471-2202-14-S1-P179 ⟩. ⟨hal-00842306⟩

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