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Poster Communications Year : 2013

Neural field simulator: fast computation and 3D-visualization

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Abstract

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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Dates and versions

hal-00842306 , version 1 (08-07-2013)

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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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