A framework for simulation and analysis of dynamically organized distributed neural networks

Details

Serval ID
serval:BIB_4A1D1C2D3552
Type
Article: article from journal or magazin.
Collection
Publications
Title
A framework for simulation and analysis of dynamically organized distributed neural networks
Journal
Lecture Notes in Computer Science
Author(s)
Shaposhnyk  V., Dutoit  P., Contreras-Lámus  V., Perrig  S., Villa  A. E. P.
ISSN
0302-9743
Publication state
Published
Issued date
2009
Peer-reviewed
Oui
Volume
5768
Pages
277-286
Language
english
Notes
Shaposhnyk2009277
Abstract
We present a framework for modelling and analyzing emerging neural activity from multiple interconnected modules, where each module is formed by a neural network. The neural network simulator operates a 2D lattice tissue of leaky integrate-and-fire neurons with genetic, ontogenetic and epigenetic features. The;lava. Agent DEvelopment (JADE) environment allows the implementation of an efficient automata-like virtually unbound and platform-independent system of agents exchanging hierarchically organized messages. This framework allowed us to develop linker agents capable to handle dynamic configurations characterized by the entrance and exit of additional modules at any time following simple rewiring rules. The development of a virtual electrode allows the recording of a "neural" generated signal, called electrochipogram (EChG), characterized by dynamics close to biological local field potentials and electroencephalograms (EEG). These signals can be used to compute Evoked Potentials by complex sensory inputs and comparisons with neurophysiological signals of similar kind.
Keywords
Spiking neural networks, Hierarchical neural networks, Distributed computing, Computational neuroscience, Bio-informatics
Web of science
Create date
23/08/2010 16:52
Last modification date
20/08/2019 14:57
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