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 Java 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.
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Shaposhnyk, V., Dutoit, P., Contreras-Lámus, V., Perrig, S., Villa, A.E.P. (2009). A Framework for Simulation and Analysis of Dynamically Organized Distributed Neural Networks. In: Alippi, C., Polycarpou, M., Panayiotou, C., Ellinas, G. (eds) Artificial Neural Networks – ICANN 2009. ICANN 2009. Lecture Notes in Computer Science, vol 5768. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04274-4_29
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DOI: https://doi.org/10.1007/978-3-642-04274-4_29
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