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Cellular neural network realizations of neuron models with diverse spiking patterns
Author(s) -
Lotz Károly,
Jacobs Adam,
Vandewalle Joos,
Werblin Frank,
Roska Tamás,
Vidnyánszky Zoltán,
Hámori József
Publication year - 1996
Publication title -
international journal of circuit theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.364
H-Index - 52
eISSN - 1097-007X
pISSN - 0098-9886
DOI - 10.1002/(sici)1097-007x(199605/06)24:3<301::aid-cta918>3.0.co;2-2
Subject(s) - computer science , spiking neural network , biological neuron model , coding (social sciences) , artificial neural network , network model , cellular neural network , neural coding , artificial intelligence , neuroscience , biology , mathematics , statistics
In this paper we show cellular neural network (CNN) models of some basic types of cells characterized by diverse spiking patterns. After presenting some preliminary models (ion channels, neurons), CNN models of action potential generation are given, followed by an analysis of the rate‐coding capabilities of the models. Furthermore, we show CNN models of synaptic connections. Finally, CNN models of neurons with diverse intrinsic firing patterns are presented.