Abstract: At present, it is obvious that different sections of nervous system utilize different methods for information coding. Primary afferent signals in most cases are represented in form of spike trains using a combination of rate coding and population coding while there are clear evidences that temporal coding is used in various regions of cortex. In the present paper, it is shown that conversion between these two coding schemes can be performed under certain conditions by a homogenous chaotic neural network. Interestingly, this effect can be achieved without network training and synaptic plasticity.
Author: Mikhail Kiselev
MLA Citation: “Homogenous chaotic network serving as a rate/population code to temporal code converter” Computational intelligence and neuroscience vol. 2014 (2014): 476580.
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