The Computational Power of Spiking Neurons Depends on the Shape of the Postsynaptic Potentials (1996)
| Citations: | 3 - 0 self |
BibTeX
@MISC{Maass96thecomputational,
author = {Wolfgang Maass and Berthold Ruf and Technische Universitaet Graz},
title = {The Computational Power of Spiking Neurons Depends on the Shape of the Postsynaptic Potentials},
year = {1996}
}
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Abstract
Recently one has started to investigate the computational power of spiking neurons (also called "integrate and fire neurons"). These are neuron models that are substantially more realistic from the biological point of view than the ones which are traditionally employed in artificial neural nets. It has turned out that the computational power of networks of spiking neurons is quite large. In particular they have the ability to communicate and manipulate analog variables in spatio-temporal coding, i.e. encoded in the time points when specific neurons "fire" (and thus send a "spike" to other neurons). These preceding results have motivated the question which details of the firing mechanism of spiking neurons are essential for their computational power, and which details are "accidental" aspects of their realization in biological "wetware". Obviously this question becomes important if one wants to capture some of the advantages of computing and learning with spatio-temporal c...
