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A Learning Algorithm for Synfire Chains

  • Jacques Sougné
Part of the Perspectives in Neural Computing book series (PERSPECT.NEURAL)

Abstract

Neurobiological studies indicate very precise temporal behavior of neuron firings. Abeles [1] has recorded spike timing of different cortical cells and, in particular, has observed the following level of precision: when a neuron A frres, neuron B would frre 151ms later and neuron C would fire precisely 289ms after that—with aprecision across trials of 1 ms! Such long delays require dozens of combined transmission delays from the presynaptic neuron (A) to the postsynaptic neuron (C). The mechanism proposed by Abeles for generating such precise delayed synchronization has been called synfire chains. How could synfire chains develop? What learning procedure could generate such precise temporal chains? How could a connectionist network of spiking neurons leam synfrre chains? An algorithm for a network of spiking neurons that learns synfire chains will be presented.

Keywords

Target Node Neuron Firing Postsynaptic Neuron Spike Timing Hebbian Learning 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© Springer-Verlag London 2001

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  • Jacques Sougné

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