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Effect on information transfer of synaptic pruning driven by spike-timing-dependent plasticity

Quansheng Ren, Zhiqiang Zhang, and Jianye Zhao*

  • School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, People’s Republic of China

  • *phdzjy@263.net
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Phys. Rev. E 85, 022901 – Published 13 February, 2012

DOI: https://doi.org/10.1103/PhysRevE.85.022901

Abstract

Spike-timing-dependent plasticity (STDP) is an important driving force of self-organization in neural systems. With properly chosen input signals, STDP can yield a synaptic pruning process, whose functional role needs to be further investigated. We explore this issue from an information theoretic standpoint. Temporally correlated stimuli are introduced to neurons of an input layer. Then synapses on the dendrite, and thus the receptive field, of an output neuron are refined by STDP. The mutual information between input and output spike trains is calculated with the context tree method. The results show that synapse removal can enhance information transfer, i.e., that “less can be more” under certain constraints that stress the balance between potentiation and depression dictated by the parameters of the STDP rule, as well as the temporal scale of the input correlation.

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Outline

Information

Phys. Rev. E 85, 022901– Published 13 February, 2012
  • Received 16 October 2011
Article part of CHORUS

©2012 American Physical Society

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