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Title: Mutual Information and Information Gating in Synfire Chains

Journal Article · · Entropy
DOI:https://doi.org/10.3390/e20020102· OSTI ID:1419762
 [1];  [2]; ORCiD logo [3];  [2]
  1. Univ. of Arizona, Tucson, AZ (United States)
  2. Peking Univ., Beijing (China)
  3. Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Univ. of California, Davis, CA (United States)

Here, coherent neuronal activity is believed to underlie the transfer and processing of information in the brain. Coherent activity in the form of synchronous firing and oscillations has been measured in many brain regions and has been correlated with enhanced feature processing and other sensory and cognitive functions. In the theoretical context, synfire chains and the transfer of transient activity packets in feedforward networks have been appealed to in order to describe coherent spiking and information transfer. Recently, it has been demonstrated that the classical synfire chain architecture, with the addition of suitably timed gating currents, can support the graded transfer of mean firing rates in feedforward networks (called synfire-gated synfire chains—SGSCs). Here we study information propagation in SGSCs by examining mutual information as a function of layer number in a feedforward network. We explore the effects of gating and noise on information transfer in synfire chains and demonstrate that asymptotically, two main regions exist in parameter space where information may be propagated and its propagation is controlled by pulse-gating: a large region where binary codes may be propagated, and a smaller region near a cusp in parameter space that supports graded propagation across many layers.

Research Organization:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
AC52-06NA25396
OSTI ID:
1419762
Report Number(s):
LA-UR-17-31404; ENTRFG
Journal Information:
Entropy, Vol. 20, Issue 2; ISSN 1099-4300
Publisher:
MDPICopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 6 works
Citation information provided by
Web of Science

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Cited By (2)

Information Theory in Neuroscience journal January 2019
Information theory in neuroscience journal January 2011