Neural correlation via random connections

  • Authors:

  • Joshua Chover

  • Affiliations:

  • Department of Mathematics, University of Wisconsin--Madison, Madison, Wisconsin 53706 USA

  • Venue:
  • Neural Computation
  • Year:
  • 1996

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Abstract

A simple neural network is studied, which has sparse, random, plastic, excitatory connections and also feedback loops between sensory cells and correlator cells. Time is limited to several discrete instants, where firing is synchronous. For parameter values within biological ranges, the system exhibits a capacity for associative recall, with a controlled amount of extraneous firing, following Hebb-like synaptic changes.