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A spiking network model of short-term active memory

D Zipser1, B Kehoe, G Littlewort

  • 1Department of Cognitive Science, University of California, San Diego, La Jolla 92093.

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
|August 1, 1993
PubMed
Summary

A new spiking neural network model suggests recurrent networks with fixed synaptic strengths can explain short-term memory. This model closely mimics monkey cortical neuron activity, supporting active storage mechanisms in the brain.

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Area of Science:

  • Computational Neuroscience
  • Cognitive Neuroscience
  • Neural Networks

Background:

  • Cortical neurons in monkeys maintain stimulus information via persistent firing during short-term memory tasks.
  • The underlying mechanism for this sustained neural activity remains largely unknown.

Purpose of the Study:

  • To investigate the hypothesis that recurrent networks with fixed connection strengths can temporarily store graded information.
  • To develop and analyze a spiking neural network model for short-term memory.

Main Methods:

  • Computed synaptic weights for a non-spiking recurrent network using optimization.
  • Transformed the non-spiking network into a spiking neural network by interpreting outputs as spiking probabilities.
  • Compared model neuron behavior with recordings from 179 monkey inferotemporal (IT) cortex neurons.

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Main Results:

  • Spiking patterns of model neurons closely resembled those of IT neurons.
  • Approximately 40% of IT neuron firing patterns matched model neuron types.
  • Evidence of characteristic statistical temporal structure in spike trains was found in about half of the IT neurons, consistent with model predictions of attractor switching.

Conclusions:

  • The behavior of many cortical memory neurons is consistent with active storage mechanisms based on recurrent activity in networks with fixed synaptic strengths.
  • Spiking neural network models provide a viable framework for understanding the neural basis of short-term memory.