Resonance with subthreshold oscillatory drive organizes activity and optimizes learning in neural networks

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Abstract
Significance: Networks of neurons need to reliably encode and replay patterns and sequences of activity. In the brain, sequences of spatially coding neurons are replayed in both the forward and reverse direction in time with respect to their order in recent experience. As of yet there is no network-level or biophysical mechanism known that can produce both modes of replay within the same network. Here we propose that resonance, a property of neurons, paired with subthreshold oscillations in neural input facilitate network-level learning of fixed and sequential activity patterns and lead to both forward and reverse replay.
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Funding Information
  • National Science Foundation (DGE 1256260)
  • National Institutes of Health (DP2MH104119)
  • National Institute of Biomedical Imaging and Bioengineering (1R01EB018297)

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