Spiking time-dependent plasticity leads to efficient coding of predictions

Biol Cybern. 2020 Feb;114(1):43-61. doi: 10.1007/s00422-019-00813-w. Epub 2019 Dec 24.

Abstract

Latency reduction in postsynaptic spikes is a well-known effect of spiking time-dependent plasticity. We expand this notion for long postsynaptic spike trains on single neurons, showing that, for a fixed input spike train, STDP reduces the number of postsynaptic spikes and concentrates the remaining ones. Then, we study the consequences of this phenomena in terms of coding, finding that this mechanism improves the neural code by increasing the signal-to-noise ratio and lowering the metabolic costs of frequent stimuli. Finally, we illustrate that the reduction in postsynaptic latencies can lead to the emergence of predictions.

Keywords: Neural adaptation; Neural code; Predictions; Spiking time-dependent plasticity; Synchronization.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Action Potentials / physiology*
  • Animals
  • Forecasting
  • Humans
  • Models, Neurological*
  • Neuronal Plasticity / physiology*
  • Neurons / physiology*