Optimizing Neural Information Capacity through Discretization

Neuron. 2017 Jun 7;94(5):954-960. doi: 10.1016/j.neuron.2017.04.044.

Abstract

Discretization in neural circuits occurs on many levels, from the generation of action potentials and dendritic integration, to neuropeptide signaling and processing of signals from multiple neurons, to behavioral decisions. It is clear that discretization, when implemented properly, can convey many benefits. However, the optimal solutions depend on both the level of noise and how it impacts a particular computation. This Perspective discusses how current physiological data could potentially be integrated into one theoretical framework based on maximizing information. Key experiments for testing that framework are discussed.

Keywords: dendrites; information theory; ion channels; ionic currents; neural cell types; neuromodulation; neuropeptide; phase transitions; power law; scale-free dynamics.

Publication types

  • Review

MeSH terms

  • Action Potentials / physiology*
  • Behavior / physiology*
  • Decision Making / physiology*
  • Humans
  • Information Theory*
  • Models, Neurological*
  • Nerve Net / physiology*
  • Neurons / physiology*
  • Neuropeptides / physiology*

Substances

  • Neuropeptides