Dynamical modeling of multi-scale variability in neuronal competition

Commun Biol. 2019 Aug 23:2:319. doi: 10.1038/s42003-019-0555-7. eCollection 2019.

Abstract

Variability is observed at multiple-scales in the brain and ubiquitous in perception. However, the nature of perceptual variability is an open question. We focus on variability during perceptual rivalry, a form of neuronal competition. Rivalry provides a window into neural processing since activity in many brain areas is correlated to the alternating perception rather than a constant ambiguous stimulus. It exhibits robust properties at multiple scales including conscious awareness and neuron dynamics. The prevalent theory for spiking variability is called the balanced state; whereas, the source of perceptual variability is unknown. Here we show that a single biophysical circuit model, satisfying certain mutual inhibition architectures, can explain spiking and perceptual variability during rivalry. These models adhere to a broad set of strict experimental constraints at multiple scales. As we show, the models predict how spiking and perceptual variability changes with stimulus conditions.

Keywords: Biophysical models; Computational biophysics; Perception.

MeSH terms

  • Action Potentials / physiology
  • Models, Neurological*
  • Nerve Net / physiology
  • Neurons / physiology*
  • Psychophysics

Associated data

  • figshare/10.6084/m9.figshare.8869109.v1