Bistable perception modeled as competing stochastic integrations at two levels

PLoS Comput Biol. 2009 Jul;5(7):e1000430. doi: 10.1371/journal.pcbi.1000430. Epub 2009 Jul 10.

Abstract

We propose a novel explanation for bistable perception, namely, the collective dynamics of multiple neural populations that are individually meta-stable. Distributed representations of sensory input and of perceptual state build gradually through noise-driven transitions in these populations, until the competition between alternative representations is resolved by a threshold mechanism. The perpetual repetition of this collective race to threshold renders perception bistable. This collective dynamics - which is largely uncoupled from the time-scales that govern individual populations or neurons - explains many hitherto puzzling observations about bistable perception: the wide range of mean alternation rates exhibited by bistable phenomena, the consistent variability of successive dominance periods, and the stabilizing effect of past perceptual states. It also predicts a number of previously unsuspected relationships between observable quantities characterizing bistable perception. We conclude that bistable perception reflects the collective nature of neural decision making rather than properties of individual populations or neurons.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Models, Neurological*
  • Perception / physiology*
  • Photic Stimulation*
  • Stochastic Processes
  • Time Factors
  • Vision, Binocular / physiology*