Stochastic resonance in binocular rivalry

Yee Joon Kim, Marcia Grabowecky, Satoru Suzuki*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

114 Scopus citations

Abstract

When a different image is presented to each eye, visual awareness spontaneously alternates between the two images-a phenomenon called binocular rivalry. Because binocular rivalry is characterized by two marginally stable perceptual states and spontaneous, apparently stochastic, switching between them, it has been speculated that switches in perceptual awareness reflect a double-well-potential type computational architecture coupled with noise. To characterize this noise-mediated mechanism, we investigated whether stimulus input, neural adaptation, and inhibitory modulations (thought to underlie perceptual switches) interacted with noise in such a way that the system produced stochastic resonance. By subjecting binocular rivalry to weak periodic contrast modulations spanning a range of frequencies, we demonstrated quantitative evidence of stochastic resonance in binocular rivalry. Our behavioral results combined with computational simulations provided insights into the nature of the internal noise (its magnitude, locus, and calibration) that is relevant to perceptual switching, as well as provided novel dynamic constraints on computational models designed to capture the neural mechanisms underlying perceptual switching.

Original languageEnglish (US)
Pages (from-to)392-406
Number of pages15
JournalVision Research
Volume46
Issue number3
DOIs
StatePublished - Feb 2006

Funding

This work was supported by a National Institutes of Health Grant EY14110 to the third author. We thank Hugh Wilson and Adam Reeves for sharing computer code and for helpful discussions of theory and model simulations.

Keywords

  • Binocular rivalry
  • Computational simulation
  • Contrast modulation
  • Dynamics
  • Neural noise
  • Perceptual alternation
  • Stochastic resonance

ASJC Scopus subject areas

  • Ophthalmology
  • Sensory Systems

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