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Related Experiment Video

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How to Create and Use Binocular Rivalry
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Attention model of binocular rivalry.

Hsin-Hung Li1, James Rankin2,3, John Rinzel2,4

  • 1Department of Psychology, New York University, New York, NY 10003; hsin.hung.li@nyu.edu david.heeger@nyu.edu.

Proceedings of the National Academy of Sciences of the United States of America
|July 12, 2017
PubMed
Summary

Binocular rivalry, where the brain alternates between two competing images, requires attention. A new computational model integrates attention and mutual inhibition to explain rivalry dynamics and key experimental findings.

Keywords:
binocular rivalrybistable perceptioncomputational modeldynamical systemvisual attention

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Perception

Background:

  • Binocular rivalry involves perceptual alternations when incompatible images are presented to corresponding retinal locations.
  • It's a model system for studying cortical computation and regulation of competing sensory inputs.
  • Previous research suggests a strong link between binocular rivalry and attention, with rivalry ceasing when attention is diverted.

Purpose of the Study:

  • To develop a computational model of binocular rivalry that incorporates the role of attention.
  • To explain key phenomena of binocular rivalry, including its dependence on attention and dynamic perceptual states.
  • To revise existing computational theories by including attentional modulation.

Main Methods:

  • Developed a computational model where image competition is driven by attentional modulation and mutual inhibition.
  • The model incorporates distinct selectivity and dynamics for attention and inhibition.
  • Utilized bifurcation analysis to identify model parameters consistent with experimental data.

Main Results:

  • The model successfully explains that binocular rivalry requires attention.
  • It accounts for varied perceptual states emerging from rapid image swapping between eyes.
  • Model predictions align with Levelt's propositions regarding dominance duration and input strength.

Conclusions:

  • Attention plays a crucial role in binocular rivalry, necessitating a revision of current computational models.
  • The proposed model, integrating attention and mutual inhibition, provides a comprehensive framework for understanding binocular rivalry.
  • The model's consistency with experimental findings validates its approach to explaining perceptual competition.