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How to Create and Use Binocular Rivalry
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Methods to assess binocular rivalry with periodic stimuli.

Farzaneh Darki1, James Rankin2

  • 1Department of Mathematics, College of Engineering, Mathematics & Physical Sciences, University of Exeter, Exeter, UK. fd303@exeter.ac.uk.

Journal of Mathematical Neuroscience
|June 17, 2020
PubMed
Summary

This study explores complex dynamics in binocular rivalry models, revealing new behaviors like mixed-mode oscillations and chaotic dynamics under periodic forcing. These findings enhance our understanding of visual perception and neural mechanisms.

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Area of Science:

  • Computational Neuroscience
  • Visual Perception
  • Dynamical Systems Theory

Background:

  • Binocular rivalry involves alternating perception between incompatible stimuli presented to each eye.
  • Existing models, like Wilson's, have been analyzed for fixed inputs, but periodic forcing dynamics remain underexplored.
  • Previous analysis identified Winner-takes-all (WTA), Rivalry oscillations (RIV), and Simultaneous activity (SIM) as key behaviors.

Purpose of the Study:

  • To provide a more complete description of complex dynamics in the unforced Wilson binocular rivalry model.
  • To conduct a bifurcation analysis of the Wilson model under periodic forcing.
  • To investigate the impact of different frequencies of periodic forcing on rivalry dynamics.

Main Methods:

  • Bifurcation analysis of the Wilson model with fixed and periodically forced inputs.
Keywords:
Bifurcation analysisFlicker and switch rivalryPeriodic forcingRivalry modelTraditional rivalry

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  • Numerical continuation to study the effects of periodic forcing at various frequencies.
  • Identification and characterization of novel dynamical behaviors beyond previously known ones.
  • Main Results:

    • Richer dynamics were found in the unforced Wilson model, including mixed-mode oscillations (MMOs) and a period-doubling cascade (low-amplitude WTA oscillations).
    • High-frequency periodic forcing (flicker) modulates existing behaviors (WTA-Mod, RIV-Mod, SIM-Mod).
    • Low-frequency periodic forcing (swap) introduces new dynamics: cycle skipping, multi-cycle skipping, and chaotic dynamics.

    Conclusions:

    • The study reveals a broader range of complex dynamics in binocular rivalry models than previously understood.
    • Periodic forcing, especially at low frequencies, can induce chaotic and skipping behaviors, offering new insights.
    • Findings provide a framework for evaluating binocular rivalry models against empirical data and understanding neural mechanisms.