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How to Create and Use Binocular Rivalry
Published on: November 10, 2010
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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
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.
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.
- 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.

