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Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

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Published on: June 21, 2022

A novel image-based neuronal network model framework for understanding visual multistability and neurological

Kaito N Hikino¹, Marina Nakayama¹, Yihui Wu¹

¹Department of Mathematics and Statistics, Swarthmore College, Swarthmore, PA, United States.

Frontiers in Computational Neuroscience

|May 15, 2026

Summary

This study models visual multistability, revealing that balanced neural excitation and inhibition dynamics are key to perceptual stability. The model also explains how imbalances contribute to amblyopia and autism.

Keywords:

autism balanced networks compressive sensing multistability neuronal networks nonlinear dynamics

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Area of Science:

Computational Neuroscience
Perception and Cognition
Systems Neuroscience

Background:

Perceptual multistability, observed across sensory systems, suggests universal organizing principles in perception.
Visual multistability involves complex neuronal dynamics, with key experimental observations in binocular rivalry.

Purpose of the Study:

To probe fundamental mechanisms of visual multistability using a neuronal network model.
To develop a methodology for reconstructing dynamic percepts and understanding decision-making systems.
To apply the model to characterize neurological disorders like amblyopia and autism.

Main Methods:

A neuronal network model with nonlinear dynamics driven by realistic images.
Incorporation of balanced network architecture, long-range connections, and dynamic spiking thresholds.
Analysis of neuronal dynamics to reconstruct percepts and simulate disorder characteristics.

Main Results:

The model replicates irregular percept switching and dominance durations observed in binocular rivalry.
A novel methodology for reconstructing dynamic percepts was derived, generalizing to multiple percepts.
Model dynamics indicate perceptual alternations stem from excitation-inhibition balance breakdown.

Conclusions:

Balanced neural dynamics facilitate longer dominance durations in perceptual tasks.
The model supports the excitation/inhibition imbalance hypothesis for autism.
Model findings provide insights into the neural basis of amblyopia and autism, linking inter-eye competition and E/I balance to observed symptoms.