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A multi-scale simulation of retinal physiology.

Belal Abuelnasr1, Adam R Stinchcombe1

  • 1Department of Mathematics, University of Toronto, Toronto, ON, M5S 2E4, Canada.

Mathematical Biosciences
|July 30, 2023
PubMed
Summary
This summary is machine-generated.

We developed a detailed computational model of the human retina, simulating phototransduction and electrical signaling. This model aids in understanding retinal function and designing visual prosthetics.

Keywords:
Adaptive solverBiological modelInexact Newton methodNewton-iterative methodsRetina modelSimulation

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Area of Science:

  • Computational neuroscience
  • Ophthalmology
  • Biophysics

Background:

  • The human retina's complex physiology involves phototransduction and neuronal signaling.
  • Existing models often lack detailed biochemical and electrophysiological components or realistic geometry.

Purpose of the Study:

  • To create a comprehensive physiological model of the human retina.
  • To incorporate phototransduction, neuronal electrical coupling, and eye geometry into a unified framework.

Main Methods:

  • Developed a parabolic-elliptic system of partial differential equations based on generalized bi-domain equations.
  • Employed non-uniform finite differences for spatial discretization and an adaptive time-stepper with backward differentiation formula and inexact Newton method.
  • Validated the numerical method through a refinement study.

Main Results:

  • Numerical simulations accurately reproduced experimental findings like photoreceptor light desensitization and calcium buffering.
  • The model revealed an interplay between photoreceptor gap junctions and inner segment calcium concentration.
  • The model's accuracy and efficiency were confirmed.

Conclusions:

  • The developed model provides a robust tool for analyzing retinal function.
  • It has potential applications in analyzing retinal calcium imaging, designing electroretinograms and visual prosthetics, and studying ephaptic coupling.