Related Experiment Video
Updated: Apr 26, 2026

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
Published on: June 21, 2022
On the capabilities and computational costs of neuron models
Abstract:
We review the Hodgkin-Huxley, Izhikevich, and leaky integrate-and-fire neuron models in regular spiking modes solved with the forward Euler, fourth-order Runge-Kutta, and exponential Euler methods and determine the necessary time steps and corresponding computational costs required to make the solutions accurate. We conclude that the leaky integrate-and-fire needs the least number of computations, and that the Hodgkin-Huxley and Izhikevich models are comparable in computational cost.
Related Concept Videos
Neural Circuits
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Neuronal Communication
Neuroplasticity
Ampere-Maxwell's Law: Problem-Solving
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of the...
The Role of Ion Channels in Neuronal Computation
Sometimes a single EPSP is strong enough to induce an action potential in the postsynaptic neuron. However, multiple presynaptic inputs must often create EPSPs around the same time for the postsynaptic neuron to be sufficiently depolarized to fire an action potential....

