Proposed cellular automaton model for a neuronal patch with a thresholded linear activation function

Authors

  • Reinier Ramos ⋅ PH National Institute of Physics, University of the Philippines Diliman
  • Johnrob Yap Bantang ⋅ PH National Institute of Physics, University of the Philippines Diliman

Abstract

Hodgkin-Huxley, and most of our current neuronal models consist of differential equations to explain the behavior of a single neuron with an electrical synapse, a chemical synapse, or both. In order to model a network of neurons, we need to couple these differential equations, and consequently, increasing the number of equations to solve. This will be difficult to do manually, and even, subjected to the limits of computing power of today’s computers, when done numerically. In this paper, we propose a model for a network of neurons (N = 10 000) placed in a 100 x 100 lattice, with a linear activation function as the rule of the cellular automaton.

Downloads

Issue

Article ID

SPP-2018-PB-37

Section

Poster Session B (Complex Systems, Simulations, and Theoretical Physics)

Published

2018-05-28

How to Cite

[1]
R Ramos and JY Bantang, Proposed cellular automaton model for a neuronal patch with a thresholded linear activation function, Proceedings of the Samahang Pisika ng Pilipinas 36, SPP-2018-PB-37 (2018). URL: https://proceedings.spp-online.org/article/view/SPP-2018-PB-37.