Proposed cellular automaton model for a neuronal patch with a thresholded linear activation function
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.
By submitting their manuscript to the Samahang Pisika ng Pilipinas (SPP) for consideration, the Authors warrant that their work is original, does not infringe on existing copyrights, and is not under active consideration for publication elsewhere.
Upon acceptance of their manuscript, the Authors further agree to grant SPP the non-exclusive, worldwide, and royalty-free rights to record, edit, copy, reproduce, publish, distribute, and use all or part of the manuscript for any purpose, in any media now existing or developed in the future, either individually or as part of a collection.
All other associated economic and moral rights as granted by the Intellectual Property Code of the Philippines are maintained by the Authors.