Verhulst and bifurcation analyses of a neuronal network on an outer-totalistic toroidal cellular automata

Authors

  • Reinier Xander Azcueta 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

Our cellular automata (CA) model of a neuronal patch is a fast way of exploring the dynamics of population of interconnected neurons. In this study, we analyzed the cobweb diagrams of our model and found that the nonzero steady-state neuronal activity is an emergent property of our model. We investigated if there exists a bifurcation and found that the period-doubling happens at negatively-sloped activation function. Neurons exhibiting this characteristic implies a possible way of modelling epileptic neurons. We propose the categorization of neuronal CA as follows: Class 0 (Zero steady-state), Class 1 (Nonzero steady-state), and Class 2 (Periodic steady-state).

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Article ID

SPP-2020-3C-05

Section

Complex Systems and Data Analytics

Published

2020-10-19

How to Cite

[1]
RXA Ramos and JY Bantang, Verhulst and bifurcation analyses of a neuronal network on an outer-totalistic toroidal cellular automata, Proceedings of the Samahang Pisika ng Pilipinas 38, SPP-2020-3C-05 (2020). URL: https://proceedings.spp-online.org/article/view/SPP-2020-3C-05.