Summary

Proceedings of the 2013 International Symposium on Nonlinear Theory and its Applications

2013

Session Number:A3L-D

Session:

Number:114

Multi-Compartment Asynchronous Cellular Automaton and its Application for Neuron Modeling

Naoki Shimada,  Hiroyuki Torikai,  

pp.114-117

Publication Date:

Online ISSN:2188-5079

DOI:10.15248/proc.2.114

PDF download (442.5KB)

Summary:
A rotate-and-fire digital spiking neuron (RDN) has been proposed, which is described by an asynchronous cellular automaton. A whole neuron is roughly divided into three parts, a soma, dendrites, and an axon. On the other hand, the RDN is the model designed for reproduction of dynamic properties of a soma. Hence, in this paper, we propose a novel multi-compartment neuron (MCN) which is based on the RDNs and is designed for reproduction of dynamic properties of a soma and dendrites. Then, we try to reproduce properties of propagation of potential observed in representative nonlinear ODE MCNs.

References:

[1] E. M. Izhikevich, “Which Model to Use for Cortical Spiking Neurons?” IEEE Trans. Neural Networks, vol. 15 no. 5, pp. 1063-1070, 2004.

[2] T. Hishiki and H. Torikai, “A Novel Rotate-and-Fire Digital Spiking Neuron and its Neuron-Like Bifurcations and Responses,” IEEE Trans. Neural Networks, vol. 22, no. 5, pp. 752-767, 2011.

[3] T. Matsubara, H. Torikai, and T. Hishiki, “A Generalized Rotate-and-Fire Digital Spiking Neuron Model and its On-FPGA Learning,” IEEE Trans. Circuits and Systems II, vol. 58, no. 10, pp. 677-681, 2011.

[4] E. M. Izhikevich, Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting. Cambridge, MA: MIT press, 2007.