Power Law Behavior in IF Model With Random Excitatory and Inhibitory Rates

Author

Sharma, Sudheer Kumar ; Karmeshu

Author_Institution

Sch. of Comput. of Syst. Sci., Jawaharlal Nehru Univ., New Delhi, India

Volume

10

Issue

3

fYear

2011

Firstpage

172

Lastpage

176

Abstract

A new mechanism is proposed to generate power law behavior in interspike interval (ISI) distribution when a collection of neurons group together and fire together. Employing superstatistical framework, the mechanism requires a population of neurons which is characterized by randomly distributed excitatory and inhibitory rates. The distribution of these rates is characterized by independent gamma variates. The effect of randomness in the rates exhibits power law behavior in first passage time of the integrate and fire (IF) model. Extensive Monte Carlo simulation studies of the underlying stochastic differential equation (SDE) are carried out which also depict asymptotically power law behavior for ISI distribution for an ensemble of IF neurons.

Keywords

Monte Carlo methods; bioelectric potentials; neurophysiology; random processes; stochastic processes; IF model; Monte Carlo simulation; gamma variates; integrate fire model; interspike interval distribution; neuron collection; neuron firing; power law behavior; random excitatory rate; random inhibitory rate; stochastic differential equation; superstatistical framework; Analytical models; Computational modeling; Mathematical model; Nanobioscience; Neurons; Numerical models; Stochastic processes; Excitatory and inhibitory rates; Poisson process; gamma variates; integrate and fire model; power law behavior; superstatistics; Models, Neurological; Monte Carlo Method; Neurons; Stochastic Processes;

fLanguage

English

Journal_Title

NanoBioscience, IEEE Transactions on

Publisher

ieee

ISSN

1536-1241

Type

jour

DOI

10.1109/TNB.2011.2164808

Filename

6018309