Estimation of biophysical parameters in a neuron model under random fluctuations

Ranjit Kumar Upadhyay, Chinmoy Paul, Argha Mondal and Gajendra K. Vishwakarma

Applied Mathematics and Computation, 2018, vol. 329, issue C, 364-373

Abstract: In this paper, an attempt has been made to estimate the biophysical parameters in an improved version of Morris–Lecar (M–L) neuron model in a noisy environment. To observe the influence of noisy stimulation in estimation procedure, a Gaussian white noise has been added to the membrane voltage of the model system. Estimation of the parameters has been investigated by a proposed algorithm. The denoising technique (local projection method) has been applied to reduce the influence of noisy stimuli and the effectiveness of the method is reported. The proposed scheme performs well for an excitable neuron model and provides good estimates between the estimated parameters and the actual values in a reasonable way. This approach can be used for parameter estimation for other nonlinear dynamical systems.

Keywords: Morris–Lecar model; White noise; Parameter estimation; Denoising technique; Algorithm; Random fluctuations (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:329:y:2018:i:c:p:364-373

DOI: 10.1016/j.amc.2018.02.011

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