Optimal parameter estimation of the Izhikevich single neuron model using experimental Inter-Spike Interval (ISI) data

Gautam Kumar, Vikram Aggarwal, Nitish V Thakor, Marc H. Schieber, Mayuresh V. Kothare

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We propose to use the Izhikevich single neuron model to represent a motor cortex neuron for studying a control-theoretic perspective of a neuroprosthetic system. The problem of estimating model parameters is addressed when the only available data from intracortical recordings of a neuron are the Inter-Spike Intervals (ISIs). Non-linear constrained and unconstrained optimization problems are formulated to estimate model parameters as well as synaptic inputs using ISIs data. The primal-dual interior-point method is implemented to solve the constrained optimization problem. Reasonable model parameters are estimated by solving these optimization problems which may serve as a template for studying and developing a model of ensemble cortical neurons for neuroprosthesis applications.

Original languageEnglish (US)
Title of host publicationProceedings of the 2010 American Control Conference, ACC 2010
Pages3586-3591
Number of pages6
Publication statusPublished - 2010
Event2010 American Control Conference, ACC 2010 - Baltimore, MD, United States
Duration: Jun 30 2010Jul 2 2010

Other

Other2010 American Control Conference, ACC 2010
CountryUnited States
CityBaltimore, MD
Period6/30/107/2/10

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ASJC Scopus subject areas

  • Control and Systems Engineering

Cite this

Kumar, G., Aggarwal, V., Thakor, N. V., Schieber, M. H., & Kothare, M. V. (2010). Optimal parameter estimation of the Izhikevich single neuron model using experimental Inter-Spike Interval (ISI) data. In Proceedings of the 2010 American Control Conference, ACC 2010 (pp. 3586-3591). [5530803]