@article{
 title = {Optimal parameter estimation of the Izhikevich single neuron model using experimental inter-spike interval (ISI) data},
 type = {article},
 id = {d8dd6827-9094-351b-bb04-b176ecec79eb},
 created = {2017-06-13T22:15:45.185Z},
 file_attached = {true},
 profile_id = {b32a5781-da35-3f2c-a309-637a9de16369},
 last_modified = {2017-06-13T22:33:20.454Z},
 read = {false},
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 authored = {true},
 confirmed = {true},
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 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 devel-oping a model of ensemble cortical neurons for neuroprosthesis applications.},
 bibtype = {article},
 author = {Kumar, Gautam and Aggarwal, Vikram and Thakor, Nitish V and Schieber, Marc H and Kothare, Mayuresh V}
}

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