Parameter estimation of neuron models using in-vitro and in-vivo electrophysiological data.
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ABSTRACT:
SUBMITTER: Lynch EP
PROVIDER: S-EPMC4403314 | biostudies-literature | 2015
REPOSITORIES: biostudies-literature
Publications
Parameter estimation of neuron models using in-vitro and in-vivo electrophysiological data.
Lynch Eoin P EP Houghton Conor J CJ
Frontiers in neuroinformatics 20150420
Spiking neuron models can accurately predict the response of neurons to somatically injected currents if the model parameters are carefully tuned. Predicting the response of in-vivo neurons responding to natural stimuli presents a far more challenging modeling problem. In this study, an algorithm is presented for parameter estimation of spiking neuron models. The algorithm is a hybrid evolutionary algorithm which uses a spike train metric as a fitness function. We apply this to parameter discove ...[more]
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