Automated Parameter Estimation of the Hodgkin-Huxley Model Using the Differential Evolution Algorithm: Application to Neuromimetic Analog Integrated Circuits

DOI10.1162/NECO_a_00170zbMath1231.62189OpenAlexW2084636147WikidataQ39739483 ScholiaQ39739483MaRDI QIDQ3116946

Filippo Grassia, Sylvie Renaud-le Masson, Laure Buhry, Audrey Giremus, Sylvain Saïghi, Eric Grivel

Publication date: 14 February 2012

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1162/neco_a_00170

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Neural biology (92C20) Neural networks for/in biological studies, artificial life and related topics (92B20)

Related Items (1)

A combined method to estimate parameters of the thalamocortical model from a heavily noise-corrupted time series of action potential

Uses Software

• Neurofitter
• BRENT

Cites Work

• Unnamed Item
• Automated neuron model optimization techniques: a review
• Minimal Hodgkin-Huxley type models for different classes of cortical and thalamic neurons
• An improved parameter estimation method for Hodgkin-Huxley models
• Differential evolution -- a simple and efficient heuristic for global optimization over continuous spaces

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