Systematic generation of biophysically detailed models for diverse cortical neuron types

Neocortical circuits exhibit diverse cell types that can be difficult to build into computational models. Here the authors employ a genetic algorithm-based parameter optimization to generate multi-compartment Hodgkin-Huxley models for diverse cell types in the Allen Cell Types Database.

Bibliographic Details
Main Authors:	Nathan W. Gouwens, Jim Berg, David Feng, Staci A. Sorensen, Hongkui Zeng, Michael J. Hawrylycz, Christof Koch, Anton Arkhipov
Format:	Article
Language:	English
Published:	Nature Publishing Group 2018-02-01
Series:	Nature Communications
Online Access:	https://doi.org/10.1038/s41467-017-02718-3

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spelling	doaj-5f1011cab91d4dc5ae8caffe5ac201b92021-05-11T10:19:00ZengNature Publishing GroupNature Communications2041-17232018-02-019111310.1038/s41467-017-02718-3Systematic generation of biophysically detailed models for diverse cortical neuron typesNathan W. Gouwens0Jim Berg1David Feng2Staci A. Sorensen3Hongkui Zeng4Michael J. Hawrylycz5Christof Koch6Anton Arkhipov7Allen Institute for Brain ScienceAllen Institute for Brain ScienceAllen Institute for Brain ScienceAllen Institute for Brain ScienceAllen Institute for Brain ScienceAllen Institute for Brain ScienceAllen Institute for Brain ScienceAllen Institute for Brain ScienceNeocortical circuits exhibit diverse cell types that can be difficult to build into computational models. Here the authors employ a genetic algorithm-based parameter optimization to generate multi-compartment Hodgkin-Huxley models for diverse cell types in the Allen Cell Types Database.https://doi.org/10.1038/s41467-017-02718-3
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Nathan W. Gouwens Jim Berg David Feng Staci A. Sorensen Hongkui Zeng Michael J. Hawrylycz Christof Koch Anton Arkhipov
spellingShingle	Nathan W. Gouwens Jim Berg David Feng Staci A. Sorensen Hongkui Zeng Michael J. Hawrylycz Christof Koch Anton Arkhipov Systematic generation of biophysically detailed models for diverse cortical neuron types Nature Communications
author_facet	Nathan W. Gouwens Jim Berg David Feng Staci A. Sorensen Hongkui Zeng Michael J. Hawrylycz Christof Koch Anton Arkhipov
author_sort	Nathan W. Gouwens
title	Systematic generation of biophysically detailed models for diverse cortical neuron types
title_short	Systematic generation of biophysically detailed models for diverse cortical neuron types
title_full	Systematic generation of biophysically detailed models for diverse cortical neuron types
title_fullStr	Systematic generation of biophysically detailed models for diverse cortical neuron types
title_full_unstemmed	Systematic generation of biophysically detailed models for diverse cortical neuron types
title_sort	systematic generation of biophysically detailed models for diverse cortical neuron types
publisher	Nature Publishing Group
series	Nature Communications
issn	2041-1723
publishDate	2018-02-01
description	Neocortical circuits exhibit diverse cell types that can be difficult to build into computational models. Here the authors employ a genetic algorithm-based parameter optimization to generate multi-compartment Hodgkin-Huxley models for diverse cell types in the Allen Cell Types Database.
url	https://doi.org/10.1038/s41467-017-02718-3
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Systematic generation of biophysically detailed models for diverse cortical neuron types

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