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.
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Nature Publishing Group
2018-02-01
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Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-017-02718-3 |
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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 |
work_keys_str_mv |
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