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WaveMAP for identifying putative cell types from in vivo electrophysiology
Action potential spike widths are used to classify cell types as either excitatory or inhibitory; however, this approach obscures other differences in waveform shape useful for identifying more fine-grained cell types. Here, we present a protocol for using WaveMAP to generate nuanced average wavefor...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10220268/ https://www.ncbi.nlm.nih.gov/pubmed/37220000 http://dx.doi.org/10.1016/j.xpro.2023.102320 |
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author | Lee, Kenji Carr, Nicole Perliss, Alec Chandrasekaran, Chandramouli |
author_facet | Lee, Kenji Carr, Nicole Perliss, Alec Chandrasekaran, Chandramouli |
author_sort | Lee, Kenji |
collection | PubMed |
description | Action potential spike widths are used to classify cell types as either excitatory or inhibitory; however, this approach obscures other differences in waveform shape useful for identifying more fine-grained cell types. Here, we present a protocol for using WaveMAP to generate nuanced average waveform clusters more closely linked to underlying cell types. We describe steps for installing WaveMAP, preprocessing data, and clustering waveform into putative cell types. We also detail cluster evaluation for functional differences and interpretation of WaveMAP output. For complete details on the use and execution of this protocol, please refer to Lee et al. (2021).(1) |
format | Online Article Text |
id | pubmed-10220268 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-102202682023-05-28 WaveMAP for identifying putative cell types from in vivo electrophysiology Lee, Kenji Carr, Nicole Perliss, Alec Chandrasekaran, Chandramouli STAR Protoc Protocol Action potential spike widths are used to classify cell types as either excitatory or inhibitory; however, this approach obscures other differences in waveform shape useful for identifying more fine-grained cell types. Here, we present a protocol for using WaveMAP to generate nuanced average waveform clusters more closely linked to underlying cell types. We describe steps for installing WaveMAP, preprocessing data, and clustering waveform into putative cell types. We also detail cluster evaluation for functional differences and interpretation of WaveMAP output. For complete details on the use and execution of this protocol, please refer to Lee et al. (2021).(1) Elsevier 2023-05-22 /pmc/articles/PMC10220268/ /pubmed/37220000 http://dx.doi.org/10.1016/j.xpro.2023.102320 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Protocol Lee, Kenji Carr, Nicole Perliss, Alec Chandrasekaran, Chandramouli WaveMAP for identifying putative cell types from in vivo electrophysiology |
title | WaveMAP for identifying putative cell types from in vivo electrophysiology |
title_full | WaveMAP for identifying putative cell types from in vivo electrophysiology |
title_fullStr | WaveMAP for identifying putative cell types from in vivo electrophysiology |
title_full_unstemmed | WaveMAP for identifying putative cell types from in vivo electrophysiology |
title_short | WaveMAP for identifying putative cell types from in vivo electrophysiology |
title_sort | wavemap for identifying putative cell types from in vivo electrophysiology |
topic | Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10220268/ https://www.ncbi.nlm.nih.gov/pubmed/37220000 http://dx.doi.org/10.1016/j.xpro.2023.102320 |
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