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Revealing the structure of pharmacobehavioral space through Motion Sequencing
Understanding how genes, drugs and neural circuits influence behavior requires the ability to effectively organize information about similarities and differences within complex behavioral datasets. Motion Sequencing (MoSeq) is an ethologically-inspired behavioral analysis method that identifies modu...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7606807/ https://www.ncbi.nlm.nih.gov/pubmed/32958923 http://dx.doi.org/10.1038/s41593-020-00706-3 |
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author | Wiltschko, Alexander B. Tsukahara, Tatsuya Zeine, Ayman Anyoha, Rockwell Gillis, Winthrop F. Markowitz, Jeffrey E. Peterson, Ralph E. Katon, Jesse Johnson, Matthew J. Datta, Sandeep Robert |
author_facet | Wiltschko, Alexander B. Tsukahara, Tatsuya Zeine, Ayman Anyoha, Rockwell Gillis, Winthrop F. Markowitz, Jeffrey E. Peterson, Ralph E. Katon, Jesse Johnson, Matthew J. Datta, Sandeep Robert |
author_sort | Wiltschko, Alexander B. |
collection | PubMed |
description | Understanding how genes, drugs and neural circuits influence behavior requires the ability to effectively organize information about similarities and differences within complex behavioral datasets. Motion Sequencing (MoSeq) is an ethologically-inspired behavioral analysis method that identifies modular components of 3D mouse body language called “syllables.” Here we show that MoSeq effectively parses behavioral differences and captures similarities elicited by a panel of neuro- and psychoactive drugs administered to a cohort of nearly 700 mice. MoSeq identifies syllables that are characteristic of individual drugs; we leverage this finding to reveal specific on- and off-target effects of both established and candidate therapeutics in a mouse model of autism spectrum disorder. These results demonstrate that MoSeq can meaningfully organize large-scale behavioral data, illustrate the power of a fundamentally modular description of behavior, and suggest that behavioral syllables represent a new class of druggable target. |
format | Online Article Text |
id | pubmed-7606807 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-76068072021-03-21 Revealing the structure of pharmacobehavioral space through Motion Sequencing Wiltschko, Alexander B. Tsukahara, Tatsuya Zeine, Ayman Anyoha, Rockwell Gillis, Winthrop F. Markowitz, Jeffrey E. Peterson, Ralph E. Katon, Jesse Johnson, Matthew J. Datta, Sandeep Robert Nat Neurosci Article Understanding how genes, drugs and neural circuits influence behavior requires the ability to effectively organize information about similarities and differences within complex behavioral datasets. Motion Sequencing (MoSeq) is an ethologically-inspired behavioral analysis method that identifies modular components of 3D mouse body language called “syllables.” Here we show that MoSeq effectively parses behavioral differences and captures similarities elicited by a panel of neuro- and psychoactive drugs administered to a cohort of nearly 700 mice. MoSeq identifies syllables that are characteristic of individual drugs; we leverage this finding to reveal specific on- and off-target effects of both established and candidate therapeutics in a mouse model of autism spectrum disorder. These results demonstrate that MoSeq can meaningfully organize large-scale behavioral data, illustrate the power of a fundamentally modular description of behavior, and suggest that behavioral syllables represent a new class of druggable target. 2020-09-21 2020-11 /pmc/articles/PMC7606807/ /pubmed/32958923 http://dx.doi.org/10.1038/s41593-020-00706-3 Text en Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms |
spellingShingle | Article Wiltschko, Alexander B. Tsukahara, Tatsuya Zeine, Ayman Anyoha, Rockwell Gillis, Winthrop F. Markowitz, Jeffrey E. Peterson, Ralph E. Katon, Jesse Johnson, Matthew J. Datta, Sandeep Robert Revealing the structure of pharmacobehavioral space through Motion Sequencing |
title | Revealing the structure of pharmacobehavioral space through Motion Sequencing |
title_full | Revealing the structure of pharmacobehavioral space through Motion Sequencing |
title_fullStr | Revealing the structure of pharmacobehavioral space through Motion Sequencing |
title_full_unstemmed | Revealing the structure of pharmacobehavioral space through Motion Sequencing |
title_short | Revealing the structure of pharmacobehavioral space through Motion Sequencing |
title_sort | revealing the structure of pharmacobehavioral space through motion sequencing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7606807/ https://www.ncbi.nlm.nih.gov/pubmed/32958923 http://dx.doi.org/10.1038/s41593-020-00706-3 |
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