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PyRAT: An Open-Source Python Library for Animal Behavior Analysis

Here we developed an open-source Python-based library called Python rodent Analysis and Tracking (PyRAT). Our library analyzes tracking data to classify distinct behaviors, estimate traveled distance, speed and area occupancy. To classify and cluster behaviors, we used two unsupervised algorithms: h...

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Detalles Bibliográficos
Autores principales: De Almeida, Tulio Fernandes, Spinelli, Bruno Guedes, Hypolito Lima, Ramón, Gonzalez, Maria Carolina, Rodrigues, Abner Cardoso
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9125180/
https://www.ncbi.nlm.nih.gov/pubmed/35615283
http://dx.doi.org/10.3389/fnins.2022.779106
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author De Almeida, Tulio Fernandes
Spinelli, Bruno Guedes
Hypolito Lima, Ramón
Gonzalez, Maria Carolina
Rodrigues, Abner Cardoso
author_facet De Almeida, Tulio Fernandes
Spinelli, Bruno Guedes
Hypolito Lima, Ramón
Gonzalez, Maria Carolina
Rodrigues, Abner Cardoso
author_sort De Almeida, Tulio Fernandes
collection PubMed
description Here we developed an open-source Python-based library called Python rodent Analysis and Tracking (PyRAT). Our library analyzes tracking data to classify distinct behaviors, estimate traveled distance, speed and area occupancy. To classify and cluster behaviors, we used two unsupervised algorithms: hierarchical agglomerative clustering and t-distributed stochastic neighbor embedding (t-SNE). Finally, we built algorithms that associate the detected behaviors with synchronized neural data and facilitate the visualization of this association in the pixel space. PyRAT is fully available on GitHub: https://github.com/pyratlib/pyrat.
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spelling pubmed-91251802022-05-24 PyRAT: An Open-Source Python Library for Animal Behavior Analysis De Almeida, Tulio Fernandes Spinelli, Bruno Guedes Hypolito Lima, Ramón Gonzalez, Maria Carolina Rodrigues, Abner Cardoso Front Neurosci Neuroscience Here we developed an open-source Python-based library called Python rodent Analysis and Tracking (PyRAT). Our library analyzes tracking data to classify distinct behaviors, estimate traveled distance, speed and area occupancy. To classify and cluster behaviors, we used two unsupervised algorithms: hierarchical agglomerative clustering and t-distributed stochastic neighbor embedding (t-SNE). Finally, we built algorithms that associate the detected behaviors with synchronized neural data and facilitate the visualization of this association in the pixel space. PyRAT is fully available on GitHub: https://github.com/pyratlib/pyrat. Frontiers Media S.A. 2022-05-09 /pmc/articles/PMC9125180/ /pubmed/35615283 http://dx.doi.org/10.3389/fnins.2022.779106 Text en Copyright © 2022 De Almeida, Spinelli, Hypolito Lima, Gonzalez and Rodrigues. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
De Almeida, Tulio Fernandes
Spinelli, Bruno Guedes
Hypolito Lima, Ramón
Gonzalez, Maria Carolina
Rodrigues, Abner Cardoso
PyRAT: An Open-Source Python Library for Animal Behavior Analysis
title PyRAT: An Open-Source Python Library for Animal Behavior Analysis
title_full PyRAT: An Open-Source Python Library for Animal Behavior Analysis
title_fullStr PyRAT: An Open-Source Python Library for Animal Behavior Analysis
title_full_unstemmed PyRAT: An Open-Source Python Library for Animal Behavior Analysis
title_short PyRAT: An Open-Source Python Library for Animal Behavior Analysis
title_sort pyrat: an open-source python library for animal behavior analysis
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9125180/
https://www.ncbi.nlm.nih.gov/pubmed/35615283
http://dx.doi.org/10.3389/fnins.2022.779106
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