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Decontaminate Traces From Fluorescence Calcium Imaging Videos Using Targeted Non-negative Matrix Factorization

Fluorescence microscopy and genetically encoded calcium indicators help understand brain function by recording large-scale in vivo videos in assorted animal models. Extracting the fluorescent transients that represent active periods of individual neurons is a key step when analyzing imaging videos....

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Detalles Bibliográficos
Autores principales: Bao, Yijun, Redington, Emily, Agarwal, Agnim, Gong, Yiyang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8815790/
https://www.ncbi.nlm.nih.gov/pubmed/35126042
http://dx.doi.org/10.3389/fnins.2021.797421
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author Bao, Yijun
Redington, Emily
Agarwal, Agnim
Gong, Yiyang
author_facet Bao, Yijun
Redington, Emily
Agarwal, Agnim
Gong, Yiyang
author_sort Bao, Yijun
collection PubMed
description Fluorescence microscopy and genetically encoded calcium indicators help understand brain function by recording large-scale in vivo videos in assorted animal models. Extracting the fluorescent transients that represent active periods of individual neurons is a key step when analyzing imaging videos. Non-specific calcium sources and background adjacent to segmented neurons contaminate the neurons’ temporal traces with false transients. We developed and characterized a novel method, temporal unmixing of calcium traces (TUnCaT), to quickly and accurately unmix the calcium signals of neighboring neurons and background. Our algorithm used background subtraction to remove the false transients caused by background fluctuations, and then applied targeted non-negative matrix factorization to remove the false transients caused by neighboring calcium sources. TUnCaT was more accurate than existing algorithms when processing multiple experimental and simulated datasets. TUnCaT’s speed was faster than or comparable to existing algorithms.
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spelling pubmed-88157902022-02-05 Decontaminate Traces From Fluorescence Calcium Imaging Videos Using Targeted Non-negative Matrix Factorization Bao, Yijun Redington, Emily Agarwal, Agnim Gong, Yiyang Front Neurosci Neuroscience Fluorescence microscopy and genetically encoded calcium indicators help understand brain function by recording large-scale in vivo videos in assorted animal models. Extracting the fluorescent transients that represent active periods of individual neurons is a key step when analyzing imaging videos. Non-specific calcium sources and background adjacent to segmented neurons contaminate the neurons’ temporal traces with false transients. We developed and characterized a novel method, temporal unmixing of calcium traces (TUnCaT), to quickly and accurately unmix the calcium signals of neighboring neurons and background. Our algorithm used background subtraction to remove the false transients caused by background fluctuations, and then applied targeted non-negative matrix factorization to remove the false transients caused by neighboring calcium sources. TUnCaT was more accurate than existing algorithms when processing multiple experimental and simulated datasets. TUnCaT’s speed was faster than or comparable to existing algorithms. Frontiers Media S.A. 2022-01-21 /pmc/articles/PMC8815790/ /pubmed/35126042 http://dx.doi.org/10.3389/fnins.2021.797421 Text en Copyright © 2022 Bao, Redington, Agarwal and Gong. 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
Bao, Yijun
Redington, Emily
Agarwal, Agnim
Gong, Yiyang
Decontaminate Traces From Fluorescence Calcium Imaging Videos Using Targeted Non-negative Matrix Factorization
title Decontaminate Traces From Fluorescence Calcium Imaging Videos Using Targeted Non-negative Matrix Factorization
title_full Decontaminate Traces From Fluorescence Calcium Imaging Videos Using Targeted Non-negative Matrix Factorization
title_fullStr Decontaminate Traces From Fluorescence Calcium Imaging Videos Using Targeted Non-negative Matrix Factorization
title_full_unstemmed Decontaminate Traces From Fluorescence Calcium Imaging Videos Using Targeted Non-negative Matrix Factorization
title_short Decontaminate Traces From Fluorescence Calcium Imaging Videos Using Targeted Non-negative Matrix Factorization
title_sort decontaminate traces from fluorescence calcium imaging videos using targeted non-negative matrix factorization
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8815790/
https://www.ncbi.nlm.nih.gov/pubmed/35126042
http://dx.doi.org/10.3389/fnins.2021.797421
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