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CAVE: An Open-Source Tool for Combined Analysis of Head-Mounted Calcium Imaging and Behavior in MATLAB

Calcium imaging in freely behaving rodents using head-mounted miniature microscopes is currently becoming an increasingly popular technique in neuroscience. Due to the large amounts of complex data that the technique produces, user friendly software is needed for quick and efficient processing. Here...

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Autores principales: Tegtmeier, Jennifer, Brosch, Marcel, Janitzky, Kathrin, Heinze, Hans-Jochen, Ohl, Frank W., Lippert, Michael T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6305314/
https://www.ncbi.nlm.nih.gov/pubmed/30618581
http://dx.doi.org/10.3389/fnins.2018.00958
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author Tegtmeier, Jennifer
Brosch, Marcel
Janitzky, Kathrin
Heinze, Hans-Jochen
Ohl, Frank W.
Lippert, Michael T.
author_facet Tegtmeier, Jennifer
Brosch, Marcel
Janitzky, Kathrin
Heinze, Hans-Jochen
Ohl, Frank W.
Lippert, Michael T.
author_sort Tegtmeier, Jennifer
collection PubMed
description Calcium imaging in freely behaving rodents using head-mounted miniature microscopes is currently becoming an increasingly popular technique in neuroscience. Due to the large amounts of complex data that the technique produces, user friendly software is needed for quick and efficient processing. Here, we present a new tool for analyzing calcium imaging data from head-mounted microscopes together with simultaneously acquired behavioral data: CAVE (Calcium ActiVity Explorer). CAVE bundles a unique set of algorithms specifically tailored to the analysis of single-photon imaging data from awake behaving animals including efficient motion correction and automatic ROI selection with manual audit and refinement. For behavioral analysis, CAVE can automatically track animal position and orientation. Individual behavioral epochs and external events can then be analyzed in correlation to calcium imaging and tracking data. Our program is written in MATLAB, the source code is open source and particularly focuses on providing a streamlined workflow for novice users while also retaining detailed configuration options for advanced users. We evaluate the performance of CAVE by investigating neural activity in hippocampus and somatosensory cortex. The fast analysis provided by CAVE allowed us to track activity in a large set of animals over the course of several months during exploration behavior, detailing the properties of onset and offset of observable activity and the visible cells per imaging location.
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spelling pubmed-63053142019-01-07 CAVE: An Open-Source Tool for Combined Analysis of Head-Mounted Calcium Imaging and Behavior in MATLAB Tegtmeier, Jennifer Brosch, Marcel Janitzky, Kathrin Heinze, Hans-Jochen Ohl, Frank W. Lippert, Michael T. Front Neurosci Neuroscience Calcium imaging in freely behaving rodents using head-mounted miniature microscopes is currently becoming an increasingly popular technique in neuroscience. Due to the large amounts of complex data that the technique produces, user friendly software is needed for quick and efficient processing. Here, we present a new tool for analyzing calcium imaging data from head-mounted microscopes together with simultaneously acquired behavioral data: CAVE (Calcium ActiVity Explorer). CAVE bundles a unique set of algorithms specifically tailored to the analysis of single-photon imaging data from awake behaving animals including efficient motion correction and automatic ROI selection with manual audit and refinement. For behavioral analysis, CAVE can automatically track animal position and orientation. Individual behavioral epochs and external events can then be analyzed in correlation to calcium imaging and tracking data. Our program is written in MATLAB, the source code is open source and particularly focuses on providing a streamlined workflow for novice users while also retaining detailed configuration options for advanced users. We evaluate the performance of CAVE by investigating neural activity in hippocampus and somatosensory cortex. The fast analysis provided by CAVE allowed us to track activity in a large set of animals over the course of several months during exploration behavior, detailing the properties of onset and offset of observable activity and the visible cells per imaging location. Frontiers Media S.A. 2018-12-18 /pmc/articles/PMC6305314/ /pubmed/30618581 http://dx.doi.org/10.3389/fnins.2018.00958 Text en Copyright © 2018 Tegtmeier, Brosch, Janitzky, Heinze, Ohl and Lippert. http://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
Tegtmeier, Jennifer
Brosch, Marcel
Janitzky, Kathrin
Heinze, Hans-Jochen
Ohl, Frank W.
Lippert, Michael T.
CAVE: An Open-Source Tool for Combined Analysis of Head-Mounted Calcium Imaging and Behavior in MATLAB
title CAVE: An Open-Source Tool for Combined Analysis of Head-Mounted Calcium Imaging and Behavior in MATLAB
title_full CAVE: An Open-Source Tool for Combined Analysis of Head-Mounted Calcium Imaging and Behavior in MATLAB
title_fullStr CAVE: An Open-Source Tool for Combined Analysis of Head-Mounted Calcium Imaging and Behavior in MATLAB
title_full_unstemmed CAVE: An Open-Source Tool for Combined Analysis of Head-Mounted Calcium Imaging and Behavior in MATLAB
title_short CAVE: An Open-Source Tool for Combined Analysis of Head-Mounted Calcium Imaging and Behavior in MATLAB
title_sort cave: an open-source tool for combined analysis of head-mounted calcium imaging and behavior in matlab
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6305314/
https://www.ncbi.nlm.nih.gov/pubmed/30618581
http://dx.doi.org/10.3389/fnins.2018.00958
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