Technology Report ARTICLE
CAVE: an Open-Source Tool for Combined Analysis of Head-Mounted Calcium Imaging and Behavior in MATLAB
- 1Systems Physiology of Neuroscience, Leibniz Institute for Neurobiology (LG), Germany
- 2Department of Neurology, Medizinische Fakultät, Universitätsklinikum Magdeburg, Germany
- 3Center for Behavioral Brain Sciences, Germany
- 4Faculty for Natural Sciences, Otto-von-Guericke Universität Magdeburg, Germany
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.
Keywords: Single Photon head-mounted calcium imaging, in vivo imaging, freely moving, Awake behaving mice, Open Source Software, Image analysis (IA)
Received: 26 Jun 2018;
Accepted: 03 Dec 2018.
Edited by:Yaroslav O. Halchenko, Dartmouth College, United States
Reviewed by:Henry Lütcke, ETH Zürich, Switzerland
Christoph Schmidt-Hieber, Institut Pasteur, France
Copyright: © 2018 Tegtmeier, Brosch, Janitzky, Heinze, Ohl and Lippert. 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.
* Correspondence: Dr. Michael T. Lippert, Leibniz Institute for Neurobiology (LG), Systems Physiology of Neuroscience, Magdeburg, Germany, firstname.lastname@example.org