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CAVE：一种用于在MATLAB中对头戴式钙成像和行为进行联合分析的开源工具。

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

作者信息

Tegtmeier Jennifer, Brosch Marcel, Janitzky Kathrin, Heinze Hans-Jochen, Ohl Frank W, Lippert Michael T

机构信息

Systems Physiology of Learning, Leibniz Institute for Neurobiology, Magdeburg, Germany.

Department of Neurology, University of Magdeburg, Magdeburg, Germany.

出版信息

Front Neurosci. 2018 Dec 18;12:958. doi: 10.3389/fnins.2018.00958. eCollection 2018.

DOI:10.3389/fnins.2018.00958
PMID:30618581
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6305314/
Abstract

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.

摘要

使用头戴式微型显微镜对自由活动的啮齿动物进行钙成像，目前已成为神经科学领域越来越受欢迎的技术。由于该技术会产生大量复杂数据，因此需要用户友好型软件来进行快速高效的处理。在此，我们展示了一种新工具，用于分析来自头戴式显微镜的钙成像数据以及同时采集的行为数据：CAVE（钙活性探索器）。CAVE集成了一组独特的算法，这些算法专门针对清醒行为动物的单光子成像数据进行分析，包括高效的运动校正以及带有手动审核和优化功能的自动感兴趣区域（ROI）选择。对于行为分析，CAVE可以自动跟踪动物的位置和方向。然后可以将各个行为时期和外部事件与钙成像及跟踪数据相关联进行分析。我们的程序用MATLAB编写，源代码是开源的，特别注重为新手用户提供简化的工作流程，同时也为高级用户保留详细的配置选项。我们通过研究海马体和体感皮层中的神经活动来评估CAVE的性能。CAVE提供的快速分析使我们能够在几个月的探索行为过程中跟踪大量动物的活动，详细描述可观察活动的起始和结束特性以及每个成像位置的可见细胞。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd37/6305314/8433c73cb9b2/fnins-12-00958-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd37/6305314/3caf7f8700be/fnins-12-00958-g001.jpg
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