neurotic: Neuroscience Tool for Interactive Characterization

• Type of Material: Article
• Authors: Jeffrey P. Gill, Case Western Reserve University; Samuel Garcia, Universite Claude Bernard Lyon; Lena Ting, Emory University; Mengnan Wu, Emory University; Hillel J. Chiel, Case Western Reserve University
• Language: English
• Date: 2020-05-01
• Publisher: Society for Neuroscience
• Publication Version: Final Published Version
• Copyright Statement: © 2020, Society for Neuroscience. All rights reserved.
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1523/ENEURO.0085-20.2020
• Title of Journal or Parent Work: eNeuro
• Volume: 7
• Issue: 3
• Grant/Funding Information: This work was supported by the National Science Foundation Integrative and Organismal Systems Israel Science Foundation (NSF-IOS-BSF) Grant 1754869 and U.S.–Israel Binational Science Foundation Grant 2017624.
• Keywords: Life Sciences & Biomedicine; data sharing; Retractor muscle; visualization; video synchronization; behavioral neuroscience; Motor neuronal activity; open source; Neurosciences; Science & Technology; Python; Neurosciences & Neurology
• Research Categories: Biology, Neuroscience; Engineering, Biomedical; Biology, Bioinformatics

Abstract

A software tool for synchronization of video with signals would be of broad general use to behavioral neuro-scientists. A new program, called neurotic (NEUROscience Tool for Interactive Characterization), allows users to review and annotate signal data synchronized with video, performs simple initial analyses including signal filtering and spike detection, is easy to use, and supports a variety of file formats. The program also facilitates collaborations by using a portable specification for loading and processing data and retrieving data files from online sources. Two examples are shown in which the software is used to explore experimental datasets with extracellular nerve or muscle recordings and simultaneous video of behavior. The configuration specification for controlling how data are located, loaded, processed, and plotted is also summarized. Algorithms for spike detection and burst detection are demonstrated. This new program could be used in many applications in which behavior and signals need to be analyzed together.