title: M-Track: A New Software for Automated Detection of Grooming Trajectories in Mice.
abstract: Grooming is a complex and robust innate behavior, commonly performed by most vertebrate species. In mice, grooming consists of a series of stereotyped patterned strokes, performed along the rostro-caudal axis of the body. The frequency and duration of each grooming episode is sensitive to changes in stress levels, social interactions and pharmacological manipulations, and is therefore used in behavioral studies to gain insights into the function of brain regions that control movement execution and anxiety. Traditional approaches to analyze grooming rely on manually scoring the time of onset and duration of each grooming episode, and are often performed on grooming episodes triggered by stress exposure, which may not be entirely representative of spontaneous grooming in freely-behaving mice. This type of analysis is time-consuming and provides limited information about finer aspects of grooming behaviors, which are important to understand movement stereotypy and bilateral coordination in mice. Currently available commercial and freeware video-tracking software allow automated tracking of the whole body of a mouse or of its head and tail, not of individual forepaws. Here we describe a simple experimental set-up and a novel open-source code, named M-Track, for simultaneously tracking the movement of individual forepaws during spontaneous grooming in multiple freely-behaving mice. This toolbox provides a simple platform to perform trajectory analysis of forepaw movement during distinct grooming episodes. By using M-track we show that, in C57BL/6 wild type mice, the speed and bilateral coordination of the left and right forepaws remain unaltered during the execution of distinct grooming episodes. Stress exposure induces a profound increase in the length of the forepaw grooming trajectories. M-Track provides a valuable and user-friendly interface to streamline the analysis of spontaneous grooming in biomedical research studies.
authors.affiliation: Department of Computer Science, State University of New York Polytechnic Institute, Utica, New York, United States of America.
authors.forename: Sheldon L
authors.initials: SL
authors.lastname: Reeves
authors.affiliation: Department of Biology, State University of New York Albany, Albany, New York, United States of America.
authors.forename: Kelsey E
authors.identifier: 0000-0002-3072-4830
authors.initials: KE
authors.lastname: Fleming
authors.affiliation: Department of Computer Science, State University of New York Albany, Albany, New York, United States of America.
authors.forename: Lin
authors.initials: L
authors.lastname: Zhang
authors.affiliation: Department of Biology, State University of New York Albany, Albany, New York, United States of America.
authors.forename: Annalisa
authors.identifier: 0000-0003-4975-093X
authors.initials: A
authors.lastname: Scimemi
mesh_terms: D000818:Animals; D001522:Behavior, Animal / Q000502:physiology*; D019295:Computational Biology; D005260:Female; D006120:Grooming / Q000502:physiology*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D051379:Mice; D008810:Mice, Inbred C57BL; D009068:Movement / Q000502:physiology*; D012984:Software; D014741:Video Recording