hkucukdereli/m-track

M-Track: A new software for automated detection of forepaw trajectories in mice

M-Track

A new software for automated detection of forepaw trajectories in mice.

SYNOPSIS AND MOTIVATION
M-Track is a new software that allows automated detection of labelled forepaws in freely behaving in mice. M-Track uses color detection and back projection algorithms to locate the position of color-labelled paws in videos of multiple freely-behaving mice. M-Track has an intuitive graphical user interface and provides a new tool to obtain quantitative information on fine aspects of spontaneous grooming behaviors, to improve the current understanding of the functional properties of brain neuronal circuits in biomedical research studies.

OVERVIEW
M-Track is an open-source software designed to detect the location of mice and of their labelled forepaws in video files. M-Track is compatible with debian and non-debian Linux installations, Mac OS X and Microsoft Windows operating systems. M-Track uses the Python language and the OpenCV, PyQt and Numpy libraries.

Two executable standalone versions of M-Track for Linux and Microsoft Windows platforms are currently available: one of them allows the user to visualize the orientation of the mouse body (v1r1), the other does not have this feature (v1r2).

Linux:
M-Track_LIN_v1r1 - The user can visualize the orientation of the mouse body
M-Track_LIN_v1r2 - The user cannot visualize the orientation of the mouse body

Microsoft Windows
M-Track_WIN_v1r1 - The user can visualize the orientation of the mouse body
M-Track_WIN_v1r2 - The user cannot visualize the orientation of the mouse body

The Sample videos and output files folder contains two sample video files, acquired on a C57BL/6 (black fur) and on a Swiss Webster mouse (white fur). Running M-Track on these sample Video files generates output files like the ones included in this folder, named Sample_Video_Black_Mice_Output.txt and Sample_Video_White_Mice_Output.txt.

INSTALLATION FOR VERSIONS v1r1 and v1r2
M-Track requires the following languages and libraries:

• Python 2.7
• OpenCV 3.0
• PyQt 4.8
• Numpy 1.10.4

INSTALLATION FOR VERSIONS v2r1 and v2r2
M-Track requires the following languages and libraries:

• Python 2.7
• OpenCV 3.2
• PyQt 4.11
• Numpy 1.13.1

In addition, M-Track requires the following package files:

• MTrack_Qt.py
• MTrack.py
• RoiLabel.py
• ColorLabel.py
• InfoDialog.py

Detailed instructions for software installation and video analysis are provided in the Installation file in the Instructions folder. All required package files are in the Package files folder.

TESTS
To test M-Track, run MTrack_Qt.py, press Load to visualize one of the two example files in the folder named Sample videos and output files, proceed through the analysis steps described in the GUI and analysis file in the Instructions folder and press Execute.

CONTRIBUTORS
M-Track was created by:
Sheldon L. Reeves ([email protected]; [email protected])
Lin Zhang ([email protected]; [email protected])
Matthew S. Brandon ([email protected]; [email protected]) Annalisa Scimemi ([email protected]; [email protected])
For support and questions, please contact Annalisa Scimemi ([email protected])
All work was funded by SUNY Albany, SUNY Albany Research Foundation and SUNY STEM Research Passport Program.

HISTORY
08-2015 - The first version of M-Track was created by Sheldon L. Reeves and Annalisa Scimemi. This version was compatible with Linux platforms and used Python 3.0, OpenCV 3.0 and PyQt 5.4.

07-2016 - An updated version of M-Track, available from this repository, was developed by Lin Zhang and Annalisa Scimemi using Python 2.7, OpenCV 3.0 and PyQt 4.8. This version of M-Track has added functionalities and fixes and is compatible with Linux, Mac OS X and Microsoft Windows platforms.

08-2017 - Anaconda1 is no longer available for new users and Anaconda2 requires using OpenCV 3.2. An updated version of M-Track, available from this repository, was developed by Matthew Brandon and Annalisa Scimemi using Python 2.7, OpenCV 3.2 and PyQt 4.11. This version of M-Track allows it to work with OpenCV 3.2.

LICENSE
Please review the terms and conditions of the license in the LICENSE_NPOSL-3.0 section of this repository before downloading the M-Track software. By downloading the M-Track software from this site you agree to be legally bound by the terms and conditions of the Open Source Initiative Non-Profit Open Software License 3.0
(NPOSL-3.0; https://tldrlegal.com/license/non-profit-open-software-license-3.0-(nposl-3.0)).