Automated Analysis of Stroke Mouse Trajectory Data With Traja

Area of Science:

• Neuroscience
• Behavioral Science
• Computational Biology

Background:

• Manual phenotyping of mouse activity is time-consuming, prone to bias, and stressful for animals.
• Quantitative analysis of locomotion and walking patterns is crucial for neurobehavioral research.
• There is a need for efficient, objective tools for long-term monitoring of mouse behavior.

Purpose of the Study:

• To introduce and demonstrate the utility of Traja, an open-source trajectory analysis software.
• To apply Traja for semi-automated analysis of high-throughput mouse home-cage data in neurobehavioral research.
• To quantify movement parameters like distance, velocity, turnings, and laterality in stroke-induced mice.

Main Methods:

• Utilized Traja, a platform-independent, open-source software for trajectory analysis.
• Recorded 24/7 activity of transient stroke-induced female C57BL/6 mice using Digital Ventilated Cages (DVC).
• Analyzed movement patterns, including traveled distance, velocity, and laterality, using Traja.

Main Results:

• Traja successfully quantified significant changes in activity, velocity, and distance walked over time.
• Both control and Fortasyn-treated mice showed increased walked distance and velocity.
• No significant diet effect was observed in turning preference (laterality) or distance traveled.

Conclusions:

• Traja provides a valuable tool for the computational analysis of 24/7 mouse locomotion in home-cage environments.
• The open-source nature of Traja supports independent development and validation of numerical methods.
• This software aids in objective, high-throughput phenotyping for neurobehavioral research and movement disorder studies.