Modular Tracking System for Treadmill-Based Rodent Experiments.

Area of Science:

• Neuroscience
• Biomedical Engineering
• Animal Behavior

Background:

• Accurate tracking of animal locomotion is crucial for correlating behavior with neural activity in neuroscience.
• Existing treadmill systems lack precise measurement of animal position and velocity, hindering detailed analysis.
• There is a need for accessible, high-fidelity tracking solutions for rodent treadmill experiments.

Purpose of the Study:

• To develop and validate a novel modular tracking system for real-time monitoring of animal position and velocity on treadmills.
• To provide a customizable and easily integrated solution for neuroscience research.
• To improve the accuracy of behavioral data in rodent locomotion studies.

Main Methods:

• A modular system using 3D-printed components and infrared (IR) break-beam sensors was designed.
• The system allows customizable configurations and supports digital/analog triggers for data synchronization.
• Position and velocity data were collected from mice on a treadmill and compared with DeepLabCut (a machine learning pose-estimation tool).

Main Results:

• The novel IR tracking system achieved real-time monitoring of animal position and velocity at 10 Hz.
• Strong correlations (average Spearman's rank correlation r = 0.8) were found between the system's data and post-processed video tracking.
• The system demonstrated accurate measurement of mouse locomotion at 0.1 m/s.

Conclusions:

• The developed modular IR tracking system offers an accurate and accessible solution for retrofitting existing treadmill setups.
• This system enhances the precision of behavioral analysis in neuroscience by providing reliable real-time locomotor data.
• It is particularly relevant for studying movement disorders in rodent models, offering precise tracking without complex computer vision.