A Real-Time Approach for Assessing Rodent Engagement in a Nose-Poking Go/No-Go Behavioral Task Using ArUco Markers

Area of Science:

• Behavioral neuroscience
• Computer vision
• Animal behavior assessment

Background:

• Manual scoring of animal behavior is labor-intensive and error-prone.
• Automated techniques are crucial for advancing brain-behavior interaction studies.
• Computer vision innovations offer marker-based and markerless tracking solutions.

Purpose of the Study:

• To present a protocol for automating rodent behavior scoring using ArUco markers.
• To enable precise assessment of rodent engagement in a nose-poking go/no-go task.
• To provide a computationally efficient and accessible tool for behavioral neuroscience.

Main Methods:

• Utilizing ArUco markers for marker-based tracking of rodent behavior.
• Detailed instructions for building a behavioral chamber and configuring software.
• Attaching ArUco markers to rodents and tracking marker positions in real-time.

Main Results:

• The protocol enables robust real-time behavioral analysis without extensive training data.
• Methods are computationally efficient, easy to implement, and adaptable.
• Engagement data analysis helps determine optimal task durations for data collection.

Conclusions:

• This ArUco marker-based approach streamlines behavioral scoring, enhancing research scalability and reproducibility.
• The protocol is accessible to laboratories with diverse resources due to minimal computational requirements.
• Freely available resources facilitate the adoption and customization of this automated behavioral analysis tool.