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Updated: Jun 10, 2025

Tracking Rats in Operant Conditioning Chambers Using a Versatile Homemade Video Camera and DeepLabCut

Tracking Rats in Operant Conditioning Chambers Using a Versatile Homemade Video Camera and DeepLabCut

Published on: June 15, 2020

REVEALS: an open-source multi-camera GUI for rodent behavior acquisition.

Rhushikesh A Phadke¹, Austin M Wetzel², Luke A Fournier³

¹Molecular Biology, Cell Biology and Biochemistry Program, Boston University, Boston, MA, United States.

Cerebral Cortex (New York, N.Y. : 1991)

|October 18, 2024

Summary

This summary is machine-generated.

Researchers can now easily capture detailed rodent behavior using multiple cameras with REVEALS (Rodent Behavior Multi-Camera Laboratory Acquisition) software. This open-source tool enhances data collection for neuroscience research.

Keywords:

behavioral tracking mouse models multi-camera software neuroscience unbiased behavioral analysis

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Last Updated: Jun 10, 2025

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Area of Science:

Neuroscience
Behavioral Science
Bioengineering

Background:

Understanding mouse behavior is vital for brain research, but current methods for data acquisition are often costly and inaccessible.
Simultaneous multi-camera recording for detailed behavioral analysis is particularly challenging.

Purpose of the Study:

To develop an affordable, accessible, and user-friendly graphical user interface for acquiring rodent behavioral data.
To enable efficient multi-camera synchronized recording for comprehensive behavioral phenotyping.

Main Methods:

Development of REVEALS (Rodent Behavior Multi-Camera Laboratory Acquisition), an open-source graphical user interface.
Integration with common USB3 cameras for synchronized video recording.
Validation using DeepLabCut for accurate rodent behavior capture across various tasks.

Main Results:

REVEALS provides stable, reliable, and accurate multi-camera data acquisition for rodent behavior.
The software streamlines the process, enabling efficient collection of large behavioral datasets.
REVEALS is compatible with existing deep learning pipelines like DeepLabCut and MoSeq.

Conclusions:

REVEALS offers a valuable, open-source solution for researchers to collect multi-perspective behavioral data.
This tool facilitates the identification and characterization of complex behavioral phenotypes using deep learning.
The software enhances accessibility and efficiency in rodent behavior research.