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An open-source capacitive touch sensing device for three chamber social behavior test.

Giovanni Barbera¹, Bo Liang¹, Yan Zhang¹

¹Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD 21224, United States.

|September 17, 2020

Summary

This summary is machine-generated.

Researchers developed a novel capacitive touch device to automatically quantify social behavior in mice during behavioral tests. This automated system offers a faster, more objective alternative to manual analysis for studying neuropsychiatric disorders.

Keywords:

Automatic touch detection Closed-loop experiments Rodent models of brain disorders Social behavior

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Area of Science:

Neuroscience
Behavioral Science
Biomedical Engineering

Background:

Deficits in social behavior are common in neuropsychiatric disorders.
Studying social behavior in mouse models is crucial for understanding these disorders.
Manual annotation of rodent social behavior is time-consuming and subjective.

Purpose of the Study:

To develop an automated system for quantifying direct social exploration in mice.
To provide a real-time, objective measure of social interaction in behavioral tests.

Main Methods:

A capacitive touch device was developed for a modified three-chamber social behavior test.
Capacitive sensors detected direct physical touches, such as nose-pokes.
A Field-Programmable Gate Array (FPGA) platform transmitted real-time data to a host computer.

Main Results:

The capacitive touch device accurately quantified direct social exploration, yielding results comparable to manual annotation.
The system provided instantaneous analysis, significantly reducing post-hoc video scoring time.
The low-cost device enhanced data objectivity by minimizing experimenter involvement.

Conclusions:

The developed capacitive touch sensing system offers an efficient and objective method for analyzing rodent social behavior.
This technology can accelerate research into the neurobiology of social deficits in neuropsychiatric disorders.
Automated behavioral quantification is essential for advancing the study of complex behaviors in animal models.