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Long-term scratching analysis of mice using machine learning
Koji Kobayashi1, Yusuke Miyazaki2, Naoaki Sakamoto2
1Department of Food and Animal Systemics, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo 113-8657, Japan.
Abstract:
Pruritus is a bothersome symptom that can occur at any time and is caused by a variety of physical and mental disorders. There is an urgent need to elucidate the detailed pathophysiology using animal models. Using image analysis and machine learning, we analyzed the scratching behavior of BALB/c mouse under both light and dark conditions and objectively quantified persistency, strength, and amount of pruritus. A 24-h analysis in naive mice revealed that mice scratched themselves more frequently and longer in the light period than in the dark period, and that scratching behavior in the light period was hard to extinguish. Administration of dinitrofluorobenzene (DNFB) induced persistent and biphasic scratching behavior while the vehicle only induced transient one. Of interest, DNFB-induced scratching behavior occurred even when the mice were resting. These features are revealed for the first time, highlighting the usefulness of automated long-term scratching behavior analysis.
Insights
Researchers developed an automated method using machine learning to quantify mouse scratching behavior, revealing new insights into pruritus (itch) and its persistence, especially under light conditions.
Area of Science:
- Animal Behavior
- Computational Biology
- Dermatology
Background:
- Pruritus is a common symptom linked to various disorders, necessitating better understanding through animal models.
- Current methods for assessing pruritus in research settings lack objective quantification.
Purpose of the Study:
- To develop and validate an automated system for objective, long-term analysis of scratching behavior in mice.
- To characterize the detailed patterns of pruritus in naive and chemically induced conditions.
Main Methods:
- Utilized image analysis and machine learning algorithms to track and quantify mouse scratching.
- Performed 24-hour continuous monitoring of BALB/c mice under light and dark conditions.
- Administered dinitrofluorobenzene (DNFB) to induce pruritus and analyzed behavioral responses.
Main Results:
- Naive mice exhibited significantly more frequent and prolonged scratching during light periods, which was resistant to extinction.
- Dinitrofluorobenzene (DNFB) induced persistent, biphasic scratching behavior compared to transient vehicle responses.
- Scratching behavior was observed even during resting periods in DNFB-treated mice.
Conclusions:
- Automated long-term scratching behavior analysis provides a powerful tool for objective pruritus research.
- Mouse scratching exhibits distinct temporal patterns influenced by light and chemical stimuli.
- This methodology offers novel insights into the pathophysiology of pruritus.
