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Updated: May 23, 2025

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Automatic quantification of disgust reactions in mice using machine learning.

Shizuki Inaba1, Naofumi Uesaka2, Daisuke H Tanaka3

  • 1Department of Cognitive Neurobiology, Graduate School of Medical and Dental Sciences, Institute of Science Tokyo, 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8519, Japan.

Scientific Reports
|May 21, 2025
PubMed
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This study introduces a machine learning method to automatically count disgust reactions in mice, significantly reducing analysis time. The automated system accurately quantifies these reactions, aiding large-scale experiments.

Area of Science:

  • Neuroscience
  • Animal Behavior
  • Machine Learning

Background:

  • Disgust is a primary emotion crucial for protection against toxins and infections.
  • Quantifying disgust reactions in rodents traditionally involves time-consuming manual video analysis.
  • The taste reactivity test is a key method for assessing disgust in animal models.

Purpose of the Study:

  • To develop and validate an automated method for quantifying disgust reactions in mice using machine learning.
  • To reduce the labor and time associated with analyzing disgust responses in rodent studies.

Main Methods:

  • Utilized DeepLabCut for automated tracking of mouse facial and paw movements.
  • Employed a random forest classifier trained on manually labeled disgust reaction data.

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  • Validated the automated method against manual counting using a test dataset.

    • Main Results:

    • The automated method achieved high correlation (Pearson's r = 0.97) with manual counts of disgust reactions.
    • Machine learning significantly decreased the time and effort required for data analysis.
    • The developed classifier accurately identified and quantified different types of disgust reactions.

    Conclusions:

    • The automated machine learning approach provides a reliable and efficient alternative to manual analysis of disgust reactions in mice.
    • This method facilitates large-scale screening and long-term experiments requiring substantial quantification of disgust responses.
    • The findings support the broader implementation of the taste reactivity test in behavioral neuroscience research.