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Evaluation of mouse behavioral responses to nutritive versus nonnutritive sugar using a deep learning-based 3D
Jineun Kim1, Dae-Gun Kim1, Wongyo Jung1
1Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
Journal of Neurogenetics
|February 15, 2023
Summary
Animals can sense sugar's nutritional value, not just its taste. Food-deprived mice show distinct approach behaviors towards nutritive sugar versus non-nutritive sugar, detected by AI Vision Analysis for Three-dimensional Action in Real-Time (AVATAR).
Area of Science:
- Neuroscience
- Animal Behavior
- Computational Biology
Background:
- Animals distinguish nutritive and non-nutritive sugars, preferring the former when deprived of food.
- This preference is independent of taste perception, suggesting other sensory cues are involved.
Purpose of the Study:
- To quantify detailed behavioral features during sugar licking using advanced technology.
- To investigate if animals exhibit different approach behaviors towards nutritive versus non-nutritive sugar before consumption.
Main Methods:
- Implementation of a multi-vision, deep learning-based 3D pose estimation system: AI Vision Analysis for Three-dimensional Action in Real-Time (AVATAR).
- Analysis of behavioral sequences in mice during interactions with nutritive and non-nutritive sugar solutions.
Main Results:
- Mice displayed significantly different approach behaviors towards nutritive and non-nutritive sugar, even prior to licking.
- Behavioral sequences diverged significantly over time as mice approached nutritive versus non-nutritive sugar.
Conclusions:
- The nutritional content of sugar influences not only consumption but also elicits specific feeding behaviors in deprived mice.
- AI-powered behavioral analysis provides novel insights into sensory-driven feeding strategies.
