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利用基于深度学习的 3D 实时姿势估计系统评估小鼠对营养性与非营养性糖的行为反应。

Evaluation of mouse behavioral responses to nutritive versus nonnutritive sugar using a deep learning-based 3D real-time pose estimation system.

机构信息

Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.

出版信息

J Neurogenet. 2023 Mar-Dec;37(1-2):78-83. doi: 10.1080/01677063.2023.2174982. Epub 2023 Feb 15.

DOI:10.1080/01677063.2023.2174982
PMID:36790034
Abstract

Animals are able to detect the nutritional content of sugar independently of taste. When given a choice between nutritive sugar and nonnutritive sugar, animals develop a preference for nutritive sugar over nonnutritive sugar during a period of food deprivation (Buchanan , 2022; Dus , 2011; 2015; Tan , 2020; Tellez , 2016). To quantify behavioral features during an episode of licking nutritive versus nonnutritive sugar, we implemented a multi-vision, deep learning-based 3D pose estimation system, termed the AI Vision Analysis for Three-dimensional Action in Real-Time (AVATAR)(Kim , 2022). Using this method, we found that mice exhibit significantly different approach behavioral responses toward nutritive sugar versus nonnutritive sugar even before licking a sugar solution. Notably, the behavioral sequences during the approach toward versus nonnutritive sugar became significantly different over time. These results suggest that the nutritional value of sugar not only promotes its consumption but also elicits distinct repertoires of feeding behavior in deprived mice.

摘要

动物能够独立于味觉来感知糖的营养价值。当动物在食物匮乏期间面临营养糖和非营养糖的选择时,它们会选择营养糖而非非营养糖(Buchanan,2022;Dus,2011;2015;Tan,2020;Tellez,2016)。为了在舔食营养糖和非营养糖的过程中量化行为特征,我们开发了一个多视图、基于深度学习的 3D 姿势估计系统,称为实时三维动作的人工智能视觉分析(AVATAR)(Kim,2022)。使用这种方法,我们发现即使在舔食糖水之前,老鼠对营养糖和非营养糖的接近行为反应就存在显著差异。值得注意的是,接近营养糖和非营养糖的行为序列随着时间的推移变得明显不同。这些结果表明,糖的营养价值不仅促进了其消费,而且在饥饿的老鼠中引发了独特的进食行为反应。

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