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Machine Learning Methods for Environmental-Enrichment-Related Variations in Behavioral Responses of Laboratory Rats

机译:机器学习方法与实验大鼠行为反应中与环境富集有关的变化

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Environmental enrichment (EE) paradigms are designed to enhance laboratory animals surroundings to encourage natural behaviors. Some enrichment paradigms also include a social component, based on the social interactions typical of the genus and species. Novel automatic methodologies based on image are becoming useful tools to improve laboratory works. This paper present a first approach to the automatic image analysis of laboratory rats in EE: behaviour, drug effects and pathology. The new methodology is based on image and Machine Learning paradigms and will become a useful tool for Neuroscience issues.
机译:环境浓缩(EE)范式旨在增强实验动物的周围环境,以鼓励自然行为。基于属和种的典型社会互动,一些富集范式还包括社会成分。基于图像的新型自动方法正在成为改善实验室工作的有用工具。本文介绍了在EE中对实验大鼠进行自动图像分析的第一种方法:行为,药物作用和病理学。新方法基于图像和机器学习范式,将成为解决神经科学问题的有用工具。

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