The development of methods to evaluate experimental animal behavior using images

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  • Sakamoto Naoaki
    Animal Radiology, Graduate School of Agricultural and Life Sciences, The University of Tokyo
  • Miyazaki Yusuke
    Animal Radiology, Graduate School of Agricultural and Life Sciences, The University of Tokyo
  • Kobayashi Koji
    Animal Radiology, Graduate School of Agricultural and Life Sciences, The University of Tokyo Food and Animal Systemics, Graduate School of Agricultural and Life Sciences, The University of Tokyo
  • Minato Takashi
    Animal Radiology, Graduate School of Agricultural and Life Sciences, The University of Tokyo Food and Animal Systemics, Graduate School of Agricultural and Life Sciences, The University of Tokyo
  • Murata Takahisa
    Animal Radiology, Graduate School of Agricultural and Life Sciences, The University of Tokyo Food and Animal Systemics, Graduate School of Agricultural and Life Sciences, The University of Tokyo Veterinary Pharmacology, Graduate School of Agricultural and Life Sciences, The University of Tokyo

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  • 動物の心を読む～画像を用いた実験動物の行動解析技術の開発～
  • ドウブツ ノ ココロ オ ヨム : ガゾウ オ モチイタ ジッケン ドウブツ ノ コウドウ カイセキ ギジュツ ノ カイハツ

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Abstract

<p>In life science and medicine, we have been conducting research using laboratory animals such as mice, rats and monkeys. However, it is impossible for humans to fully understand the feelings and conditions of experimental animals with whom we cannot communicate. In particular, investigators have recently focused on brain function and have created animal models to mimic human depression, pain, and dementia through behavioral tests such as tail suspension and mazes. These methods allow for some evaluation of the animal’s condition. However, we cannot detect trivial behavioral changes that reflect the state of mind and body of the animals reproducibly and objectively. With improvements in imaging and information processing technology, it is now possible to photograph animals for extended periods of time and perform sophisticated analysis. Artificial intelligence (AI) can also perform learning and inference, or intelligent work (machine learning), for extended periods of time by processing higher levels of information and can find interpretations that humans are unaware of. To bring innovation to life science research using animals, it is necessary to integrate and utilize these technologies to digitize and extensively and deeply evaluate biological information and emotions of experimental animals. We have been developing some basic technologies for experimental animals by applying image analysis technology, AI, and mathematical analysis. In this review, we introduce the technologies we have developed, including the latest reports.</p>

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