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  • 标题:An odor detection system based on automatically trained mice by relative go no-go olfactory operant conditioning
  • 本地全文:下载
  • 作者:Jing He ; JingKuan Wei ; Joshua D. Rizak
  • 期刊名称:Scientific Reports
  • 电子版ISSN:2045-2322
  • 出版年度:2015
  • 卷号:5
  • DOI:10.1038/srep10019
  • 出版社:Springer Nature
  • 摘要:Odor detection applications are needed by human societies in various circumstances. Rodent offers unique advantages in developing biologic odor detection systems. This report outlines a novel apparatus designed to train maximum 5 mice automatically to detect odors using a new olfactory, relative go no-go, operant conditioning paradigm. The new paradigm offers the chance to measure real-time reliability of individual animal’s detection behavior with changing responses. All of 15 water-deprivation mice were able to learn to respond to unpredictable delivering of the target odor with higher touch frequencies via a touch sensor. The mice were continually trained with decreasing concentrations of the target odor ( n -butanol), the average correct percent significantly dropped when training at 0.01% solution concentration; the alarm algorithm showed excellent recognition of odor detection behavior of qualified mice group through training. Then, the alarm algorithm was repeatedly tested against simulated scenario for 4 blocks. The mice acted comparable to the training period during the tests, and provided total of 58 warnings for the target odor out of 59 random deliveries and 0 false alarm. The results suggest this odor detection method is promising for further development in respect to various types of odor detection applications.
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