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An odor detection system based on automatically trained mice by relative go no-go olfactory operant conditioning

机译:基于通过相对去嗅觉操作条件自动训练的小鼠的气味检测系统

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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.
机译:人类社会在各种情况下都需要气味检测应用程序。啮齿动物在开发生物气味检测系统方面具有独特的优势。该报告概述了一种新颖的设备,该设备设计为使用一种新的嗅觉,相对去执行,可操作的操作条件范式自动训练最多5只小鼠以检测气味。新的范式提供了通过变化的响应来测量单个动物的检测行为的实时可靠性的机会。 15只缺水小鼠全部能够学会通过触摸传感器以更高的触摸频率对目标气味的不可预测的传递做出响应。以降低的目标气味(正丁醇)浓度连续训练小鼠,以0.01%的溶液浓度训练时,平均正确百分比显着下降;通过训练,该警报算法显示出对合格小鼠组的气味检测行为的出色识别。然后,针对模拟场景针对4个块反复测试了警报算法。在测试期间,小鼠的行为与训练期间相当,并且在59次随机分娩和0次虚警中总共提供了58条针对目标气味的警告。结果表明,这种气味检测方法有望在各种类型的气味检测应用中得到进一步发展。

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