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Evaluation of the Validity of a Maximum Likelihood Adaptive Staircase Procedure for Measurement of Olfactory Detection Threshold in Mice

机译:最大似然自适应楼梯程序测量小鼠嗅觉检测阈值的有效性的评估

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摘要

Threshold is defined as the stimulus intensity necessary for a subject to reach a specified percent correct on a detection test.MLPEST (maximum likelihood parameter estimation by sequential testing) is a method that is able to determine threshold accurately and more rapidly than many other methods.Originally developed for human auditory and visual tasks,it has been adapted for human olfactory and gustatory tests.In order to utilize this technique for olfactory testing in mice,we have adapted MLPEST methodology for use with computerized olfactometry as a tool to estimate odor detection thresholds.Here we present Monte Carlo simulations and operant conditioning data that demonstrate the potential utility of this technique in mice,we explore the ramifications of altering MLPEST test parameters on performance,and we discuss the advantages and disadvantages of using MLPEST compared to other methods for the estimation of thresholds in rodents.Using MLPEST,we find that olfactory detection thresholds in mice deficient for the cyclic nucleotide-gated channel subunitA2 are similar to those of wild-type animals for odorants the knockout animals are able to detect.
机译:阈值被定义为受试者在检测测试中达到指定正确百分比所必需的刺激强度。MLPEST(通过顺序测试的最大似然参数估计)是一种能够比许多其他方法准确,更快地确定阈值的方法。最初是为人类的听觉和视觉任务而开发的,现在已经适应了人类的嗅觉和味觉测试。为了将这种技术用于小鼠的嗅觉测试,我们对MLPEST方法进行了改进,并与计算机嗅觉测量法配合使用,以此作为估计气味检测阈值的工具在这里,我们提供了蒙特卡罗模拟和操作条件数据,这些数据证明了该技术在小鼠中的潜在效用,我们探讨了改变MLPEST测试参数对性能的影响,并讨论了与其他方法相比,使用MLPEST的优缺点。啮齿动物的阈值估计。使用MLPEST,我们发现嗅觉检测缺乏环状核苷酸门控通道亚基A2的小鼠的门槛与野生型动物的门槛相似,因为敲除动物能够检测到它们的气味。

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