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检测刺激后时间直方图累积和导数变化的统计界限。

Statistical limits for detecting change in the cumulative sum derivative of the peristimulus time histogram.

作者信息

Davey N J, Ellaway P H, Stein R B

出版信息

J Neurosci Methods. 1986 Aug;17(2-3):153-66. doi: 10.1016/0165-0270(86)90068-3.

Abstract

The peristimulus time histogram (psth) provides a means of correlating the discharges of neurones with other events. The cumulative sum (cusum) derived from the psth facilitates the detection of small changes in the psth that may be obscured by random fluctuations in counts. The cusum integrates differences from the mean control level of counts in the psth. Any signal in the data that is related to the stimulus appears as a slope in the cusum. Psth's constructed from the rhythmic discharges of single neurones are shown to contain periodical fluctuations in counts that arise from refractoriness. This periodicity results in a cusum which deviates less from the horizontal line than predicted from a Poisson distribution of points. The more regular the spike train, i.e., the lower the coefficient of variation of the distribution of interspike intervals, the flatter is the cusum. The theory of stochastic point processes is used to derive an algorithm for calculating the best approximation of variance of the cusum. Significance limits set at 3 standard deviations of the cusum are shown to provide a good fit to cusums for unit discharges over a wide range of coefficients of variation (0.09-0.60).

摘要

刺激时间直方图(psth)提供了一种将神经元放电与其他事件相关联的方法。从psth导出的累积和(cusum)有助于检测psth中可能被计数的随机波动所掩盖的微小变化。cusum整合了psth中与平均对照计数水平的差异。数据中与刺激相关的任何信号在cusum中都表现为斜率。由单个神经元的节律性放电构建的psth显示在计数中包含由不应期引起的周期性波动。这种周期性导致cusum比根据点的泊松分布预测的更偏离水平线。尖峰序列越规则,即峰间间隔分布的变异系数越低,cusum就越平坦。随机点过程理论用于推导一种算法,以计算cusum方差的最佳近似值。设定为cusum的3个标准差的显著性界限显示,在广泛的变异系数范围(0.09 - 0.60)内,对于单位放电的cusum具有良好的拟合度。

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