刺激后时间和间隔直方图与脉冲序列定时特征的关系。
The relationship of post-stimulus time and interval histograms to the timing characteristics of spike trains.
作者信息
Johnson D H
出版信息
Biophys J. 1978 Jun;22(3):413-30. doi: 10.1016/S0006-3495(78)85496-4.
Abstract
PST (post-stimulus time) and interval histograms computed from recorded spike trains are related to an average timing characteristics of the spike train. The exact nature of this relationship varies with recording parameters, interfering signals, the histogram bin width, and the duration of the measurement interval. This work describes the conditions under which a PST histogram can serve as an unbiased estimate of the ensemble average of a spike train's intensity and an interval histogram can serve as an unbiased estimate of the probability density function of the interspike intervals. Simulation studies are used to confirm the validity of the theoretical results. As an example of an application, these results are used to analyze recordings of singleunit activity in the eight cranial nerve.
摘要
根据记录的脉冲序列计算出的刺激后时间（PST）和间隔直方图与脉冲序列的平均时间特征相关。这种关系的确切性质会随记录参数、干扰信号、直方图的bin宽度以及测量间隔的持续时间而变化。这项工作描述了在哪些条件下，PST直方图可以作为脉冲序列强度总体平均值的无偏估计，以及间隔直方图可以作为脉冲间隔概率密度函数的无偏估计。通过模拟研究来证实理论结果的有效性。作为一个应用示例，这些结果被用于分析第八对脑神经中单个神经元活动的记录。
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本文引用的文献
1
Intracochlear potential recorded with micropipets. II. Responses in the cochlear scalae to tones.
J Acoust Soc Am. 1971 Aug;50(2):587-601. doi: 10.1121/1.1912675.
2
Phase-locked response to low-frequency tones in single auditory nerve fibers of the squirrel monkey.松鼠猴单根听神经纤维对低频音调的锁相反应。
J Neurophysiol. 1967 Jul;30(4):769-93. doi: 10.1152/jn.1967.30.4.769.
3
Neuronal spike trains and stochastic point processes. I. The single spike train.神经元脉冲序列与随机点过程。I. 单个脉冲序列。
Biophys J. 1967 Jul;7(4):391-418. doi: 10.1016/S0006-3495(67)86596-2.
4
Sequential interval histogram analysis of non-stationary neuronal spike trains.非平稳神经元脉冲序列的顺序间隔直方图分析
Biol Cybern. 1976 Mar 30;22(2):61-71. doi: 10.1007/BF00320131.
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