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非平稳泊松点过程描述了外侧上橄榄核听觉神经元在长时间尺度上的动作电位序列。

A nonstationary Poisson point process describes the sequence of action potentials over long time scales in lateral-superior-olive auditory neurons.

作者信息

Turcott R G, Lowen S B, Li E, Johnson D H, Tsuchitani C, Teich M C

机构信息

Department of Electrical Engineering, Columbia University, New York, NY 10027.

出版信息

Biol Cybern. 1994;70(3):209-17. doi: 10.1007/BF00197601.

DOI:10.1007/BF00197601
PMID:8136404
Abstract

The behavior of lateral-superior-olive (LSO) auditory neurons over large time scales was investigated. Of particular interest was the determination as to whether LSO neurons exhibit the same type of fractal behavior as that observed in primary VIII-nerve auditory neurons. It has been suggested that this fractal behavior, apparent on long time scales, may play a role in optimally coding natural sounds. We found that a nonfractal model, the nonstationary dead-time-modified Poisson point process (DTMP), describes the LSO firing patterns well for time scales greater than a few tens of milliseconds, a region where the specific details of refractoriness are unimportant. The rate is given by the sum of two decaying exponential functions. The process is completely specified by the initial values and time constants of the two exponentials and by the dead-time relation. Specific measures of the firing patterns investigated were the interspike-interval (ISI) histogram, the Fano-factor time curve (FFC), and the serial count correlation coefficient (SCC) with the number of action potentials in successive counting times serving as the random variable. For all the data sets we examined, the latter portion of the recording was well approximated by a single exponential rate function since the initial exponential portion rapidly decreases to a negligible value. Analytical expressions available for the statistics of a DTMP with a single exponential rate function can therefore be used for this portion of the data. Good agreement was obtained among the analytical results, the computer simulation, and the experimental data on time scales where the details of refractoriness are insignificant.(ABSTRACT TRUNCATED AT 250 WORDS)

摘要

研究了外侧上橄榄核(LSO)听觉神经元在较大时间尺度上的行为。特别令人感兴趣的是确定LSO神经元是否表现出与在初级听神经听觉神经元中观察到的相同类型的分形行为。有人提出,这种在长时间尺度上明显的分形行为可能在自然声音的最佳编码中起作用。我们发现,一种非分形模型,即非平稳死区修正泊松点过程(DTMP),对于大于几十毫秒的时间尺度,能很好地描述LSO的放电模式,在这个区域,不应期的具体细节并不重要。放电率由两个衰减指数函数的和给出。该过程完全由两个指数的初始值和时间常数以及死区关系确定。所研究的放电模式的具体测量指标包括峰峰间隔(ISI)直方图、法诺因子时间曲线(FFC)以及序列计数相关系数(SCC),其中连续计数时间内的动作电位数量作为随机变量。对于我们检查的所有数据集,记录的后半部分可以很好地用单个指数率函数近似,因为初始指数部分迅速下降到可忽略的值。因此,对于具有单个指数率函数的DTMP统计量可用的解析表达式可用于这部分数据。在不应期细节不重要的时间尺度上,解析结果、计算机模拟和实验数据之间取得了很好的一致性。(摘要截断于250字)

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