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Sample Size Dependence of Estimation Error of Information Carried by Neuronal Spike Train

机译：神经元尖峰序列携带的信息估计误差的样本大小依赖性

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摘要

The operating performance of a neural system should be represented by the amount of information carried by neurons. The neuron behaves as a pulse encoder, which converts a stimulus waveform into a discrete pulse (spike) train. In practice, the rate of information transmission is estimated on the basis of a finite number of spikes obtained in a finite observation period. Consequently, the result includes an error. This paper considers the case in which the rate of information transmission is derived from the stimulus-response coherence, and analyzes the relation between the estimation error and the sample size (total number of spikes). It is found that the estimation error of information carried by a single spike is inversely proportional to the total number of spikes used for the estimation. It is pointed out that the asymptotic value of inverse proportion should be used for the comparison of information obtained from different neurons. The validity of the relation between the number of samples and the information per spike is verified by using data obtained from the cricket cereal sensory cells.
机译：神经系统的运行性能应由神经元携带的信息量来表示。神经元的作用就像一个脉冲编码器，它将刺激波形转换成离散的脉冲（尖峰）序列。实际上，信息传输速率是基于在有限的观察周期内获得的有限数量的尖峰来估计的。因此，结果包括错误。本文考虑了一种情况，其中信息传输的速率是从刺激-响应相干性得出的，并分析了估计误差与样本大小（尖峰总数）之间的关系。发现单个尖峰所承载的信息的估计误差与用于估计的尖峰的总数成反比。指出应使用反比例的渐近值来比较从不同神经元获得的信息。通过使用从cereal谷物感官细胞获得的数据，可以验证样本数量与每个峰值的信息之间关系的有效性。

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