Schultz S R, Panzeri S
Howard Hughes Medical Institute and Center for Neural Science, New York University, 4 Washington Place, New York, New York 10003, USA.
Phys Rev Lett. 2001 Jun 18;86(25):5823-6. doi: 10.1103/PhysRevLett.86.5823.
Sampling considerations limit the experimental conditions under which information theoretic analyses of neurophysiological data yield reliable results. We develop a procedure for computing the full temporal entropy and information of ensembles of neural spike trains, which performs reliably for limited samples of data. This approach also yields insight to the role of correlations between spikes in temporal coding mechanisms. The method, when applied to recordings from complex cells of the monkey primary visual cortex, results in lower rms error information estimates in comparison to a "brute force" approach.
采样方面的考虑因素限制了实验条件，在这些条件下对神经生理学数据进行信息论分析才能得出可靠的结果。我们开发了一种计算神经脉冲序列集合的完整时间熵和信息的程序，该程序在有限的数据样本上能可靠运行。这种方法还能深入了解脉冲之间的相关性在时间编码机制中的作用。当将该方法应用于猴子初级视觉皮层复杂细胞的记录时，与“强力”方法相比，其均方根误差信息估计更低。
