Lewi Jeremy, Schneider David M, Woolley Sarah M N, Paninski Liam
Georgia Institute of Technology, Atlanta, GA 30332, USA.
J Comput Neurosci. 2011 Feb;30(1):181-200. doi: 10.1007/s10827-010-0248-1. Epub 2010 Jun 16.
Adaptive stimulus design methods can potentially improve the efficiency of sensory neurophysiology experiments significantly; however, designing optimal stimulus sequences in real time remains a serious technical challenge. Here we describe two approximate methods for generating informative stimulus sequences: the first approach provides a fast method for scoring the informativeness of a batch of specific potential stimulus sequences, while the second method attempts to compute an optimal stimulus distribution from which the experimenter may easily sample. We apply these methods to single-neuron spike train data recorded from the auditory midbrain of zebra finches, and demonstrate that the resulting stimulus sequences do in fact provide more information about neuronal tuning in a shorter amount of time than do more standard experimental designs.
自适应刺激设计方法有可能显著提高感觉神经生理学实验的效率；然而，实时设计最优刺激序列仍然是一项严峻的技术挑战。在此，我们描述了两种生成信息丰富的刺激序列的近似方法：第一种方法提供了一种快速方法，用于对一批特定潜在刺激序列的信息量进行评分，而第二种方法试图计算出一种最优刺激分布，实验者可以从中轻松采样。我们将这些方法应用于从斑胸草雀听觉中脑记录的单神经元放电序列数据，并证明与更标准的实验设计相比，由此产生的刺激序列实际上确实能在更短的时间内提供更多关于神经元调谐的信息。
