Schneider G, Nikolić D
Department of Computer Science and Mathematics, Johann Wolfgang Goethe University, Robert-Mayer-Str. 10, 60325 Frankfurt (Main), Germany.
J Neurosci Methods. 2006 Apr 15;152(1-2):97-106. doi: 10.1016/j.jneumeth.2005.08.014. Epub 2005 Sep 26.
Cross-correlation histograms (CCHs) have been widely used to study the temporal relationship between pairwise recordings of neuronal signals. One interesting parameter of a CCH is the time position of the central peak which indicates delays between signals. In order to study the potential relevance of these delays which can be as small as 1 ms, it is necessary to measure them with high precision. We present a method for the estimation of the central peak's position that is based on fitting a cosine function to the CCH and show that the precision of this estimate can be tracked analytically. We validate the resulting formula by simulations and by the analysis of a sample dataset obtained from cat visual cortex. The results indicate that the time position of the center peak can be estimated with submillisecond precision. The formula allows one also to develop a test of statistical significance for differences between two sets of measurements.
互相关直方图(CCH)已被广泛用于研究神经元信号成对记录之间的时间关系。CCH的一个有趣参数是中心峰值的时间位置,它表示信号之间的延迟。为了研究这些可能小至1毫秒的延迟的潜在相关性,有必要高精度地测量它们。我们提出了一种基于对CCH拟合余弦函数来估计中心峰值位置的方法,并表明可以通过解析方法跟踪该估计的精度。我们通过模拟和对从猫视觉皮层获得的样本数据集的分析来验证所得公式。结果表明,中心峰值的时间位置可以以亚毫秒精度进行估计。该公式还允许人们针对两组测量值之间的差异开展统计显著性检验。