Quantifying circular-linear associations: Hippocampal phase precession
Quantifying circular-linear associations: Hippocampal phase precession
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DOI：
10.1016/j.jneumeth.2012.03.007
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发表时间：
2012-05-30
影响因子：
3
通讯作者：
Schmidt, Robert
中科院分区：
文献类型：
--
作者：
Kempter, Richard;Leibold, Christian;Schmidt, Robert
当大鼠穿过海马锥体细胞的位置场时，该细胞通常会发出一系列尖峰信号。相对于局部场电位的θ振荡测量的尖峰相位平均作为行进的空间距离的函数减小。相位和尖峰位置之间的这种关系可能是编码的神经基础，称为相位进动。然而，循环相位变量和线性空间变量之间的关联程度通常通过线性-线性相关系数来量化，其中通过将相位限制到任意选择的范围来将循环变量转换为线性变量，这可能使估计的相关性有偏差。在这里，我们引入了一个新的措施来量化循环线性关联。该措施导致回归线的斜率和相位偏移的稳健估计，并且它提供了循环线性数据的相关系数，该相关系数是线性-线性数据的Pearson积矩相关系数的自然模拟。使用替代数据，我们表明，新的方法优于标准的线性线性方法的回归线和相关性的估计，新的方法是依赖于噪声和样本大小。我们证实了这些发现在一个大的数据集的实验记录海马位置细胞和θ振荡，我们讨论了剩余的问题，是相关的相位进动的分析和解释。总之，我们提供了一种新的方法来量化的循环线性协会。(C)2012爱思唯尔有限公司版权所有。
When a rat crosses the place field of a hippocampal pyramidal cell, this cell typically fires a series of spikes. Spike phases, measured with respect to theta oscillations of the local field potential, on average decrease as a function of the spatial distance traveled. This relation between phase and position of spikes might be a neural basis for encoding and is called phase precessior.. The degree of association between the circular phase variable and the linear spatial variable is commonly quantified through, however, a linear-linear correlation coefficient where the circular variable is converted to a linear variable by restricting the phase to an arbitrarily chosen range, which may bias the estimated correlation. Here we introduce a new measure to quantify circular-linear associations. This measure leads to a robust estimate of the slope and phase offset of the regression line, and it provides a correlation coefficient for circular-linear data that is a natural analog of Pearson's product-moment correlation coefficient for linear-linear data. Using surrogate data, we show that the new method outperforms the standard linear-linear approach with respect to estimates of the regression line and the correlation, and that the new method is less dependent on noise and sample size. We confirm these findings in a large data set of experimental recordings from hippocampal place cells and theta oscillations, and we discuss remaining problems that are relevant for the analysis and interpretation of phase precession. In summary, we provide a new method for the quantification of circular-linear associations. (C) 2012 Elsevier B.V. All rights reserved.