Decomposing delta, theta, and alpha time-frequency ERP activity from a visual oddball task using PCA
Decomposing delta, theta, and alpha time-frequency ERP activity from a visual oddball task using PCA
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DOI：
10.1016/j.ijpsycho.2006.07.015
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发表时间：
2007-04-01
影响因子：
3
通讯作者：
Iacono, William G.
中科院分区：
文献类型：
--
作者：
Bernat, Edward M.;Malone, Stephen M.;Iacono, William G.
目的：时频分析已成为从事件相关范式评估脑电和脑磁活动的重要工具。在电位数据中，θ和δ活动已被证明是P300活动的基础，α活动已被证明在P300活动期间受到抑制。δ、θ和α活性的测量通常取自TF表面。然而，用于提取相关活动的方法通常不超出在表面上采取窗口的手段，类似于在仅时间信号表示中的定义的P300窗口内测量活动。目前的目标是使用数据驱动的方法，从oddball paradigm.Methods中的大量参与者的事件相关电位数据中获得相关TF分量：采用最近开发的PCA方法提取TF分量[Bernat，E. M.，威廉姆斯，W。J.，和Gehring，W. J.（2005年）。利用PCA对ERP进行时频能量分解。Clin Neurophysiol，116（6），1314-1334]，来自2068名17岁奥尔兹少年（979名男性）的ERP数据集。TF活性取自个体试验和条件平均值。活动包括频率范围从0到14 Hz和时间范围从刺激开始到1312.5 ms.Results：一个协调的时间-频率事件是明显的整个分解。类似的TF组件表示较早的θ，然后是三角洲提取从两个单独的试验和平均数据。预测的α活动仅在从试验水平数据生成时频表面时才明显，并且在P300期间以减少为特征。结论：Theta、Delta和α活动是以可预测的时间过程提取的。值得注意的是，这种方法在表征来自单电极的数据时是有效的。最后，TF数据分解产生的个人试验和条件平均值产生了类似的结果，但可预测的差异。具体而言，试验水平的数据证明了越来越多的不同θ测量，并占总方差较小。(c)2006 Elsevier B. V.保留所有权利。
Objective: Time-frequency (TF) analysis has become an important tool for assessing electrical and magnetic brain activity from event-related paradigms. In electrical potential data, theta and delta activities have been shown to underlie P300 activity, and alpha has been shown to be inhibited during P300 activity. Measures of delta, theta, and alpha activity are commonly taken from TF surfaces. However, methods for extracting relevant activity do not commonly go beyond taking means of windows on the surface, analogous to measuring activity within a defined P300 window in time-only signal representations. The current objective was to use a data driven method to derive relevant TF components from eventrelated potential data from a large number of participants in an oddball paradigm.Methods: A recently developed PCA approach was employed to extract TF components [Bernat, E. M., Williams, W. J., and Gehring, W. J. (2005). Decomposing ERP time-frequency energy using PCA. Clin Neurophysiol, 116(6), 1314-1334] from an ERP dataset of 2068 17 year olds (979 males). TF activity was taken from both individual trials and condition averages. Activity including frequencies ranging from 0 to 14 Hz and time ranging from stimulus onset to 1312.5 ms were decomposed.Results: A coordinated set of time-frequency events was apparent across the decompositions. Similar TF components representing earlier theta followed by delta were extracted from both individual trials and averaged data. Alpha activity, as predicted, was apparent only when time-frequency surfaces were generated from trial level data, and was characterized by a reduction during the P300.Conclusions: Theta, delta, and alpha activities were extracted with predictable time-courses. Notably, this approach was effective at characterizing data from a single-electrode. Finally, decomposition of TF data generated from individual trials and condition averages produced similar results, but with predictable differences. Specifically, trial level data evidenced more and more varied theta measures, and accounted for less overall variance. (c) 2006 Elsevier B.V. All rights reserved.