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在事件相关电位(ERP)测量中最大化信噪比和统计功效:单站点与多站点平均簇

Maximizing signal-to-noise ratio and statistical power in ERP measurement: Single sites versus multi-site average clusters.

作者信息

Zhang Wendy, Kappenman Emily S

机构信息

Department of Psychology, San Diego State University, San Diego, California, USA.

San Diego Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California, San Diego, California, USA.

出版信息

Psychophysiology. 2024 Feb;61(2):e14440. doi: 10.1111/psyp.14440. Epub 2023 Nov 16.

DOI:10.1111/psyp.14440
PMID:37973199
Abstract

One important decision in every event-related potential (ERP) experiment is which electrode site(s) to use in quantifying the ERP component of interest. A common approach is to measure the ERP from a single electrode site, typically the site where the ERP component is largest. Alternatively, two or more electrode sites in a given spatial region are averaged together, and the ERP is measured from the resulting multi-site cluster. The goal of the present study was to systematically compare these two measurement approaches across a range of outcome measures and ERP components to determine whether measuring from a single electrode site or an average of multiple sites yields consistently better results. We examined seven common ERP components from the open-source ERP CORE dataset that span a range of neurocognitive processes: N170, mismatch negativity (MMN), N2pc, N400, P3, lateralized readiness potential (LRP), and error-related negativity (ERN). For each component, we compared ERP amplitude, noise level, signal-to-noise ratio, and effect size at two single electrode sites and four multi-site clusters. We also used a Monte Carlo approach to simulate within-participant and between-groups experiments with known effect magnitudes to compare statistical power at single sites and multi-site clusters. Overall, measuring from a multi-site cluster produced results that were as good as or better than measuring from a single electrode site across analyses and components, indicating that the cluster-based measurement approach may be beneficial in quantifying ERPs from a range of neurocognitive domains.

摘要

在每一项与事件相关电位(ERP)的实验中,一个重要的决策是在量化感兴趣的ERP成分时使用哪些电极位点。一种常见的方法是从单个电极位点测量ERP,通常是ERP成分最大的位点。另一种方法是将给定空间区域内的两个或更多电极位点进行平均,并从所得的多位点簇测量ERP。本研究的目的是在一系列结果测量和ERP成分中系统地比较这两种测量方法,以确定从单个电极位点测量还是从多个位点的平均值测量是否能始终产生更好的结果。我们从开源的ERP CORE数据集中检查了七个常见的ERP成分,这些成分涵盖了一系列神经认知过程:N170、失配负波(MMN)、N2pc、N400、P3、偏侧化准备电位(LRP)和错误相关负波(ERN)。对于每个成分,我们比较了两个单电极位点和四个多位点簇处的ERP振幅、噪声水平、信噪比和效应大小。我们还使用蒙特卡罗方法模拟具有已知效应大小的参与者内和组间实验,以比较单位点和多位点簇处的统计功效。总体而言,在各项分析和成分中,从多位点簇测量产生的结果与从单个电极位点测量的结果一样好或更好,这表明基于簇的测量方法在量化来自一系列神经认知领域的ERP时可能是有益的。

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