首页> 外文期刊>Biological Cybernetics: Communication and Control in Organisms and Automata: = Nachrichtenubertragung, Nachrichtenverarbeitung, Steuerung und Regelung in Organismen und in Automaten >Short-window spectral analysis of cortical event-related potentials by adaptive multivariate autoregressive modeling: data preprocessing, model validation, and variability assessment
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Short-window spectral analysis of cortical event-related potentials by adaptive multivariate autoregressive modeling: data preprocessing, model validation, and variability assessment

机译:通过自适应多元自回归建模对皮质事件相关电位进行短窗光谱分析:数据预处理,模型验证和变异性评估

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摘要

In this article we consider the application of parametric spectral analysis to multichannel event-related potentials (ERPs) during cognitive experiments. We show that with proper data preprocessing, Adaptive MultiVariate AutoRegressive (AMVAR) modeling is an effective technique for dealing with nonstationary ERP time series. We propose a bootstrap procedure to assess the variability in the estimated spectral quantities. Finally, we apply AMVAR spectral analysis to a visuomotor integration task, revealing rapidly changing cortical dynamics during different stages of task processing. [References: 19]
机译:在本文中,我们考虑在认知实验期间将参数频谱分析应用于多通道事件相关电位(ERP)。我们表明,通过适当的数据预处理,自适应多变量自回归(AMVAR)建模是一种有效的技术,用于处理非平稳ERP时间序列。我们提出了一个自举程序来评估估计频谱量中的可变性。最后,我们将AMVAR频谱分析应用于视觉运动整合任务,揭示在任务处理的不同阶段快速变化的皮质动力学。 [参考:19]

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