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“认知”任务期间的脑电图模式。I. 复杂行为的方法学与分析

EEG patterns during 'cognitive' tasks. I. Methodology and analysis of complex behaviors.

作者信息

Gevins A S, Zeitlin G M, Yingling C D, Doyle J C, Dedon M F, Schaffer R E, Roumasset J T, Yeager C L

出版信息

Electroencephalogr Clin Neurophysiol. 1979 Dec;47(6):693-703. doi: 10.1016/0013-4694(79)90296-7.

Abstract

This paper presents a methodology which uses nonlinear pattern recognition to study the spatial distribution of EEG patterns accompanying higher cortical functions. The multivariate decision rules reveal the essential EEG patterns which differentiate performance of two tasks. Cross-validation classification accuracy measures the generality of the findings. Using this method, EEG patterns were derived from a group of 23 adults during performance of several complex tasks, including Koh's block design, writing sentences, mental paper folding, and reading silently. These patterns discriminate between the tasks, are consistent with, and extend the results of, visual EEG interpretations and univariate analysis of spectral intensities. Since writing sentences could not be distinguished from mere scribbling, it is unclear whether the EEG patterns found to distinguish complex behaviors were related to the cognitive components of tasks, or to sensory-motor and performance-related factors.

摘要

本文提出了一种利用非线性模式识别来研究伴随高级皮层功能的脑电图(EEG)模式空间分布的方法。多变量决策规则揭示了区分两项任务表现的基本EEG模式。交叉验证分类准确率衡量了研究结果的普遍性。使用这种方法,从23名成年人在执行多项复杂任务(包括科赫积木设计、写句子、心理折纸和默读)过程中获取了EEG模式。这些模式能够区分不同任务,与视觉EEG解释和频谱强度单变量分析的结果一致且有所扩展。由于写句子无法与随意涂鸦区分开来,所以尚不清楚所发现的区分复杂行为的EEG模式是与任务的认知成分有关,还是与感觉运动及表现相关因素有关。

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