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Inter-channel Correlation in the EEG Activity During a Cognitive Problem Solving Task with an Increasing Difficulty Questions Progression

机译:难度越来越大的认知问题解决任务期间脑电活动中的通道间相关性。

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Correlation analysis allows detecting the degree of relatedness between two variables. Even when correlation does not mean necessarily causation, in a time series, it indicates the degree of synchrony of two comparing variables and in many aspects renders similar information compared with cross-coherence analysis of the electroencephalographic signal. In this work we explore rather simple statistical features to mine into deeper underlying aspects of the functional organization of the brain during performing an intelligence test. We studied time length duration taken to solve a series of questions ordered with increasing difficulty and the correlation values reached by tine series data synchronization between the 14 EEG channels placed in the subject's scalp, during the mental task. The intelligence test consisted in an abbreviated (15 questions) version of the Raven Matrices test. Results coming from the correlation analysis showed relevant information about functional organization strategies of the brain solving a cognitive problem, as well as good discrimination for inter-individual differences in the way inter-channel correlation values distribute differently for each subject around central values of R.
机译:相关分析允许检测两个变量之间的相关程度。即使相关性不一定表示因果关系,在时间序列上,它也表示两个比较变量的同步程度,并且在许多方面,与脑电图信号的交叉相干分析相比,它提供了相似的信息。在这项工作中,我们探索了相当简单的统计功能,以在进行智力测试时挖掘出大脑功能组织的更深层次的潜在方面。我们研究了为解决一系列难度越来越大的问题而花费的时间长度,以及在心理任务期间通过放置在对象头皮上的14个EEG通道之间的齿序列数据同步所达到的相关值。智力测试包括Raven矩阵测试的缩写版本(15个问题)。来自相关分析的结果表明,有关大脑解决认知问题的功能组织策略的相关信息,以及对通道间相关值在R的中心值附近针对每个对象的不同分布方式的个体间差异的良好区分。

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