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EEG Based Coherence Analysis for Identifying Inter Individual Differences in Language and Logic Study

机译:基于EEG的一致性分析,用于识别语言和逻辑研究中的个体差异

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According to Multiple Intelligences (MI) theory by Howard Gardner, human's intelligence can be divided into linguistic, logical/mathematical, musical, spatial, bodily/kinesthetic, interpersonal, intrapersonal and naturalistic areas. In this paper, two groups of students with high and low MI scores in each area for linguistic and logical/mathematical intelligences were categorized and tested based on a questionnaire in an experiment. Electroencephalogram (EEG) was recorded from 16 electrodes using Emotiv EPOC for 29 kindergarten children and 9 high school students during the assessment. To investigate the neuro-physiological substrates of intelligence, EEG signal based coherence analysis in alpha, beta, gamma and theta frequency bands was performed. Our findings indicate that the group with low MI score for both language and logic showed wider and distributed cognitive activations suggesting an increased effort in processing a particular task. The group with high MI score for language showed effective connectivity within left-hemisphere and low activation in the right parietal lobe. The group with high MI score for logic/mathematics showed increased frontal activation. Performance in language and logic test was further correlated with effective connectivity in the task specific areas of brain. Based on our results we conclude that a smarter brain for language and logic is associated with the limited but affective connectivity.
机译:根据霍华德·加德纳(Howard Gardner)的多元智能(MI)理论,人类的智能可分为语言,逻辑/数学,音乐,空间,身体/运动,人际关系,人际内部和自然主义领域。在本文中,根据问卷调查,对两组在语言和逻辑/数学智力方面每个领域的MI分数均高和低的学生进行了分类和测试。在评估过程中,使用Emotiv EPOC从16根电极上记录了29名幼儿园儿童和9名高中学生的脑电图(EEG)。为了研究智力的神经生理学底物,在α,β,γ和θ频带中进行了基于EEG信号的相干分析。我们的发现表明,在语言和逻辑方面的MI分数均较低的组显示出更广泛和分散的认知活动,表明在处理特定任务方面的工作量有所增加。语言语言MI分数高的组显示左半球内有效的连接性,而右顶叶的激活性低。逻辑/数学MI分数高的组显示额叶活动性增强。语言和逻辑测试的表现还与大脑特定任务区域的有效连通性相关。根据我们的结果,我们得出结论,语言和逻辑的智慧大脑与有限但有效的连接性相关。

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