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- W2331228847 abstract "Objective: To use multivariate statistical analysis to process the electroencephalographic (EEG) signal recordedduring the solving of language and mathematics tasks by two groups of children, with (LD) and without (NO) learningdisabilities, and thus, to understand the possible difference in the neural circuit organization between these twogroups.Methods: We processed the EEG data using an algorithm that summarize all the information about the possiblesources of the EEG signal, recorded by each of our 20 electrodes, into a unique variable. Factor Analysis (FA) wasused to study the covariance of this variable and Linear Discriminant Analysis (LDA) to separate samples of distinctgroups.Results: FA disclosed 3 factors to group NO and 2 for group LD. The electrodes, grouped on each factor of eachgroup are quietly different. LDA disclosed a frontal/posterior differentiation between NO and LD groups, groupingmainly the frontal and central electrodes on NO group and the occipital and posterior temporal electrodes on the LDgroup.Conclusion: Results clearly differentiate both groups of children, showing a stronger participation of (pre)frontaland central regions of the brain on normal children, whereas learning disabled children showed the use of frontal,temporal and occipital areas." @default.
- W2331228847 created "2016-06-24" @default.
- W2331228847 creator A5081149122 @default.
- W2331228847 date "2014-01-01" @default.
- W2331228847 modified "2023-09-30" @default.
- W2331228847 title "EEG Brain Mapping of Normal and Learning Disabled Children Using Factor and Linear Discriminant Analyses" @default.
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- W2331228847 doi "https://doi.org/10.4172/2155-9562.1000262" @default.
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