Fabio Theoto Rocha, Eduardo Massad, Carlos Eduardo Thomaz and Armando Freitas da Rocha
Objective: To use multivariate statistical analysis to process the electroencephalographic (EEG) signal recorded
during the solving of language and mathematics tasks by two groups of children, with (LD) and without (NO) learning
disabilities, and thus, to understand the possible difference in the neural circuit organization between these two
groups.
Methods: We processed the EEG data using an algorithm that summarize all the information about the possible
sources of the EEG signal, recorded by each of our 20 electrodes, into a unique variable. Factor Analysis (FA) was
used to study the covariance of this variable and Linear Discriminant Analysis (LDA) to separate samples of distinct
groups.
Results: FA disclosed 3 factors to group NO and 2 for group LD. The electrodes, grouped on each factor of each
group are quietly different. LDA disclosed a frontal/posterior differentiation between NO and LD groups, grouping
mainly the frontal and central electrodes on NO group and the occipital and posterior temporal electrodes on the LD
group.
Conclusion: Results clearly differentiate both groups of children, showing a stronger participation of (pre)frontal
and central regions of the brain on normal children, whereas learning disabled children showed the use of frontal,
temporal and occipital areas.