Design of a Decision-making Tool to Identify Cross-correlation Brain Dominances

Abstract

The objective of this study is to design a decision-making tool to carry out a sequence of intermediate processing analytic steps in order to render a graphic visualization of significant correlations between pairs of EEG channels. We submitted a set of students to an abbreviated version of a visual intelligent test while we recorded EEG activity covering frontal, temporal, parietal and occipital areas of the brain cortex through the scalp. The graphs generated show correlations between specific ranges of R Spearman values and pairs of electrodes relevant for the particular study needed. We used this tool to make a descriptive classification of subjects according to the inter-channels correlation maps generated by our decision-making tool. We called correlation “dominances” to the areas defined for a high concentration of significant correlations. This term has been used previously as a way to classify styles of people's thinking-acting in relation to four descriptive referential brain areas. We contrasted our correlation dominances results with this psychological-questionnaire tool in search of consistencies. To design the brain connectivity module, we used Rapid Application Development (RAD) methodology. The tool has been developed in Matlab to analyze signal data ranges delta, theta, alpha, beta, and gamma; all these obtained from the EEG cleaned off artifacts, pre-processed and separated into bands using EEGLAB. Pearson correlation is utilized to detect synchronic connectivity dominances (correlations) through the brain areas. The results are presented in terms of cross-correlation maps, or correlation matrices, between the 14 channels of EEG signal for different EEG frequency bands.