Investigation of brain functional integration and segregation in individuals based on the quality of performing mathematical calculations

The study of brain connectivity is one of the recent and growing concepts which has been very important as exploring brain function discrepancy between healthy and patient ones. In this study, a non-invasive Electroencephalography (EEG) method is used to record the electrical activity of the brain. EEG signals are recorded of individuals at resting-state and performing mathematical calculations. According to the quality of performing mathematical calculations, 36 study participants were classified into two groups of bad and good counters. To analyze brain connectivity, two approaches are considered. The first analysis is comparing the performance of good and bad counters, and the next step involved comparing rest and doing task patterns among all cases. In this regard, graph theory has been used. These mentioned graphs are constructed using Pearson correlation analysis and by using different thresholds, the graphs are sparsed. At each threshold, graph features are extracted. In the continuation of the research, after extracting features such as global efficiency, local efficiency, clustering coefficient, transitivity, and modularity, a non-parametric statistical test is used for evaluation. The results show a significant difference in the features of global efficiency and modularity at the 0.65 threshold in both resting and performing mental tasks in all individuals. Moreover, there is no statistically significant difference in thresholds when comparing good and bad counters features at resting-state.