Publication Details
Abstract
This project investigates the synchronization dynamics within simulated functional brain networks of children diagnosed with Attention Deficit Hyperactivity Disorder (ADHD) and compares them to those of healthy controls. Electroencephalogram (EEG) signals recorded while observing various facial expressions (angry, happy, neutral, and sad) served as the basis for constructing these networks. To achieve this, each node in the extracted subnetworks was replaced with a Hindmarsh-Rose neuronal model, known for its ability to describe complex neuronal activity patterns. Simulations were performed in a MATLAB environment, where edge weights between neurons represented the Correlation between Probability of Signal Recurrences (CPR) values derived from EEG signals. The coupling strength between neurons was varied to observe different synchronization patterns. The results indicate that ADHD brain networks exhibit higher synchronization compared to healthy controls, particularly in the frontal and occipital brain lobes during happy emotions. Furthermore, the chimera phenomenon, characterized by the coexistence of synchronous and asynchronous groups, was observed in both ADHD and healthy groups, but it occurred in the ADHD group at a lower coupling strength. These findings suggest a potential deficit in the brain's emotional and visual processing centers in the ADHD group, which might explain their difficulties in recognizing emotional facial expressions.