Synchronization levels in EEG connectivity during cognitive workloads while driving

Understanding the impact of cognitive workload on neuronal synchronization and brain network structure is crucial for deciphering brain function across various cognitive tasks. This study explores how different levels of cognitive workload influence brain activity during driving, focusing on urban and motorway settings with and without traffic. By analyzing the phase locking value of EEG data from 20 drivers, we identify distinct changes in brain functional connectivity patterns, in high versus low cognitive workloads, particularly in the delta and theta bands. Scenarios with higher cognitive workload reveal a less efficient network structure and decreased small-worldness, especially within the delta and theta bands during urban driving. Frontal and occipital-parietal nodes show a greater tendency to cluster in low cognitive workload conditions compared to high workload, particularly in low-frequency EEG bands. These results provide significant insights into the neural mechanisms of cognitive load, with implications for enhancing cognitive task design and developing future real-time applications in fields like driving assistance and workload management.