Subject, session and task effects on power, connectivity and network centrality: A source-based EEG study

Inter-subjects’ variability in functional brain networks has been extensively investigated in the last fewyears. In this context, unveiling subject-specific characteristics of EEG features may play an importantrole for both clinical (e.g., biomarkers) and bio-engineering purposes (e.g., biometric systems and braincomputer interfaces). Nevertheless, the effects induced by multi-sessions and task-switching are notcompletely understood and considered. In this work, we aimed to investigate how the variability due tosubject, session and task affects EEG power, connectivity and network features estimated using source-reconstructed EEG time-series. Our results point out a remarkable ability to identify stable subject featureswithin a given task together with striking independence from the session. The results also show a relevanteffect of task-switching, which is comparable to individual variability. This study suggests that powerand connectivity EEG features may be adequate to detect stable (over-time) individual properties withinpredefined and controlled tasks and that these findings are consistent over a range of connectivity metrics,different epoch lengths and parcellation schemes.© 2020