Assessment of functional connectivity induced by driving experience

Abstract

Recently, an importance of estimating driver's experiences has been recognized in advanced driver assistant systems. Furthermore, neuro-imaging studies showed that the characteristics of functional whole-brain networks, typified as functional connectivity, strongly reflect driving performance. In this study, we estimated functional connectivity through electroencephalogram (EEG) signals while watching a driving scene by phase lag index (PLI) with high spatio-temporal resolution and compared the functional connectivity between beginner and expert groups for driving. The results showed significantly enhanced gamma-band functional connectivity in the expert groups. Therefore, the PLI approach could be utilized for estimating driving performance in the advanced driver assistant systems.