Abstract
For further development of advanced driver assistant systems, the elucidation of functional whole-brain networks regarding driving performance is awaited. To reveal the characteristics of these networks, in this study, we estimate the functional connectivity through electroencephalogram (EEG) signals under the condition of watching a driving scene by a phase lag index (PLI) with high spatio-temporal resolution, and compared the functional connectivity between beginner and expert groups for driving. The results show significant enhanced gamma-band functional connectivity in expert groups. Therefore, the PLI approach has a capacity for the estimation of driving performance in advanced driver assistant systems.
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