Although abbreviated as “the Real-World Driving experiment”, the main aims of this project focus on how individuals navigate the social world, and how brain signals acquired in real-world environments can predict longitudinal variability in performance. This unique dataset includes measurements from the brain and body collected in the real world as driver and passenger participants drove on I-95 and engaged in social interaction, as well as longitudinal tracking of sleep and physical activity (measured with accelerometers), daily social interactions (measured with experience sampling), and social network properties (measured from digital records of social interactions). The overall aim of this research is to examine variability in human brain and behavioral state changes during functional tasks performed in a naturalistic setting, and identify how neural and linguistic synchrony during social interactions influence successful communication, and thereby improve performance, in this context.
RWN Neural predictors of driving outcomes (RWN-NPDO)
DCS Corporation and Army Research Office
18 Sep 2013 to 04 Apr 2019