Mind over motor mapping: Driver response to changing vehicle dynamics

Improvements in vehicle safety require understanding of the neural systems that support the complex, dynamic task of real‐world driving. We used functional near infrared spectroscopy (fNIRS) and pupilometry to quantify cortical and physiological responses during a realistic, simulated driving task i...

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Bibliographic Details
Published in:Human brain mapping 2018-10, Vol.39 (10), p.3915-3927
Main Authors: Bruno, Jennifer L., Baker, Joseph M., Gundran, Andrew, Harbott, Lene K., Stuart, Zachary, Piccirilli, Aaron M., Hosseini, S. M. Hadi, Gerdes, J. Christian, Reiss, Allan L.
Format: Article
Language:English
Subjects:
Activation
Adolescent
Adult
Automobile Driving
Brain
Cerebral Cortex - diagnostic imaging
Cerebral Cortex - physiology
Cortex
Driver behavior
drviving
Female
functional near infrared spectroscopy
Functional Neuroimaging - methods
Humans
In vehicle
Infrared spectroscopy
Learning - physiology
Male
Man-Machine Systems
Motor skill learning
Motors
Near infrared radiation
personality
Personality - physiology
Physiological responses
Physiology
Psychomotor Performance - physiology
Pupil - physiology
pupilometry
Safety systems
Spectroscopy, Near-Infrared - methods
steering control
Traffic accidents & safety
Vehicle safety
Young Adult
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Summary:Improvements in vehicle safety require understanding of the neural systems that support the complex, dynamic task of real‐world driving. We used functional near infrared spectroscopy (fNIRS) and pupilometry to quantify cortical and physiological responses during a realistic, simulated driving task in which vehicle dynamics were manipulated. Our results elucidate compensatory changes in driver behavior in response to changes in vehicle handling. We also describe associated neural and physiological responses under different levels of mental workload. The increased cortical activation we observed during the late phase of the experiment may indicate motor learning in prefrontal–parietal networks. Finally, relationships among cortical activation, steering control, and individual personality traits suggest that individual brain states and traits may be useful in predicting a driver's response to changes in vehicle dynamics. Results such as these will be useful for informing the design of automated safety systems that facilitate safe and supportive driver–car communication.
ISSN:1065-9471
1097-0193
1097-0193
DOI:10.1002/hbm.24220