Investigating multilevel cognitive processing within error-free and error-prone feedback conditions in executed and...

Area of Science:

• Neuroscience
• Cognitive Science
• Road Safety

Background:

• Run-off-road incidents contribute significantly to road traffic fatalities.
• Understanding drivers' brain responses during critical driving scenarios, like deviations from the road, is crucial for improving safety.
• Existing research lacks insight into the cortical mechanisms underlying continuous steering adjustments in response to road position discrepancies.

Purpose of the Study:

• To disentangle subprocesses involved in driving, such as error processing and motor control, by analyzing brain activity.
• To investigate the neural correlates of steering behavior and cognitive control during both normal and erroneous driving conditions.
• To explore the feasibility of using electroencephalography (EEG) to predict vehicle deviations from the road.

Main Methods:

• Electroencephalography (EEG) signals were recorded from 26 participants over 13 sessions.
• Participants engaged in a driving task under passive (observing) and active (steering) conditions, with both error-free and error-prone scenarios.
• Simultaneous recording of 'Executors' (actively steering) and 'Observers' (passively observing) allowed for comparative analysis.

Main Results:

• Executors exhibited common brain patterns across driving conditions, with a shift from motor beta to occipital alpha oscillations during erroneous conditions.
• Significant frontocentral EEG differences between Observers and Executors, linked to the caudal anterior cingulate cortex, indicated heightened motor-behavioral cognitive control during active steering.
• Regression analyses showed potential for EEG signals to predict steering adjustments and vehicle position relative to the road.

Conclusions:

• The study identified distinct neural patterns associated with steering, cognitive control, and error processing during driving.
• EEG can differentiate between active steering and passive observation, reflecting cognitive control mechanisms.
• The findings suggest that EEG-based analysis holds promise for predicting and potentially mitigating road departure incidents.