Decoding the dynamic perception of risk and speed using naturalistic stimuli: A multivariate, whole-brain analysis

Area of Science:

• Neuroscience
• Cognitive Psychology
• Human Factors Engineering

Background:

• Understanding driving safety relies on decoding speed and risk perception.
• Real-time brain activity analysis is crucial for comprehending dynamic perceptual processes.

Purpose of the Study:

• To investigate time-resolved neural decoding of subjective speed and risk perception during simulated driving.
• To identify brain regions involved in processing dynamic risk and speed information.

Main Methods:

• Utilized fMRI with a trackball for dynamic ratings of perceived risk and speed during naturalistic driving videos.
• Employed multivariate correlation analysis to decode neural representations of subjective ratings.
• Compared standard analysis with time-resolved decoding approaches.

Main Results:

• Standard analysis showed limited decoding of risk in visual areas.
• Time-resolved decoding revealed frontal, visual, and temporal activation for risk, and dorsal visual stream/temporal activation for speed.
• Brain regions for risk decoding varied over time, while speed decoding regions remained stable.

Conclusions:

• Time-resolved decoding offers superior insights into dynamic neural processes of risk and speed perception.
• Distinct and dynamic neural networks underlie the perception of risk and speed in driving scenarios.