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Updated: May 26, 2025

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
Published on: November 8, 2012
Causality of brain region activation during driver takeover in conditional autonomous driving: a study based on fMRI
Xiaonan Li1, Feng Chen1, Yunjie Ju1
1Key Laboratory of Road & Traffic Engineering of the Ministry of Education, Tongji University, Shanghai, P.R. China.
Objective:
Understanding the neural decision-making mechanisms of drivers during takeover in conditional autonomous driving is crucial for improving driver safety and performance. This study investigates how visibility and urgency affect the activation and interactions of key brain regions, including the middle temporal gyrus (MTG), fusiform gyrus (FG), middle occipital gyrus (MOG), precentral gyrus (PCG), and precuneus (PCu), which are involved in distance perception, visual recognition, color processing, motor planning, and memory retrieval.
Methods:
Functional magnetic resonance imaging (fMRI) and Granger causality analysis were used to examine the brain activation patterns and interregional interactions of these areas during four driving scenarios, involving good or poor visibility and emergency or non-emergency conditions in a conditional autonomous driving context.
Results:
Under complex driving conditions (poor visibility or emergency), interactions among regions involved in visual processing and spatial cognition were significantly enhanced, reflecting the need for rapid integration of visual information. Both immediate and delayed effects were identified, with immediate responses prioritizing rapid perception and motor actions, while delayed effects supported sustained visual and spatial processing as conditions stabilized.
Conclusions:
These findings provide insights into the neural mechanisms driving behavior under varying driving conditions, aiding the optimization of driver assistance systems (ADAS), enhancing semi-autonomous driving safety and performance, and informing the development of personalized driver support technologies.

