Effective Connectivity Analysis of Brain Activated Regions during Distracted Driving

Abstract

This study aims to use functional magnetic resonance imaging (fMRI) to assess the effective connectivity between the regions of the brain activated when driving and performing a secondary task (addition task). The subjects used an MR-compatible driving simulator ㅊ to manipulate the driving wheel with both hands and control the pedals (accelerator and brake) with their right foot as if they were driving in an actual environment. Effective connectivity analysis was performed for three regions of the right and the left hemispheres with the highest z-scores, and six of the regions of the entire brain (right and left hemisphere) activated during driving by dynamic causal modeling (DCM). In the right hemisphere, a motor control pathway related to movement control for driving performance was discovered; in the left hemisphere, the pathways in the regions related to movement control for driving performance, starting with the region associated with the secondary task, were discovered. In the whole brain, connectivity was discovered in each of the right and left hemispheres. The motor network of declarative memory, which is the connectivity of the right thalamus, left lingual gyrus, and right precentral gyrus, was worth noting. These results seem meaningful, as they demonstrate the connectivity associated with the control of voluntary movement related to memory from human experience, although limited to driving tasks.

Research on driving fatigue detection based on basic scale entropy and MVAR-PSI

“…Among them, the subjective detection method is affected by the subjective judgment ability of the driver and the researcher, and has certain limitations in detecting the fatigue state, and is usually used as an auxiliary method. In recent years, people have conducted a lot of research on objective methods of driving fatigue detection (Jiao et al 2004, Dorrian et al 2007, Liu et al 2017, Choi et al 2021. Studies have shown that using physiological signal as the index to evaluate driving fatigue has the advantages of objectivity and accuracy, convenient collection and good universality, which is a promising method to study driving fatigue.…”