Effective Connectivity Analysis of the Brain Network in Drivers during Actual Driving Using Near-Infrared Spectroscopy

Abstract

Driving a vehicle is a complex activity that requires high-level brain functions. This study aimed to assess the change in effective connectivity (EC) between the prefrontal cortex (PFC), motor-related areas (MA) and vision-related areas (VA) in the brain network among the resting, simple-driving and car-following states. Twelve young male right-handed adults were recruited to participate in an actual driving experiment. The brain delta [HbO2] signals were continuously recorded using functional near infrared spectroscopy (fNIRS) instruments. The conditional Granger causality (GC) analysis, which is a data-driven method that can explore the causal interactions among different brain areas, was performed to evaluate the EC. The results demonstrated that the hemodynamic activity level of the brain increased with an increase in the cognitive workload. The connection strength among PFC, MA and VA increased from the resting state to the simple-driving state, whereas the connection strength relatively decreased during the car-following task. The PFC in EC appeared as the causal target, while the MA and VA appeared as the causal sources. However, l-MA turned into causal targets with the subtask of car-following. These findings indicate that the hemodynamic activity level of the cerebral cortex increases linearly with increasing cognitive workload. The EC of the brain network can be strengthened by a cognitive workload, but also can be weakened by a superfluous cognitive workload such as driving with subtasks.

Effects of HD‐tDCS on Resting‐State Functional Connectivity in the Prefrontal Cortex: An fNIRS Study

“…Therefore, fNIRS has many advantages over other neuroimaging modalities; its application has great potential in studying the functional imaging of the brain [51], perception and cognition [52], behavioral and cognitive neurodevelopment [53,54], somatosensory and bundled optode configuration [55,56], stroke and brain injury [57,58], and brain-computer interfaces [59,60]. Moreover, various studies have used fNIRS to investigate functional connectivity in different brain regions [61][62][63][64][65].…”

Neuromuscular Control of the Agonist–Antagonist Muscle Coordination Affected by Visual Dimension: An EMG-fNIRS Study

“…In this study, the activation in the PFC was higher in the two-dimensional task than that in the one-dimensional task, revealing that the subjects increased the recruitment of the PFC in response to the additional visual input within two-dimensional MCI, which could increase cognitive workload and consequently caused the higher neural activity in the PFC [51]. Liu et al pointed out that the hemodynamic activation in the PFC showed an increasing tendency with the increase of cognitive workload [52]. Basso et al testified that the activation in the PFC was related to the difficulty level of the task, since the harder task could incur more cognitive workload and then require higher activation in the PFC [53].…”

NIRS-KIT: a MATLAB toolbox for both resting-state and task fNIRS data analysis

“… 79 Effective connectivity has been applied in several fNIRS studies. 80 – 82 In addition, although multiple popular group-level statistical models are provided, individual-level statistical tests are not supported in the current version of NIRS-KIT. We plan to incorporate these functionalities to future versions of NIRS-KIT.…”