Regional Gray Matter Volume Identifies High Risk of Unsafe Driving in Healthy Older People

Uniformly positive or negative correlation of cerebral gray matter regions with driving safety behaviors of healthy older drivers

This study investigated the relationship between cerebral gray matter (GM) regions and driving safety behaviors (DSBs) of 98 older drivers without dementia (mean age, 77.72 ± 3.677 years). Their DSBs were evaluated on actual vehicles running on a closed-circuit course. The DSB was scored in six categories: DSB1, visual search behavior; DSB2, speeding; DSB3, signaling of the indicator; DSB4, vehicle stability; DSB5, positioning; and DSB6, steering. The scores were calculated by a single driving instructor; larger scores indicated safer driving performances. Regional GM volumes were measured with voxel-based morphometry by magnetic resonance imaging (MRI). Out of 56 GM regions, 18 were correlated with DSB categories except for DSB4. When a single GM region was correlated with multiple DSB categories, a positive or negative response was uniformly determined for the respective region despite clear differences in the DSB categories. This result suggests the possible existence of two contradictory mechanisms in the brain for DSB. The left postcentral gyrus may largely function in regulating DSBs because it was negatively correlated with five of six DSB categories. Thus, MRI's measurement of regional GM volumes may help deepen the understanding of the diversity and complexity inherent in brain functions for DSBs.

Adult attention-deficit/hyperactivity disorder traits in healthy adults associated with brain volumetric data identify precuneus involvement in traffic crashes

This large-scale study including 2548 healthy adults with no clinical attention-deficit/hyperactivity disorder (ADHD) diagnosis intended to clarify the complex relationships between cerebral grey matter volumes (GMVs), ADHD traits, and driving safety behaviours. Path analysis of magnetic resonance imaging (MRI) results and questionnaires about ADHD traits and traffic crashes over the past decade revealed significant correlations of ADHD traits with different brain regions relevant to different cognitive functions. The left precuneus responsible for visuospatial cognition was the sole region correlated with all ADHD trait categories, suggesting it plays an important role in understanding driving safety and traffic crashes. For the first time, a strong relationship was found among regional GMVs, ADHD traits, and real-life traffic crashes. These insights into the complex interplay may inform the development of an effective intervention with MRI examination to prevent traffic crashes. Large-scale brain volumetric data may further open social applications of behaviour science and neuroimaging.

Task and Resting-State Functional Connectivity Predict Driving Violations

Aberrant driving behaviors cause accidents; however, there is a lack of understanding of the neural mechanisms underlying these behaviors. To address this issue, a task and resting-state functional connectivity was used to predict aberrant driving behavior and associated personality traits. The study included 29 right-handed participants with driving licenses issued for more than 1 year. During the functional magnetic resonance imaging experiment, participants first recorded their resting state and then watched a driving video while continuously rating the risk and speed on each block. Functional connectome-based predictive modeling was employed for whole brain tasks and resting-state functional connectivity to predict driving behavior (violation, error, and lapses), sensation-seeking, and impulsivity. Resting state and task-based functional connectivity were found to significantly predict driving violations, with resting state significantly predicting lapses and task-based functional connectivity showing a tendency to predict errors. Conversely, neither impulsivity nor sensation-seeking was associated with functional connectivity. The results suggest a significant association between aberrant driving behavior, but a nonsignificant association between impulsivity and sensation-seeking, and task-based or resting state functional connectivity. This could provide a deeper understanding of the neural processing underlying reckless driving that may ultimately be used to prevent accidents.

White matter alterations in the dorsal attention network contribute to a high risk of unsafe driving in healthy older people

Aim

Healthy older drivers may be at high risk of fatal traffic accidents. Our recent study showed that volumetric alterations in gray matter in the brain regions within the dorsal attention network (DAN) were strongly related to the risk of unsafe driving in healthy older people. However, the relationship between white matter (WM) structural connectivity and driving ability in healthy older people is still unclear.

Methods

We used diffusion tensor imaging to examine the association between microstructural alterations in the DAN and the risk of unsafe driving among healthy older people. We enrolled 32 healthy older individuals aged over 65 years and screened unsafe drivers using an on-road driving test. We then determined the pattern of WM aberrations in unsafe drivers using tract-based spatial statistics.

Results

The analysis demonstrated that unsafe drivers had significantly higher axial diffusivity values in nine WM clusters compared with safe drivers. These results were primarily observed bilaterally in the dorsal superior longitudinal fasciculus, which is involved in the DAN. Furthermore, correlation analyses showed that higher axial diffusivity values in the superior longitudinal fasciculus were associated with lower Trail Making Test A scores within unsafe drivers. This result suggests that functionally, WM microstructural alterations in the DAN are associated with attention problems, which may contribute to the risk of unsafe driving among healthy older people.

Conclusion

Our findings may elucidate the neurobiological mechanisms underlying the increased risk of unsafe driving in healthy older people, potentially facilitating the development of new interventions to prevent fatal accidents.

Relationships between Personality Traits and Brain Gray Matter Are Different in Risky and Non-risky Drivers

Personality traits such as impulsivity or sensitivity to rewards and punishments have been associated with risky driving behavior, but it is still unclear how brain anatomy is related to these traits as a function of risky driving. In the present study, we explore the neuroanatomical basis of risky driving behavior and how the level of risk-taking influences the relationship between the traits of impulsivity and sensitivity to rewards and punishments and brain gray matter volume. One hundred forty-four participants with different risk-taking tendencies assessed by real-life driving situations underwent MRI. Personality traits were assessed with self-report measures. We observed that the total gray matter volume varied as a function of risky driving tendencies, with higher risk individuals showing lower gray matter volumes. Similar results were found for volumes of brain areas involved in the reward and cognitive control networks, such as the frontotemporal, parietal, limbic, and cerebellar cortices. We have also shown that sensitivity to reward and punishment and impulsivity are differentially related to gray matter volumes as a function of risky driving tendencies. Highly risky individuals show lower absolute correlations with gray matter volumes than less risk-prone individuals. Taken together, our results show that risky drivers differ in the brain structure of the areas involved in reward processing, cognitive control, and behavioral modulation, which may lead to dysfunctional decision-making and riskier driving behavior.

Aging Brains Degrade Driving Safety Performances of the Healthy Elderly

The relationship between aging brains and driving safety performances (DSPs) of elderly drivers was studied. A total of 90 dementia-free participants (63 men and 27 women, mean age 75.31 ± 4.795 years) were recruited and their DSPs were analyzed on actual vehicles running through a closed-circuit course. DSPs were comprehensively evaluated on the basis of driving instructors' scores (DIS). Signaling and visual research behaviors, part of DSPs, were measured to supplement the DIS evaluation by driving recorders (DR) and wearable wireless sensors (WS), respectively. Aging brains were evaluated via magnetic resonance imaging (MRI) findings and experimentally assigned to two grades (high vs. low) of brain atrophy (BA) and leukoaraiosis (LA). Regression analyses on DIS and DR data, and logistic analysis on WS scores showed significant correlations of aging brains with degradation of DSPs. The participant group with more advanced BAs and LAs showed lower DIS, DR data, and WS scores representing degraded DSP regardless of age. These results suggest that MRI examinations from both volumetric and pathological perspectives of brains have the potential to help identify elderly drivers with dangerous driving behaviors. Brain healthcare, lifestyle improvements and medical treatments to suppress BA and LA, may contribute to preventing DSP degradation of elderly drivers with aging brains.