Motor vehicle crashes remain a leading cause of injury and death in adolescents, with teen drivers three times more likely to be in a fatal crash when compared to adults. One potential contributing risk factor is the ongoing development of executive functioning with maturation of the frontal lobe through adolescence and into early adulthood. Atypical development resulting in poor or impaired executive functioning (as in Attention-Deficit/Hyperactivity Disorder) has been associated with risky driving and crash outcomes. However, executive function broadly encompasses a number of capacities and domains (e.g., working memory, inhibition, set-shifting). In this review, we examine the role of various executive function sub-processes in adolescent driver behavior and crash rates. We summarize the state of methods for measuring executive control and driving outcomes and highlight the great heterogeneity in tools with seemingly contradictory findings. Lastly, we offer some suggestions for improved methods and practical ways to compensate for the effects of poor executive function (such as in-vehicle assisted driving devices). Given the key role that executive function plays in safe driving, this review points to an urgent need for systematic research to inform development of more effective training and interventions for safe driving among adolescents.

Throughout the US, graduated driver licensing (GDL) laws have contributed to lowering motor vehicle crash risk¹; however, crash rates (both per driver and per mile driven) remain disproportionately high among young, novice drivers.^2-4 Motor vehicle crashes are one of the most preventable public health problems in the US: driver error accounts for an estimated 96% of crashes,⁵ and newly licensed drivers commit more safety-critical driving errors than more experienced drivers.⁶

Driving, a skill commonly acquired during adolescence, is also a potentially dangerous behavior. Motor vehicle crashes are the leading cause of injury and death for adolescents in the United States.¹ When compared with other age groups, adolescent drivers have the highest rate of crashes, injuries, and mortality.² Poor skills and inexperience explain some of this risk early after licensure: crash rates are highest during the first 6 months of independent driving.^3,4 However, even among equally novice drivers, crash risk is age graded. At the outset of independent driving, drivers aged approximately 17 years have a higher crash rate than drivers aged approximately 20 years.³ Given this age-graded risk, individual variation in development is likely associated with crash risk, but its nature and contribution to this risk is not known.

Magnetoencephalography (MEG) is particularly well‐suited to the study of human motor cortex oscillatory rhythms and motor control. However, the motor tasks studied to date are largely overly simplistic. This study describes a new approach: a novel event‐based simulated drive made operational via MEG compatible driving simulator hardware, paired with differential beamformer methods to characterize the neural correlates of realistic, complex motor activity. We scanned 23 healthy individuals aged 16–23 years (mean age = 19.5, SD = 2.5; 18 males and 5 females, all right‐handed) who completed a custom‐built repeated trials driving scenario. MEG data were recorded with a 275‐channel CTF, and a volumetric magnetic resonance imaging scan was used for MEG source localization. To validate this paradigm, we hypothesized that pedal‐use would elicit expected modulation of primary motor responses beta‐event‐related desynchronization (B‐ERD) and movement‐related gamma synchrony (MRGS). To confirm the added utility of this paradigm, we hypothesized that the driving task could also probe frontal cognitive control responses (specifically, frontal midline theta [FMT]). Three of 23 participants were removed due to excess head motion (>1.5 cm/trial), confirming feasibility. Nonparametric group analysis revealed significant regions of pedal‐use related B‐ERD activity (at left precentral foot area, as well as bilateral superior parietal lobe: p < .01 corrected), MRGS (at medial precentral gyrus: p < .01 corrected), and FMT band activity sustained around planned braking (at bilateral superior frontal gyrus: p < .01 corrected). This paradigm overcomes the limits of previous efforts by allowing for characterization of the neural correlates of realistic, complex motor activity in terms of brain regions, frequency bands and their dynamic temporal interplay.