Working Memory Development and Motor Vehicle Crashes in Young Drivers

An updating-based working memory load alters the dynamics of eye movements but not their spatial extent during free viewing of natural scenes

The relationship between spatial deployments of attention and working memory load is an important topic of study, with clear implications for real-world tasks such as driving. Previous research has generally shown that attentional breadth broadens under higher load, while exploratory eye-movement behaviour also appears to change with increasing load. However, relatively little research has compared the effects of working memory load on different kinds of spatial deployment, especially in conditions that require updating of the contents of working memory rather than simple retrieval. The present study undertook such a comparison by measuring participants' attentional breadth (via an undirected Navon task) and their exploratory eye-movement behaviour (a free-viewing recall task) under low and high updating working memory loads. While spatial aspects of task performance (attentional breadth, and peripheral extent of image exploration in the free-viewing task) were unaffected by the load manipulation, the exploratory dynamics of the free-viewing task (including fixation durations and scan-path lengths) changed under increasing load. These findings suggest that temporal dynamics, rather than the spatial extent of exploration, are the primary mechanism affected by working memory load during the spatial deployment of attention. Further, individual differences in exploratory behaviour were observed on the free-viewing task: all metrics were highly correlated across working memory load blocks. These findings suggest a need for further investigation of individual differences in eye-movement behaviour; potential factors associated with these individual differences, including working memory capacity and persistence versus flexibility orientations, are discussed.

On the importance of working memory in the driving safety field: A systematic review

In recent years, many studies have used poor cognitive functions to explain risk safety differences among drivers. Working memory is a cognitive function with information storage and attentional control that plays a crucial role in driver information processing. Furthermore, it is inextricably linked to parameters such as driving performance, driving eye movements and driving neurophysiology, which have a significant impact on drivers' risky behavior and crash risk. In particular, crash risk is a serious risk to social safety and economic development. For this reason, it is necessary to understand how risk-related working memory affects driving so that pre-driving safety pre-training programs and in-vehicle safety assistance systems for driving can be developed accordingly, contributing to the development of semi-autonomous vehicles and even autonomous vehicles. In this paper, a systematic search of the literature over the past 23 years resulted in 78 articles that met the eligibility criteria and quality assessment. The results show that higher working memory capacity, as measured neuropsychologically, is associated with more consistent and safer driving-related parameters for drivers (e.g., lane keeping) and may be related to pupil dilation during risk perception while driving, which is associated with driving outcomes (tickets, pull-overs, penalty points and fines,and driving accidents) is closely related to the perceived usefulness of the human-machine interface, reaction time, standard deviation of steering wheel corners, etc. when the autonomous driving takes over. In addition, higher working memory load interference was associated with more inconsistent and unsafe driving-related parameters (including but not limited to eye movements, electrophysiology, etc.), with higher working memory load being associated with easier driver concentration on the road, faster heart rate, lower heart rate variability, and lower oxyhemoglobin (OxyHb) and deoxyhemoglobin (DeoxyHb). Only a limited number of studies have simultaneously investigated the relationship between working memory capacity, working memory load and driving, showing an interaction between working memory capacity and working memory load on lane change initiation and lane change correctness, with working memory capacity acting as a covariate that mediated the effect of working memory load on braking reaction time. In addition, working memory-related cognitive training had a transfer effect on improving driving ability. Overall, working memory capacity determines the upper limit of the number of working memory attention resources, while working memory load occupies part of the working memory attention resources, thus influencing information perception, decision judgment, operational response, and collision avoidance in driving. Future effective interventions for safe driving can be combined with capacity training and load alerting. These findings contribute to our understanding of the role of working memory in driving and provide new insights into the design of driver safety training programs and automated driving personalized in-vehicle safety systems and roadside devices such as signage.

Novel use of a virtual driving assessment to classify driver skill at the time of licensure

Motor vehicle crash rates are highest immediately after licensure, and driver error is one of the leading causes. Yet, few studies have quantified driving skills at the time of licensure, making it difficult to identify at-risk drivers before independent driving. Using data from a virtual driving assessment implemented into the licensing workflow in Ohio, this study presents the first population-level study classifying degree of skill at the time of licensure and validating these against a measure of on-road performance: license exam outcomes. Principal component and cluster analysis of 33,249 virtual driving assessments identified 20 Skill Clusters that were then grouped into 4 major summary "Driving Classes"; i) No Issues (i.e. careful and skilled drivers); ii) Minor Issues (i.e. an average new driver with minor vehicle control skill deficits); iii) Major Issues (i.e. drivers with more control issues and who take more risks); and iv) Major Issues with Aggression (i.e. drivers with even more control issues and more reckless and risk-taking behavior). Category labels were determined based on patterns of VDA skill deficits alone (i.e. agnostic of the license examination outcome). These Skill Clusters and Driving Classes had different distributions by sex and age, reflecting age-related licensing policies (i.e. those under 18 and subject to GDL and driver education and training), and were differentially associated with subsequent performance on the on-road licensing examination (showing criterion validity). The No Issues and Minor Issues classes had lower than average odds of failing, and the other two more problematic Driving Classes had higher odds of failing. Thus, this study showed that license applicants can be classified based on their driving skills at the time of licensure. Future studies will validate these Skill Cluster classes in relation to their prediction of post-licensure crash outcomes.

A Systematic Review on the Impact of Hot and Cool Executive Functions on Pediatric Injury Risks: a Meta-Analytic Structural Equation Modeling Approach

Injury is a leading cause of morbidity and mortality among children in the USA. Understanding the impact of executive functions (EFs) on the risk of injuries is crucial for developing effective interventions. However, literature has failed to examine the relationship between multiple EFs and injury domains. The present paper quantitatively synthesized research on cool and hot EFs and children's intentional and unintentional injury risks using a novel meta-analytic structural equation modeling (MASEM) approach. A systematic review was conducted in the following databases: PsycINFO, Scopus, SafetyLit, Cochrane Central, and PubMed (Medline). After screening titles, abstracts, and full texts, a total of 31 studies were eligible for the MASEM analysis. One-stage MASEM was conducted on six conceptualized path analysis models according to the complexity of exogenous and endogenous variables. The MASEM models suggested that hot and cool EFs were negatively associated with children's risk of injury or injury-related risk behaviors regardless of mean age and proportion of females. Among cool EF skills, inhibitory control, but not working memory or cognitive flexibility, was significantly associated with risks of unintentional injuries. Emotion regulation was the dominant hot EF skill examined in the literature and was found significantly associated with risks of non-suicidal self-injuries (NSSIs). EF has a significant impact on children's risk of both unintentional and intentional injuries. Future research should focus on the combined force of hot and cool EF on children's risks of injuries and injury-related risk behaviors.

Rethinking Cell Phone Use While Driving: Isolated Risk Behavior or a Pattern of Risk-Taking Associated with Impulsivity in Young Drivers?

This study examines whether cell phone use stands apart from a general pattern of risky driving practices associated with crashes and impulsivity-related personality traits in young drivers. A retrospective online survey study recruited 384 young drivers from across the United States using Amazon’s Mechanical Turk to complete a survey measuring risky driving practices (including cell phone use), history of crashes, and impulsivity-related personality traits. Almost half (44.5%) of the drivers reported being involved in at least one crash, and the majority engaged in cell phone use while driving (up to 73%). Factor analysis and structural equation modeling found that cell phone use loaded highly on a latent factor with other risky driving practices that were associated with prior crashes (b = 0.15, [95% CI: 0.01, 0.29]). There was also an indirect relationship between one form of impulsivity and crashes through risky driving (b = 0.127, [95% CI: 0.01, 0.30]). Additional analyses did not find an independent contribution to crashes for frequent cell phone use. These results suggest a pattern of risky driving practices associated with impulsivity in young drivers, indicating the benefit of exploring a more comprehensive safe driving strategy that includes the avoidance of cell phone use as well as other risky practices, particularly for young drivers with greater impulsive tendencies.

Advancing our understanding of cognitive development and motor vehicle crash risk: A multiverse representation analysis

Neurobiological and cognitive maturational models are the dominant theoretical account of adolescents' risk-taking behavior. Both the protracted development of working memory (WM) through adolescence, as well as individual differences in WM capacity have been theorized to be related to risk-taking behavior, including reckless driving. In a cohort study of 84 adolescent drivers Walshe et al. (2019) found adolescents who crashed had an attenuated trajectory of WM growth compared to adolescent drivers who never reported being in a crash, but observed no difference in WM capacity at baseline. The objectives of this report were to attempt to replicate these associations and to evaluate their robustness using a hybrid multiverse - specification curve analysis approach, henceforth called multiverse representation analysis (MRA). The authors of the original report provided their data: 84 adolescent drivers with annual evaluations of WM and other risk factors from 2005 to 2013, and of driving experiences in 2015. The original analysis was implemented as described in the original report. An MRA approach was used to evaluate the robustness of the association between developmental trajectories of WM and adolescents' risk-taking (indexed by motor vehicle crash involvement) to different reasonable methodological choices. We enumerated 6 reasonable choice points in data processing-analysis configurations: (1) model type: latent growth or multi-level regression, (2) treatment of WM data; (3) which waves are included; (4) covariate treatment; (5) how time is coded; and (6) link function/estimation method: weighted least squares means and variance estimation (WLSMV) with a linear link versus logistic regression with maximum likelihood estimation. This multiverse consists of 96 latent growth models and 18 multi-level regression models.

Reward-Sensitive Basal Ganglia Stabilize the Maintenance of Goal-Relevant Neural Patterns in Adolescents

Maturation of basal ganglia (BG) and frontoparietal circuitry parallels developmental gains in working memory (WM). Neurobiological models posit that adult WM performance is enhanced by communication between reward-sensitive BG and frontoparietal regions, via increased stability in the maintenance of goal-relevant neural patterns. It is not known whether this reward-driven pattern stability mechanism may have a role in WM development. In 34 young adolescents (12.16-14.72 years old) undergoing fMRI, reward-sensitive BG regions were localized using an incentive processing task. WM-sensitive regions were localized using a delayed-response WM task. Functional connectivity analyses were used to examine the stability of goal-relevant functional connectivity patterns during WM delay periods between and within reward-sensitive BG and WM-sensitive frontoparietal regions. Analyses revealed that more stable goal-relevant connectivity patterns between reward-sensitive BG and WM-sensitive frontoparietal regions were associated with both greater adolescent age and WM ability. Computational lesion models also revealed that functional connections to WM-sensitive frontoparietal regions from reward-sensitive BG uniquely increased the stability of goal-relevant functional connectivity patterns within frontoparietal regions. Findings suggested (1) the extent to which goal-relevant communication patterns within reward-frontoparietal circuitry are maintained increases with adolescent development and WM ability and (2) communication from reward-sensitive BG to frontoparietal regions enhances the maintenance of goal-relevant neural patterns in adolescents' WM. The maturation of reward-driven stability of goal-relevant neural patterns may provide a putative mechanism for understanding the developmental enhancement of WM.