Rachel J. Hopman

Purpose: Today’s children are increasingly inactive, with >50% not meeting the recommended 60 minutes of daily physical activity (PA). Recent reports suggest scores in reading and mathematics have also declined. Virtual reality (VR) is a technology that can be used to simulate real-world scenarios, like classroom learning. This study investigated whether a single dose of walking benefits learning in a VR classroom (measured via quiz performance). Method: Forty-seven children (15 females, 9.64 [0.12] y) completed 2, randomized and counterbalanced 20-minute interventions on separate days: acute PA (walking) and seated rest (control), followed by a stationary educational lesson in a distracting VR classroom. Children then completed a quiz on the lesson. Results: Children had higher quiz performance following PA (z-score = 0.16 [0.13]) compared with following rest (z-score = −0.18 (0.14); F_1,45 = 6.17, P = .017), indicating that PA enhanced learning. Children with average intelligence quotient had quiz performance that was higher after PA (z-score = 0.04 [0.20]) compared with after rest (z-score = −0.60 [0.19]), t(22) = 3.34, P = .003. Higher intelligence quotient children did not demonstrate differences in quiz performance after PA compared with after rest. Conclusions: Learning in a VR classroom may be improved following acute PA, particularly for children with average intelligence quotient. These findings support public health guidelines promoting PA across the day.

Exposure to environments that contain natural features can benefit mood, cognition, and physiological responses. Previous research proposed exposure to nature restores voluntary attention – attention that is directed towards a task through top down control. Voluntary attention is limited in capacity and depletes with use. Nature provides unique stimuli that do not require voluntary attention; therefore, the neural resources needed for attention to operate efficiently are theorized to restore when spending time in nature. Electroencephalography reflects changes in attention through fluctuations in power within specific frequencies. The current study (N = 29) measured changes in averaged resting state posterior alpha power before, during, and after a multiday nature exposure. Linear mixed-effects models revealed posterior alpha power was significantly lower during the nature exposure compared to pre-trip and post-trip testing, suggesting posterior alpha power may be a potential biomarker for differences related to exposure to natural and urban environments.

Accumulating evidence suggests that exercise training is associated with improvements in brain health in older adults, yet the extant literature is insufficient in detailing why exercise training facilitates brain structure and function. Specifically, few studies have employed the FITT-VP principle (i.e., Frequency, Intensity, Time, Type, Volume, and Progression) to characterize the exercise exposure, thus research is yet to specify which characteristics of exercise training benefit brain outcomes. To determine whether exercise training is consequential to cognitive and brain outcomes, we conducted a systematic review investigating the effects of exercise training on brain structure and function in older adults. PubMed and Scopus were searched from inception to February 2020, and study quality was assessed using the Cochrane risk-of-bias tool. A total of 24 randomized controlled trials were included. This systematic review indicates that older adults involved in exercise training may derive general benefits to brain health, as reflected by intervention-induced changes in brain structure and function. However, such benefits are dependent upon the dose of the exercise intervention. Importantly, current evidence remains limited for applied exercise prescriptions (e.g., volume, progression) and future research is needed to clarify the effects of exercise training on cognitive and brain outcomes in older adults.

The introduction of semi-automated driving systems is expected to mitigate the safety consequences of human error. Observational findings suggest that relinquishing control of vehicle operational control to assistance systems might diminish driver engagement in the driving task, by reducing levels of arousal. In this study, drivers drove a Tesla Model S with Autopilot in both semi-automated and manual modes. Driver behavior was monitored using a combination of physiological and behavioral measures. Compared to manual driving, a reduction in driver physiological activation was observed during semi-automated driving. Also, performance to the peripheral detection task suffered in semi-automated mode, with slower response times recorded in this condition than during manual driving. Taken together, our data suggest that semi-automated driving might not ease safety consequences of human error. Instead, these findings suggest it might cause a drop in driver monitoring, possibly followed by a spike in automation-generated distraction.

The goal of this research was to examine the impact of voice-based interactions using 3 different intelligent personal assistants (Apple's Siri, Google's Google Now for Android phones, and Microsoft's Cortana) on the cognitive workload of the driver. In 2 experiments using an instrumented vehicle on suburban roadways, we measured the cognitive workload of drivers when they used the voice-based features of each smartphone to place a call, select music, or send text messages. Cognitive workload was derived from primary task performance through video analysis, secondary-task performance using the Detection Response Task (DRT), and subjective mental workload. We found that workload was significantly higher than that measured in the single-task drive. There were also systematic differences between the smartphones: The Google system placed lower cognitive demands on the driver than the Apple and Microsoft systems, which did not differ. Video analysis revealed that the difference in mental workload between the smartphones was associated with the number of system errors, the time to complete an action, and the complexity and intuitiveness of the devices. Finally, surprisingly high levels of cognitive workload were observed when drivers were interacting with the devices: "on-task" workload measures did not systematically differ from that associated with a mentally demanding Operation Span (OSPAN) task. The analysis also found residual costs associated using each of the smartphones that took a significant time to dissipate. The data suggest that caution is warranted in the use of smartphone voice-based technology in the vehicle because of the high levels of cognitive workload associated with these interactions. (PsycINFO Database Record

This research examined the impact of in-vehicle information system (IVIS) interactions on the driver’s cognitive workload; 257 subjects participated in a weeklong evaluation of the IVIS interaction in one of ten different model-year 2015 automobiles. After an initial assessment of the cognitive workload associated with using the IVIS, participants took the vehicle home for 5 days and practiced using the system. At the end of the 5 days of practice, participants returned and the workload of these IVIS interactions was reassessed. The cognitive workload was found to be moderate to high, averaging 3.34 on a 5-point scale and ranged from 2.37 to 4.57. The workload was associated with the intuitiveness and complexity of the system and the time it took participants to complete the interaction. The workload experienced by older drivers was significantly greater than that experienced by younger drivers performing the same operations. Practice did not eliminate the interference from IVIS interactions. In fact, IVIS interactions that were difficult on the first day were still relatively difficult to perform after a week of practice. Finally, there were long-lasting residual costs after the IVIS interactions had terminated. The higher levels of workload should serve as a caution that these voice-based interactions can be cognitively demanding and ought not to be used indiscriminately while operating a motor vehicle.

Objective: The cognitive workload of three Smartphone Digital Assistants (SDA) was manipulated in an on-off manner while participants drove an instrumented vehicle in order to measure the costs associated with intermittent dual tasking. Background: Previous research has shown costs in productivity when switching between two discrete tasks; however, similar costs have not yet been examined using intermittent, continuous dual tasks. Methods: Participating drivers completed 5 conditions: baseline driving, 3 SDA conditions, and a cognitively demanding math-memory operation span (OSPAN) task, each while responding to Detection Response Task (DRT) stimuli. Within the SDA conditions, on- and off-task DRT performance was compared to baseline driving and to the OSPAN task performance. Results: The on-task periods of the SDA conditions resulted in similar RTs as the OSPAN condition, while the off-task periods did not immediately return to baseline driving performance. Post hoc analyses of the on-off transitions within the SDA conditions revealed a gradual return to baseline driving performance over the course of 18 seconds. Conclusions: The delays in returning to baseline driving performance after completing a secondary task raise concerns about the usage of in-vehicle devices while driving as the effects of the delays last beyond the cessation of the SDA interaction.