Immersion in nature enhances neural indices of executive attention.

There is conjecture that our modern urban environments place high demand on our attentional resources, which can become depleted over time and cause mental fatigue. Natural environments, on the other hand, are thought to provide relief from this demand and allow our resources to be replenished. While these claims have been assessed with self-report and behavioral measures, there is limited understanding of the neural mechanisms underlying these attentional benefits. The present randomized controlled trial fills this gap in the literature by using electroencephalography to explore three aspects of attention-alerting, orienting, and executive control-from a behavioral and neural perspective. Participants (N = 92) completed the Attention Network Task before and after either a 40-min walk in nature or a 40-min walk in a control, urban environment. Participants that walked in nature reported their walk to be more restorative than those that walked in the urban environment. Furthermore, the nature group showed an enhanced error-related negativity after their walk, an event-related brain component that indexes executive control capacity, whereas the urban group did not. These findings demonstrate that a 40-min nature walk enhances executive control at a neural level, providing a potential neural mechanism for attention restoration in nature.

Driver behavior while using Level 2 vehicle automation: a hybrid naturalistic study.

Vehicle automation is becoming more prevalent. Understanding how drivers use this technology and its safety implications is crucial. In a 6-8 week naturalistic study, we leveraged a hybrid naturalistic driving research design to evaluate driver behavior with Level 2 vehicle automation, incorporating unique naturalistic and experimental control conditions. Our investigation covered four main areas: automation usage, system warnings, driving demand, and driver arousal, as well as secondary task engagement. While on the interstate, drivers were advised to engage Level 2 automation whenever they deemed it safe, and they complied by using it over 70% of the time. Interestingly, the frequency of system warnings increased with prolonged use, suggesting an evolving relationship between drivers and the automation features. Our data also revealed that drivers were discerning in their use of automation, opting for manual control under high driving demand conditions. Contrary to common safety concerns, our data indicated no significant rise in driver fatigue or fidgeting when using automation, compared to a control condition. Additionally, observed patterns of engagement in secondary tasks like radio listening and text messaging challenge existing assumptions about automation leading to dangerous driver distraction. Overall, our findings provide new insights into the conditions under which drivers opt to use automation and reveal a nuanced behavioral profile that emerges when automation is in use.

This Is Your Brain on Autopilot 2.0: The Influence of Practice on Driver Workload and Engagement During On-Road, Partially Automated Driving.

OBJECTIVE: This on-road study employed behavioral and neurophysiological measurement techniques to assess the influence of six weeks of practice driving a Level 2 partially automated vehicle on driver workload and engagement. BACKGROUND: Level 2 partial automation requires a driver to maintain supervisory control of the vehicle to detect "edge cases" that the automation is not equipped to handle. There is mixed evidence regarding whether drivers can do so effectively. There is also an open question regarding how practice and familiarity with automation influence driver cognitive states over time. METHOD: Behavioral and neurophysiological measures of driver workload and visual engagement were recorded from 30 participants at two testing sessions-with a six-week familiarization period in-between. At both testing sessions, participants drove a vehicle with partial automation engaged (Level 2) and not engaged (Level 0) on two interstate highways while reaction times to the detection response task (DRT) and neurophysiological (EEG) metrics of frontal theta and parietal alpha were recorded. RESULTS: DRT results demonstrated that partially automated driving placed more cognitive load on drivers than manual driving and six weeks of practice decreased driver workload-though only when the driving environment was relatively simple. EEG metrics of frontal theta and parietal alpha showed null effects of partial automation. CONCLUSION: Driver workload was influenced by level of automation, specific highway characteristics, and by practice over time, but only on a behavioral level and not on a neural level. APPLICATION: These findings expand our understanding of the influence of practice on driver cognitive states under Level 2 partial automation.

To err is human- to understand error-processing is divine: Contributions of working memory and anxiety to error-related brain and pupil responses.

Both anxiety and working memory capacity appear to predict increased (more negative) error-related negativity (ERN) amplitudes, despite being inversely related to one another. Until the interactive effects of these variables on the ERN are clarified, there may be challenges posed to our ability to use the ERN as an endophenotype for anxiety, as some have suggested. The compensatory error monitoring hypothesis suggests that high trait-anxiety individuals have larger ERN amplitudes because they must employ extra, compensatory efforts to override the working memory demands of their anxiety. Yet, to our knowledge, no ERN study has employed direct manipulation of working memory demands in conjunction with direct manipulations of induced (state) anxiety. Furthermore, little is known about how these manipulations affect other measures of error processing, such as the error-related pupil dilation response and post-error behavioral adjustments. Therefore, we manipulate working memory load and anxiety in a 2 × 2 within-subjects design to examine the interactive effects of working memory load and anxiety on ERN amplitude, error-related pupil dilation response amplitude, and post-error behavior. There were no effects of our manipulations on ERN amplitude, suggesting a strong interpretation of compensatory error-processing theory. However, our worry manipulation affected post-error behavior, such that worry caused a reduction in post-error accuracy. Additionally, our working memory manipulation affected error-related PDR magnitude and the amplitude of the error-related positivity (Pe), such that increased working memory load decreased the amplitude of these responses. Implications of these results within the context of the compensatory error processing framework are discussed.

Vigilance Decrement During On-Road Partially Automated Driving Across Four Systems.

OBJECTIVE: This study uses a detection task to measure changes in driver vigilance when operating four different partially automated systems. BACKGROUND: Research show temporal declines in detection task performance during manual and fully automated driving, but the accuracy of using this approach for measuring changes in driver vigilance during on-road partially automated driving is yet unproven. METHOD: Participants drove four different vehicles (Tesla Model 3, Cadillac CT6, Volvo XC90, and Nissan Rogue) equipped with level-2 systems in manual and partially automated modes. Response times to a detection task were recorded over eight consecutive time periods. RESULTS: Bayesian analysis revealed a main effect of time period and an interaction between mode and time period. A main effect of vehicle and a time period x vehicle interaction were also found. CONCLUSION: Results indicated that the reduction in detection task performance over time was worse during partially automated driving. Vehicle-specific analysis also revealed that detection task performance changed across vehicles, with slowest response time found for the Volvo. APPLICATION: The greater decline in detection performance found in automated mode suggests that operating level-2 systems incurred in a greater vigilance decrement, a phenomenon that is of interest for Human Factors practitioners and regulators. We also argue that the observed vehicle-related differences are attributable to the unique design of their in-vehicle interfaces.

Updating the relationship of the Ne/ERN to task-related behavior: A brief review and suggestions for future research.

The error negativity/error-related negativity (Ne/ERN) is one of the most well-studied event-related potential (ERP) components in the electroencephalography (EEG) literature. Peaking about 50 ms after the commission of an error, the Ne/ERN is a negative deflection in the ERP waveform that is thought to reflect error processing in the brain. While its relationships to trait constructs such as anxiety are well-documented, there is still little known about how the Ne/ERN may subsequently influence task-related behavior. In other words, does the occurrence of the Ne/ERN trigger any sort of error corrective process, or any other behavioral adaptation to avoid errors? Several theories have emerged to explain how the Ne/ERN may implement or affect behavior on a task, but evidence supporting each has been mixed. In the following manuscript, we review these theories, and then systematically discuss the reasons that there may be discrepancies in the literature. We review both the inherent biological factors of the neural regions that underlie error-processing in the brain, and some of the researcher-induced factors in analytic and experimental choices that may be exacerbating these discrepancies. We end with a table of recommendations for future researchers who aim to understand the relationship between the Ne/ERN and behavior.

Measuring affect and complex working memory in natural and urban environments.

Introduction: Research suggests that spending time in natural environments is associated with cognitive and affective benefits, while increased use of technology and time spent in urban environments are associated with depletion of cognitive resources and an increasing prevalence of mental illness. Attention Restoration Theory suggests that exposure to natural environments can restore depleted attentional resources and thereby improve cognitive functioning and mood. Specifically, recent meta-analyses have revealed that the most improved cognitive abilities after nature exposure include selective attention, working memory, and cognitive flexibility. Methods: While existing studies examined these cognitive abilities, few have examined the Operation Span (OSPAN), a complex measure of working memory capacity. Therefore, the current study (N = 100) compared performance on the OSPAN and self-reported mood using the Positive and Negative Affect Schedule before and after a 30-min walk in a natural or urban environment. Results: Results from the study showed that both groups exhibited an increase in positive affect and a decrease in negative affect, suggesting that going outside for a walk can boost mood regardless of environment type. Inconsistent with past work, there were no significant changes in OSPAN scores before and after the walk for either environment type. Discussion: Future studies should analyze how the length of time spent in the environment, certain characteristics of the environment, and individual differences in connectedness to nature may impact attention restoration to gain insight on nature's ability to improve our affect and cognition.

Ebola virus disease: In vivo protection provided by the PAMP restricted TLR3 agonist rintatolimod and its mechanism of action.

Ebola virus (EBOV) is a highly infectious and lethal pathogen responsible for sporadic self-limiting clusters of Ebola virus disease (EVD) in Central Africa capable of reaching epidemic status. 100% protection from lethal EBOV-Zaire in Balb/c mice was achieved by rintatolimod (Ampligen) at the well tolerated human clinical dose of 6 mg/kg. The data indicate that the mechanism of action is rintatolimod's dual ability to act as both a competitive decoy for the IID domain of VP35 blocking viral dsRNA sequestration and as a pathogen-associated molecular pattern (PAMP) restricted agonist for direct TLR3 activation but lacking RIG-1-like cytosolic helicase agonist properties. These data show promise for rintatolimod as a prophylactic therapy against human Ebola outbreaks.

Freshwater mussel conservation: A global horizon scan of emerging threats and opportunities.

We identified 14 emerging and poorly understood threats and opportunities for addressing the global conservation of freshwater mussels over the next decade. A panel of 17 researchers and stakeholders from six continents submitted a total of 56 topics that were ranked and prioritized using a consensus-building Delphi technique. Our 14 priority topics fell into five broad themes (autecology, population dynamics, global stressors, global diversity, and ecosystem services) and included understanding diets throughout mussel life history; identifying the drivers of population declines; defining metrics for quantifying mussel health; assessing the role of predators, parasites, and disease; informed guidance on the risks and opportunities for captive breeding and translocations; the loss of mussel-fish co-evolutionary relationships; assessing the effects of increasing surface water changes; understanding the effects of sand and aggregate mining; understanding the effects of drug pollution and other emerging contaminants such as nanomaterials; appreciating the threats and opportunities arising from river restoration; conserving understudied hotspots by building local capacity through the principles of decolonization; identifying appropriate taxonomic units for conservation; improved quantification of the ecosystem services provided by mussels; and understanding how many mussels are enough to provide these services. Solutions for addressing the topics ranged from ecological studies to technological advances and socio-political engagement. Prioritization of our topics can help to drive a proactive approach to the conservation of this declining group which provides a multitude of important ecosystem services.

Dynamic workload measurement and modeling: Driving and conversing.

Tillman et al. (2017) used evidence-accumulation modeling to ascertain the effects of a conversation (either with a passenger or on a hands-free cell phone) on a drivers' mental workload. They found that a concurrent conversation increased the response threshold but did not alter the rate of evidence accumulation. However, this earlier research collapsed across speaking and listening components of a natural conversation, potentially masking any dynamic fluctuations associated with this dual-task combination. In the present study, a unique implementation of the detection response task was used to simultaneously measure the demands on the driver and the nondriver when they were speaking or when they were listening. We found that the natural ebb and flow of a conversation altered both the rate of evidence accumulation and the response threshold for drivers and nondrivers alike. The dynamic fluctuations in cognitive workload observed with this novel method illustrate how quickly the parameters of cognition are altered by real-time task demands. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

This Is Your Brain on Autopilot: Neural Indices of Driver Workload and Engagement During Partial Vehicle Automation.

OBJECTIVE: This research explores the effect of partial vehicle automation on neural indices of mental workload and visual engagement during on-road driving. BACKGROUND: There is concern that the introduction of automated technology in vehicles may lead to low driver stimulation and subsequent disengagement from the driving environment. Simulator-based studies have examined the effect of automation on a driver's cognitive state, but it is unknown how the conclusions translate to on-road driving. Electroencephalographic (EEG) measures of frontal theta and parietal alpha can provide insight into a driver's mental workload and visual engagement while driving under various conditions. METHOD: EEG was recorded from 71 participants while driving on the roadway. We examined two age cohorts, on two different highway configurations, in four different vehicles, with partial vehicle automation both engaged and disengaged. RESULTS: Analysis of frontal theta and parietal alpha power revealed that there was no change in mental workload or visual engagement when driving manually compared with driving under partial vehicle automation. CONCLUSION: Drivers new to the technology remained engaged with the driving environment when operating under partial vehicle automation. These findings suggest that the concern surrounding driver disengagement under vehicle automation may need to be tempered, at least for drivers new to the experience. APPLICATION: These findings expand our understanding of the effects of partial vehicle automation on drivers' cognitive states.

The persistence of distraction: The hidden costs of intermittent multitasking.

We examined the hidden costs of intermittent multitasking. Participants performed a pursuit-tracking task (Experiment 1) or drove in a high-fidelity driving simulator (Experiment 2) by itself or while concurrently performing an easy or difficult backwards counting task that periodically started and stopped, creating on-task and off-task multitasking epochs. A novel application of the Detection Response Task (DRT), a standardized protocol for measuring cognitive workload (ISO 17488, 2016), was used to measure performance in the on-task and off-task intervals. We found striking costs that persisted well after the counting task had stopped. In fact, the multitasking costs dissipated as a negatively accelerated function of time with the largest costs observed immediately after multitasking ceased. Performance in the off-task interval remained above baseline levels throughout the 30-s off-task interval. We suggest that loading new procedures into working memory occurs fairly quickly, whereas purging this information from working memory takes considerably longer. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

A cognitive model of response omissions in distraction paradigms.

The effects of distraction on responses manifest in three ways: prolonged reaction times, and increased error and response omission rates. However, the latter effect is often ignored or assumed to be due to a separate cognitive process. We investigated omissions occurring in two paradigms that manipulated distraction. One required simple stimulus detection of younger participants, the second required choice responses and was completed by both younger and older participants. We fit data from these paradigms with a model that identifies three causes of omissions: two are related to the process of accumulating the evidence on which a response is based: intrinsic omissions (due to between-trial variation in accumulation rates making it impossible to ever reach the evidence threshold) and design omissions (due to response windows that cause slow responses not to be recorded; a third, contaminant omissions, allows for a cause unrelated to the response process. In both data sets systematic differences in omission rates across conditions were accounted for by task-related omissions. Intrinsic omissions played a lesser role than design omissions, even though the presence of design omissions was not evident in descriptive analyses of the data. The model provided an accurate account of all aspects of the detection data and the choice-response data, but slightly underestimated overall omissions in the choice paradigm, particularly in older participants, suggesting that further investigation of contaminant omission effects is needed.

No Difference in Arousal or Cognitive Demands Between Manual and Partially Automated Driving: A Multi-Method On-Road Study.

INTRODUCTION: Partial driving automation is not always reliable and requires that drivers maintain readiness to take over control and manually operate the vehicle. Little is known about differences in drivers' arousal and cognitive demands under partial automation and how it may make it difficult for drivers to transition from automated to manual modes. This research examined whether there are differences in drivers' arousal and cognitive demands during manual versus partial automation driving. METHOD: We compared arousal (using heart rate) and cognitive demands (using the root mean square of successive differences in normal heartbeats; RMSSD, and Detection Response Task; DRT) while 39 younger (M = 28.82 years) and 32 late-middle-aged (M = 52.72 years) participants drove four partially automated vehicles (Cadillac, Nissan Rogue, Tesla, and Volvo) on interstate highways. If compared to manual driving, drivers' arousal and cognitive demands were different under partial automation, then corresponding differences in heart rate, RMSSD, and DRT would be expected. Alternatively, if drivers' arousal and cognitive demands were similar in manual and partially automated driving, no difference in the two driving modes would be expected. RESULTS: Results suggest no significant differences in heart rate, RMSSD, or DRT reaction time performance between manual and partially automated modes of driving for either younger or late-middle-aged adults across the four test vehicles. A Bayes Factor analysis suggested that heart rate, RMSSD, and DRT data showed extreme evidence in favor of the null hypothesis. CONCLUSION: This novel study conducted on real roads with a representative sample provides important evidence of no difference in arousal and cognitive demands. Younger and late-middle-aged motorists who are new to partial automation are able to maintain arousal and cognitive demands comparable to manual driving while using the partially automated technology. Drivers who are more experienced with partially automated technology may respond differently than those with limited prior experience.

Real-time prediction of short-timescale fluctuations in cognitive workload.

Human operators often experience large fluctuations in cognitive workload over seconds timescales that can lead to sub-optimal performance, ranging from overload to neglect. Adaptive automation could potentially address this issue, but to do so it needs to be aware of real-time changes in operators' spare cognitive capacity, so it can provide help in times of peak demand and take advantage of troughs to elicit operator engagement. However, it is unclear whether rapid changes in task demands are reflected in similarly rapid fluctuations in spare capacity, and if so what aspects of responses to those demands are predictive of the current level of spare capacity. We used the ISO standard detection response task (DRT) to measure cognitive workload approximately every 4 s in a demanding task requiring monitoring and refueling of a fleet of simulated unmanned aerial vehicles (UAVs). We showed that the DRT provided a valid measure that can detect differences in workload due to changes in the number of UAVs. We used cross-validation to assess whether measures related to task performance immediately preceding the DRT could predict detection performance as a proxy for cognitive workload. Although the simple occurrence of task events had weak predictive ability, composite measures that tapped operators' situational awareness with respect to fuel levels were much more effective. We conclude that cognitive workload does vary rapidly as a function of recent task events, and that real-time predictive models of operators' cognitive workload provide a potential avenue for automation to adapt without an ongoing need for intrusive workload measurements.

The autonomic nervous system in its natural environment: Immersion in nature is associated with changes in heart rate and heart rate variability.

Stress Recovery Theory (SRT) suggests that time spent in nature reduces stress. While many studies have examined changes in stress physiology after exposure to nature imagery, nature virtual reality, or nature walks, this study is the first to examine changes in heart rate (HR) and vagally mediated HR variability, as assessed by Respiratory Sinus Arrythmia (RSA), after a longer duration of nature exposure. Consistent with SRT, we hypothesized that immersion in nature would promote stress recovery, as indexed by an increase in RSA and a decrease in HR. We also predicted that exposure to nature would improve self-reported mood. We used a within-subjects design (N = 67) to assess changes in peripheral physiology before, during, and after a 5-day nature trip. Results demonstrated a significant decrease in RSA and a significant increase in HR during the trip compared to before or after the trip, suggesting that immersion in nature is associated with a shift toward parasympathetic withdrawal and possible sympathetic activation. These results were contrary to our hypotheses and may suggest increased attentional intake or presence of emotions associated with an increase in sympathetic activation. We also found an improvement in self-reported measures of mood during the trip compared to before or after the trip, confirming our hypotheses and replicating previous research. Implications of this study are discussed in the context of SRT.

Resting-state posterior alpha power changes with prolonged exposure in a natural environment.

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.

Effect of disease duration in a randomized Phase III trial of rintatolimod, an immune modulator for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.

BACKGROUND: Rintatolimod is a selective TLR3 agonist, which has demonstrated clinical activity for ME/CFS in Phase II and Phase III double-blind, placebo-controlled, randomized, multi-site clinical trials. METHODS AND FINDINGS: A hypothesis-based post-hoc analysis of the Intent to Treat (ITT) population diagnosed with ME/CFS from 12 independent clinical sites of a Phase III trial was performed to evaluate the effect of rintatolimod therapy based on disease duration. The clinical activity of rintatolimod was evaluated by exercise treadmill tolerance (ETT) using a modified Bruce protocol. The ITT population (n = 208) was divided into two subsets of symptom duration. Patients with symptom duration of 2-8 years were identified as the Target Subset (n = 75); the remainder (<2 year plus >8 year) were identified as the Non-Target Subset (n = 133). Placebo-adjusted percentage improvements in exercise duration and the vertical rise for the Target Subset (n = 75) were more than twice that of the ITT population. The Non-Target Subset (n = 133) failed to show any clinically significant ETT response to rintatolimod when compared to placebo. Within the Target Subset, 51.2% of rintatolimod-treated patients improved their exercise duration by ≥25% (p = 0.003) despite reduced statistical power from division of the original ITT population into two subsets. CONCLUSION/SIGNIFICANCE: Analysis of ETT from a Phase III trial has identified within the ITT population, a subset of ME/CFS patients with ≥2 fold increased exercise response to rintatolimod. Substantial improvement in physical performance was seen for the majority (51.2%) of these severely debilitated patients who improved exercise duration by ≥25%. This magnitude of exercise improvement was associated with clinically significant enhancements in quality of life. The data indicate that ME/CFS patients have a relatively short disease duration window (<8 years) to expect a significant response to rintatolimod under the dosing conditions utilized in this Phase III clinical trial. These results may have direct relevance to the cognitive impairment and fatigue being experienced by patients clinically recovered from COVID-19 and free of detectable SARS-CoV-2. TRIAL REGISTRATION: ClinicalTrials.gov: NCT00215800.