Multitasking Induced Contextual Blindness.

OBJECTIVE: To examine the impact of secondary task performance on contextual blindness arising from the suppression and masking of temporal and spatial sequence learning. BACKGROUND: Dual-task scenarios can lead to a diminished ability to use environmental cues to guide attention, a phenomenon that is related to multitasking-induced inattentional blindness. This research aims to extend the theoretical understanding of how secondary tasks can impair attention and memory processes in sequence learning and access. METHOD: We conducted three experiments. In Experiment 1, we used a serial reaction time task to investigate the impact of a secondary tone counting task on temporal sequence learning. In Experiment 2, we used a contextual cueing task to examine the effects of dual-task performance on spatial cueing. In Experiment 3, we integrated and extended these concepts to a simulated driving task. RESULTS: Across the experiments, the performance of a secondary task consistently suppressed (all experiments) and masked task learning (experiments 1 and 3). In the serial response and spatial search tasks, dual-task conditions reduced the accrual of sequence knowledge and impaired knowledge expression. In the driving simulation, similar patterns of learning suppression from multitasking were also observed. CONCLUSION: The findings suggest that secondary tasks can significantly suppress and mask sequence learning in complex tasks, leading to a form of contextual blindness characterized by impairments in the ability to use environmental cues to guide attention and anticipate future events. APPLICATION: These findings have implications for both skill acquisition and skilled performance in complex domains such as driving, aviation, manufacturing, and human-computer interaction.

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.

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.

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.

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.

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.

A conceptual map of invasion biology: Integrating hypotheses into a consensus network.

BACKGROUND AND AIMS: Since its emergence in the mid-20th century, invasion biology has matured into a productive research field addressing questions of fundamental and applied importance. Not only has the number of empirical studies increased through time, but also has the number of competing, overlapping and, in some cases, contradictory hypotheses about biological invasions. To make these contradictions and redundancies explicit, and to gain insight into the field's current theoretical structure, we developed and applied a Delphi approach to create a consensus network of 39 existing invasion hypotheses. RESULTS: The resulting network was analysed with a link-clustering algorithm that revealed five concept clusters (resource availability, biotic interaction, propagule, trait and Darwin's clusters) representing complementary areas in the theory of invasion biology. The network also displays hypotheses that link two or more clusters, called connecting hypotheses, which are important in determining network structure. The network indicates hypotheses that are logically linked either positively (77 connections of support) or negatively (that is, they contradict each other; 6 connections). SIGNIFICANCE: The network visually synthesizes how invasion biology's predominant hypotheses are conceptually related to each other, and thus, reveals an emergent structure - a conceptual map - that can serve as a navigation tool for scholars, practitioners and students, both inside and outside of the field of invasion biology, and guide the development of a more coherent foundation of theory. Additionally, the outlined approach can be more widely applied to create a conceptual map for the larger fields of ecology and biogeography.

Visual and Cognitive Demands of CarPlay, Android Auto, and Five Native Infotainment Systems.

OBJECTIVE: The present research compared and contrasted the workload associated with using in-vehicle information systems commonly available in five different automotive original equipment manufacturers (OEMs) with that of CarPlay and Android Auto when used in the same vehicles. BACKGROUND: A growing trend is to provide access to portable smartphone-based systems (e.g., CarPlay and Android Auto) that support an expansion of various in-vehicle infotainment system features and functions. METHOD/RESULTS: The study involved on-road testing of 24 participants in each configuration of five vehicles crossed with the three different infotainment systems: the embedded portion of the native OEM systems, CarPlay, and Android Auto. Our analysis found that workload was significantly greater for the embedded portion of the native OEM systems than for CarPlay and Android Auto. The strengths and weaknesses of each CarPlay and Android Auto traded off in such a way that the overall demand associated with using the two systems did not differ. CONCLUSION: CarPlay and Android Auto provided more functionality and resulted in lower levels of workload than the embedded portion of the native OEM infotainment systems. APPLICATION: Potential applications of this research include refinements to CarPlay and Android Auto to address variations in workload as a function of task type, the modality of interaction, and OEM implementation of the system.

Boom-bust dynamics in biological invasions: towards an improved application of the concept.

Boom-bust dynamics - the rise of a population to outbreak levels, followed by a dramatic decline - have been associated with biological invasions and offered as a reason not to manage troublesome invaders. However, boom-bust dynamics rarely have been critically defined, analyzed, or interpreted. Here, we define boom-bust dynamics and provide specific suggestions for improving the application of the boom-bust concept. Boom-bust dynamics can arise from many causes, some closely associated with invasions, but others occurring across a wide range of ecological settings, especially when environmental conditions are changing rapidly. As a result, it is difficult to infer cause or predict future trajectories merely by observing the dynamic. We use tests with simulated data to show that a common metric for detecting and describing boom-bust dynamics, decline from an observed peak to a subsequent trough, tends to severely overestimate the frequency and severity of busts, and should be used cautiously if at all. We review and test other metrics that are better suited to describe boom-bust dynamics. Understanding the frequency and importance of boom-bust dynamics requires empirical studies of large, representative, long-term data sets that use clear definitions of boom-bust, appropriate analytical methods, and careful interpretations.

SPIDER: A Framework for Understanding Driver Distraction.

OBJECTIVE: The objective was to identify key cognitive processes that are impaired when drivers divert attention from driving. BACKGROUND: Driver distraction is increasingly recognized as a significant source of injuries and fatalities on the roadway. METHOD/RESULTS: A "SPIDER" model is developed that identifies key cognitive processes that are impaired when drivers divert attention from driving. SPIDER is an acronym standing for scanning, predicting, identifying, decision making, and executing a response. CONCLUSION: When drivers engage in secondary activities unrelated to the task of driving, SPIDER-related processes are impaired, situation awareness is degraded, and the ability to safely operate a motor vehicle may be compromised. APPLICATION: The pattern of interference helps to illuminate the sources of driver distraction and may help guide the integration of new technology into the automobile.

Working memory's workload capacity.

We examined the role of dual-task interference in working memory using a novel dual two-back task that requires a redundant-target response (i.e., a response that neither the auditory nor the visual stimulus occurred two back versus a response that one or both occurred two back) on every trial. Comparisons with performance on single two-back trials (i.e., with only auditory or only visual stimuli) showed that dual-task demands reduced both speed and accuracy. Our task design enabled a novel application of Townsend and Nozawa's (Journal of Mathematical Psychology 39: 321-359, 1995) workload capacity measure, which revealed that the decrement in dual two-back performance was mediated by the sharing of a limited amount of processing capacity. Relative to most other single and dual n-back tasks, performance measures for our task were more reliable, due to the use of a small stimulus set that induced a high and constant level of proactive interference. For a version of our dual two-back task that minimized response bias, accuracy was also more strongly correlated with complex span than has been found for most other single and dual n-back tasks.

Driven to Distraction.

We address several themes that emerged in the commentaries related to our target article. First, we consider the relationship between cognitive distraction and crash risk. Second, we discuss the development of our cognitive distraction scale. Third, we weigh issues of self-regulation, appropriate baselines, and satisficing. Finally, we identify several areas where additional research is needed to refine our understanding of driver distraction and crash risk.

Assessing Cognitive Distraction in the Automobile.

OBJECTIVE: The objective was to establish a systematic framework for measuring and understanding cognitive distraction in the automobile. BACKGROUND: Driver distraction from secondary in-vehicle activities is increasingly recognized as a significant source of injuries and fatalities on the roadway. METHOD: Across three studies, participants completed eight in-vehicle tasks commonly performed by the driver of an automobile. Primary, secondary, subjective, and physiological measures were collected and integrated into a cognitive distraction scale. RESULTS: In-vehicle activities, such as listening to the radio or an audio book, were associated with a low level of cognitive workload; the conversation activities of talking to a passenger in the vehicle or conversing with a friend on a handheld or hands-free cell phone were associated with a moderate level of cognitive workload; and using a speech-to-text interfaced e-mail system involved a high level of cognitive workload. CONCLUSION: The research established that there are significant impairments to driving that stem from the diversion of attention from the task of operating a motor vehicle and that the impairments to driving are directly related to the cognitive workload of these in-vehicle activities. Moreover, the adoption of voice-based systems in the vehicle may have unintended consequences that adversely affect traffic safety. APPLICATION: These findings can be used to help inform scientifically based policies on driver distraction, particularly as they relate to cognitive distraction stemming from the diversion of attention to other concurrent activities in the vehicle.

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.

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).

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.

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.

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.

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.