The Effects of Increased Visual Information on Cognitive Workload in a Helicopter Simulator.

OBJECTIVE: To test the effects of enhanced display information ("symbology") on cognitive workload in a simulated helicopter environment, using the detection response task (DRT). BACKGROUND: Workload in highly demanding environments can be influenced by the amount of information given to the operator and consequently it is important to limit potential overload. METHODS: Participants (highly trained military pilots) completed simulated helicopter flights, which varied in visual conditions and the amount of information given. During these flights, participants also completed a DRT as a measure of cognitive workload. RESULTS: With more visual information available, pilots' landing accuracy was improved across environmental conditions. The DRT is sensitive to changes in cognitive workload, with workload differences shown between environmental conditions. Increasing symbology appeared to have a minor effect on workload, with an interaction effect of symbology and environmental condition showing that symbology appeared to moderate workload. CONCLUSION: The DRT is a useful workload measure in simulated helicopter settings. The level of symbology-moderated pilot workload. The increased level of symbology appeared to assist pilots' flight behavior and landing ability. Results indicate that increased symbology has benefits in more difficult scenarios. APPLICATIONS: The DRT is an easily implemented and effective measure of cognitive workload in a variety of settings. In the current experiment, the DRT captures the increased workload induced by varying the environmental conditions, and provides evidence for the use of increased symbology to assist pilots.

A Broader Application of the Detection Response Task to Cognitive Tasks and Online Environments.

OBJECTIVE: The present research applied a well-established measure of cognitive workload in driving literature to an in-lab paradigm. We then extended this by comparing the in-lab version of the task to an online version. BACKGROUND: The accurate and objective measurement of cognitive workload is important in many aspects of psychological research. The detection response task (DRT) is a well-validated method for measuring cognitive workload that has been used extensively in applied tasks, for example, to investigate the effects of phone usage or passenger conversation on driving, but has been used sparingly outside of this field. METHOD: The study investigated whether the DRT could be used to measure cognitive workload in tasks more commonly used in experimental cognitive psychology and whether this application could be extended to online environments. We had participants perform a multiple object tracking (MOT) task while simultaneously performing a DRT. We manipulated the cognitive load of the MOT task by changing the number of dots to be tracked. RESULTS: Measurements from the DRT were sensitive to changes in the cognitive load, establishing the efficacy of the DRT for experimental cognitive tasks in lab-based situations. This sensitivity continued when applied to an online environment (our code for the online DRT implementation is freely available at https://osf.io/dc39s/), though to a reduced extent compared to the in-lab situation. CONCLUSION: The MOT task provides an effective manipulation of cognitive workload. The DRT is sensitive to changes in workload across a range of settings and is suitable to use outside of driving scenarios, as well as via online delivery. APPLICATION: Methodology shows how the DRT could be used to measure sources of cognitive workload in a range of human factors contexts.

Mixed messages: Assessing interactions between portion-size and energy-density perceptions in different weight and sex groups.

INTRODUCTION: Food portion size (PS) and energy density (ED) are the two primary determinants of total energy intake. While emerging neuroscientific data indicate judgments of PS and ED involve distinct brain regions, it is not understood how these judgements interact with each other to influence an individual's energy consumption. The present study investigated these cognitive interactions against body-mass-index (BMI) and sex. METHODS: We tested 70 participants (including 34 overweight individuals) for cognitive biases when judging PS and ED, using the Garner task paradigm. Participants were asked to discriminate PS and ED, following pre-determined cognitive rules. Reaction time and correctness of their responses were recorded and analysed against the testing conditions across sexes and BMI groups. RESULTS: We detected a significant 3-way interaction between BMI, Task, and Condition (F(3, 67) = 4.1, p = 0.047, ƞ2 = 0.06). Post-hoc tests suggested that, in the PS task, both weight groups experienced the Garner Interference effect introduced by variations of ED. That is, when making judgments concerning PS, participants were unable to ignore information relating to ED. Results from the ED task differed across weight groups, with only the overweight group being susceptible to the Garner Interference introduced by variations of PS. Additionally, both Sex and BMI were significant factors moderating reaction time when judging PS. Significantly longer reaction time was observed in female versus male comparisons, and for overweight versus healthy-weight participants (p < 0.05). CONCLUSION: Overall, the results confirmed cognitive interactions involving PS and ED, although these interactions were asymmetric across BMI groups. These findings provide new insights into the cognitive processes underpinning individual dietary decision-making, and are potentially important for developing targeted intervention strategies for effective management of unhealthy eating behaviour.

Breaking the rules in perceptual information integration.

We develop a broad theoretical framework for modelling difficult perceptual information integration tasks under different decision rules. The framework allows us to compare coactive architectures, which combine information before it enters the decision process, with parallel architectures, where logical rules combine independent decisions made about each perceptual source. For both architectures we test the novel hypothesis that participants break the decision rules on some trials, making a response based on only one stimulus even though task instructions require them to consider both. Our models take account of not only the decisions made but also the distribution of the time that it takes to make them, providing an account of speed-accuracy tradeoffs and response biases occurring when one response is required more often than another. We also test a second novel hypothesis, that the nature of the decision rule changes the evidence on which choices are based. We apply the models to data from a perceptual integration task with near threshold stimuli under two different decision rules. The coactive architecture was clearly rejected in favor of logical-rules. The logical-rule models were shown to provide an accurate account of all aspects of the data, but only when they allow for response bias and the possibility for subjects to break those rules. We discuss how our framework can be applied more broadly, and its relationship to Townsend and Nozawa's (1995) Systems-Factorial Technology.

Set size slope still does not distinguish parallel from serial search.

Much of the evidence for theories in visual search (including Hulleman & Olivers' [H&O's]) comes from inferences made using changes in mean RT as a function of the number of items in a display. We have known for more than 40 years that these inferences are based on flawed reasoning and obscured by model mimicry. Here we describe a method that avoids these problems.

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.

Measuring single-item identification efficiencies for letters and 3-D objects.

Identification thresholds and the corresponding efficiencies (ideal/human thresholds) are typically computed by collapsing data across an entire stimulus set within a given task in order to obtain a "multiple-item" summary measure of information use. However, some individual stimuli may be processed more efficiently than others, and such differences are not captured by conventional multiple-item threshold measurements. Here, we develop and present a technique for measuring "single-item" identification efficiencies. The resulting measure describes the ability of the human observer to make use of the information provided by a single stimulus item within the context of the larger set of stimuli. We applied this technique to the identification of 3-D rendered objects (Exp. 1) and Roman alphabet letters (Exp. 2). Our results showed that efficiency can vary markedly across stimuli within a given task, demonstrating that single-item efficiency measures can reveal important information that is lost by conventional multiple-item efficiency measures.

Efficiency in redundancy.

In engineering, redundancy is the duplication of vital systems for use in the event of failure. In studies of human cognition, redundancy often refers to the duplication of the signal. Scores of studies have shown the salutary effects of a combined auditory and visual signal over single modality, the advantage of processing complete faces over facial features, and more recently the advantage of two observers over one. But what if the signal (or the number of observers) is fixed and cannot be altered or augmented? Can people improve the efficiency of information processing by recruiting an additional, redundant system? Here we demonstrate that recruiting a second redundant system can, under reasonable assumptions about human capacity, result in improved performance. Recruiting a second redundant system may come with a higher energy cost, but may be worthwhile in high-stakes situations where processing information accurately is crucial.

In human-machine trust, humans rely on a simple averaging strategy.

With the growing role of artificial intelligence (AI) in our lives, attention is increasingly turning to the way that humans and AI work together. A key aspect of human-AI collaboration is how people integrate judgements or recommendations from machine agents, when they differ from their own judgements. We investigated trust in human-machine teaming using a perceptual judgement task based on the judge-advisor system. Participants ( n = 89 ) estimated a perceptual quantity, then received a recommendation from a machine agent. The participants then made a second response which combined their first estimate and the machine's recommendation. The degree to which participants shifted their second response in the direction of the recommendations provided a measure of their trust in the machine agent. We analysed the role of advice distance in people's willingness to change their judgements. When a recommendation falls a long way from their initial judgement, do people come to doubt their own judgement, trusting the recommendation more, or do they doubt the machine agent, trusting the recommendation less? We found that although some participants exhibited these behaviours, the most common response was neither of these tendencies, and a simple model based on averaging accounted best for participants' trust behaviour. We discuss implications for theories of trust, and human-machine teaming.

Prior beliefs and the interpretation of scientific results.

How do prior beliefs affect the interpretation of scientific results? I discuss a hypothetical scenario where researchers publish results that could either support a theory they believe in, or refute that theory, and ask if the two instances carry the same weight. More colloquially, I ask if we should overweigh scientific results supporting a given theory and reported by a researcher, or a team, that initially did not support that theory. I illustrate the challenge using two examples from psychology: evidence accumulation models, and extra sensory perception.

Human Performance in Competitive and Collaborative Human-Machine Teams.

In the modern world, many important tasks have become too complex for a single unaided individual to manage. Teams conduct some safety-critical tasks to improve task performance and minimize the risk of error. These teams have traditionally consisted of human operators, yet, nowadays, artificial intelligence and machine systems are incorporated into team environments to improve performance and capacity. We used a computerized task modeled after a classic arcade game to investigate the performance of human-machine and human-human teams. We manipulated the group conditions between team members; sometimes, they were instructed to collaborate, compete, or work separately. We evaluated players' performance in the main task (gameplay) and, in post hoc analyses, participant behavioral patterns to inform group strategies. We compared game performance between team types (human-human vs. human-machine) and group conditions (competitive, collaborative, independent). Adapting workload capacity analysis to human-machine teams, we found performance under both team types and all group conditions suffered a performance efficiency cost. However, we observed a reduced cost in collaborative over competitive teams within human-human pairings, but this effect was diminished when playing with a machine partner. The implications of workload capacity analysis as a powerful tool for human-machine team performance measurement are discussed.

Extending systems factorial technology to errored responses.

Systems factorial technology (SFT) is a theoretically derived methodology that allows for strong inferences to be made about underlying processing architectures (e.g., whether processing occurs in a pooled, coactive fashion or in serial or in parallel). Measures of mental architecture using SFT have been restricted to the use of error-free response times (RTs). In this article, through formal proofs and demonstrations, we extended the measure of architecture, the survivor interaction contrast (SIC), to RTs conditioned on whether they are correct or incorrect. We show that so long as an ordering relation (between stimulus conditions of different difficulty) is preserved, we learn that the canonical SIC predictions result when exhaustive processing is necessary and sufficient for a response. We further prove that this ordering relation holds for the popular Wiener diffusion model for both correct and error RTs but fails under some classes of a Poisson counter model, which affords a strong potential experimental test of the latter class versus the others. Our exploration also serves to point to the importance of detailed studies of how errors are made in perceptual and cognitive tasks. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Unraveling the Physiological Correlates of Mental Workload Variations in Tracking and Collision Prediction Tasks.

Modern work environments have extensive interactions with technology and greater cognitive complexity of the tasks, which results in human operators experiencing increased mental workload. Air traffic control operators routinely work in such complex environments, and we designed tracking and collision prediction tasks to emulate their elementary tasks. The physiological response to the workload variations in these tasks was elucidated to untangle the impact of workload variations experienced by operators. Electroencephalogram (EEG), eye activity, and heart rate variability (HRV) data were recorded from 24 participants performing tracking and collision prediction tasks with three levels of difficulty. Our findings indicate that variations in task load in both these tasks are sensitively reflected in EEG, eye activity and HRV data. Multiple regression results also show that operators' performance in both tasks can be predicted using the corresponding EEG, eye activity and HRV data. The results also demonstrate that the brain dynamics during each of these tasks can be estimated from the corresponding eye activity, HRV and performance data. Furthermore, the markedly distinct neurometrics of workload variations in the tracking and collision prediction tasks indicate that neurometrics can provide insights on the type of mental workload. These findings have applicability to the design of future mental workload adaptive systems that integrate neurometrics in deciding not just "when" but also "what" to adapt. Our study provides compelling evidence in the viability of developing intelligent closed-loop mental workload adaptive systems that ensure efficiency and safety in complex work environments.

Using Past and Present Indicators of Human Workload to Explain Variance in Human Performance.

Cognitive workload is assumed to influence performance due to resource competition. However, there is a lack of evidence for a direct relationship between changes in workload within an individual over time and changes in that individual's performance. We collected performance data using a multiple object-tracking task in which we measured workload objectively in real-time using a modified detection response task. Using a multi-level Bayesian model controlling for task difficulty and past performance, we found strong evidence that workload both during and preceding a tracking trial was predictive of performance, such that higher workload led to poorer performance. These negative workload-performance relationships were remarkably consistent across individuals. Importantly, we demonstrate that fluctuations in workload independent from the task demands accounted for significant performance variation. The outcomes have implications for designing real-time adaptive systems to proactively mitigate human performance decrements, but also highlight the pervasive influence of cognitive workload more generally.

A show about nothing: No-signal processes in systems factorial technology.

Systems Factorial Technology (SFT) is a popular framework for that has been used to investigate processing capacity across many psychological domains over the past 25+ years. To date, it had been assumed that no processing resources are used for sources in which no signal has been presented (i.e., in a location that can contain a signal but does not on a given trial). Hence, response times are purely driven by the signal-containing location or locations. This assumption is critical to the underlying mathematics of the capacity coefficient measure of SFT. In this article, we show that stimulus locations influence response times even when they contain no signal, and that this influence has repercussions for the interpretation of processing capacity under the SFT framework, particularly in conjunctive (AND) tasks-where positive responses require detection of signals in multiple locations. We propose a modification to the AND task requiring participants to fully identify both target locations on all trials. This modification allows a new coefficient to be derived. We apply the new coefficient to novel experimental data and resolve a previously reported empirical paradox, where observed capacity was limited in an OR detection task but super capacity in an AND detection task. Hence, previously reported differences in processing capacity between OR and AND task designs are likely to have been spurious. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Gene Deletion and Sleep Depletion: Exploring the Relationship Between Sleep and Affect in 22q11.2 Deletion Syndrome.

22q11.2 deletion syndrome (22q11DS) is a neurodevelopmental disorder caused by a microdeletion on the long arm of chromosome 22. Sleep problems have been reported in this population, and psychiatric disorders and affect dysregulation are common to the behavioral phenotype of 22q11DS. Sleep and affect have been consistently linked across multiple studies, yet despite this very little research has investigated sleep problems in 22q11DS, or the link between sleep and affect in this population. The Experience Sampling Method was used to track daily reports of sleep quality and affect in a total of 29 individuals with 22q11DS and 21 control subjects. Measurements were recorded during a 6-day period using an electronic device that prompted daily response with audio cues. Participants with 22q11DS were found to experience a longer sleep onset latency and a greater amount, and duration, of night wakings compared with control subjects. Despite this, no significant between-group difference was found for subjective sleep quality. 22q11DS participants reported more experiences of negative affect and less positive affect than control subjects. A bidirectional relationship was found between sleep measures and affect. Sleep problems can cause a wide range of negative health effects, and individuals with 22q11DS are particularly vulnerable to deficits of sleep. To ensure high standards of care, healthcare providers should be aware of the possibility and impact of sleep problems in this population.

The workload capacity of semantic search in convergent thinking.

The present study used Systems Factorial Technology (Townsend & Nozawa, 1995) to investigate how people combine dual cues in semantic memory search. Our aims were (a) to understand how cues interact during the process of semantic search in convergent thinking and (b) to determine how workload capacity (i.e. cue-processing efficiency) is related to search performance. In two experiments, participants completed a typical convergent thinking test and a word production task. The results revealed that: (a) collective evidence supports similar patterns in cue-combination strategy despite individual differences in workload capacity, and (b) there exists a negative correlation between workload capacity and performance on convergent thinking test. A potential explanation is that, for the creative individual, loading many candidate answers leads to consumption of substantial processing resources that obtains as low workload capacity but also allows creative individuals to switch more easily from one candidate to another so that there is a higher probability of successfully producing an answer within a limited time. Our results further imply that workload capacity is a significant factor for the semantic search process in convergent thinking and provides new insight on the model of semantic search and creativity. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

What do cows drink? A systems factorial technology account of processing architecture in memory intersection problems.

It has long been known that cues can be used to improve performance on memory recall tasks. There is evidence to suggest additional cues provide further benefit, presumably by narrowing the search space. Problems that require integration of two or more cues, alternately referred to as memory intersections or multiply constrained memory problems, could be approached using several strategies, namely serial or parallel consideration of cues. The type of strategy implicated is essential information for the development of theories of memory, yet evidence to date has been inconclusive. Using a novel application of the powerful Systems Factorial Technology (Townsend & Nozawa, 1995) we find strong evidence that participants use two cues in parallel in free recall tasks - a finding that contradicts two recent publications in this area. We then provide evidence from a related recognition task showing that while most participants also use a parallel strategy in that paradigm, a reliable subset of participants used a serial strategy. Our findings suggest a theoretically meaningful distinction between participants strategies in recall and recognition based intersection memory tasks, and also highlight the importance of tightly controlled methodological and analytic frameworks to overcome issues of serial/parallel model mimicry.

Going, going, gone: competitive decision-making in Dutch auctions.

In a Dutch auction, an item is offered for sale at a set maximum price. The price is then gradually lowered over a fixed interval of time until a bid is made, securing the item for the bidder at the current price. Bidders must trade-off between certainty and price: bid early to secure the item and you pay a premium; bid later at a lower price but risk losing to another bidder. These properties of Dutch auctions provide new opportunities to study competitive decision-making in a group setting. We developed a novel computerised Dutch auction platform and conducted a set of experiments manipulating volatility (fixed vs varied number of items for sale) and price reduction interval rate (step-rate). Triplets of participants ([Formula: see text]) competed with hypothetical funds against each other. We report null effects of step-rate and volatility on bidding behaviour. We developed a novel adaptation of prospect theory to account for group bidding behaviour by balancing certainty and subjective expected utility. We show the model is sensitive to variation in auction starting price and can predict the associated changes in group bid prices that were observed in our data.

How is multi-tasking different from increased difficulty?

With the advancement of technologies like in-car navigation and smartphones, concerns around how cognitive functioning is influenced by "workload" are increasingly prevalent. Research shows that spreading effort across multiple tasks can impair cognitive abilities through an overuse of resources, and that similar overload effects arise in difficult single-task paradigms. We developed a novel lab-based extension of the Detection Response Task, which measures workload, and paired it with a Multiple Object Tracking Task to manipulate cognitive load. Load was manipulated either by changing within-task difficulty or by the addition of an extra task. Using quantitative cognitive modelling we showed that these manipulations cause similar cognitive impairments through diminished processing rates, but that the introduction of a second task tends to invoke more cautious response strategies that do not occur when only difficulty changes. We conclude that more prudence should be exercised when directly comparing multi-tasking and difficulty-based workload impairments, particularly when relying on measures of central tendency.