Search

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.

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.

The aim of this study was to explore the potential association between (i) the technology features of the applied cognitive technology (ACT) used to support employment-related outcomes for people with intellectual and developmental disabilities and (ii) the cognitive functions. The WHO International Classification of Functioning, Disability and Health (ICF) was used to categorize the cognitive functions. The researchers of the 41 papers included in previous meta-analyses on the same topic were invited to participate in the study. An online survey was conducted. Correspondence analysis was employed to analyze the aforementioned association. Attention, memory, and higher-level cognitive functions were primarily associated with the majority of the ACT’s technology features. The results demonstrated a main distinct cluster including these three dominant cognitive functions and predominantly all the “output” categories of technology features. Another smaller but distinct cluster including mental function of sequencing complex movements and “touch screen/touchpad” category of technology features was also demonstrated. In line with previous studies, the largest proportion of ACTs have been used to assist primarily the aforementioned three cognitive functions. The new classification of ACT’s technology features based on cognitive function in this study can promote a common language and shared understanding for the prescription of 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).

Adaptive human behaviour requires cognitive control ‐ the monitoring of actions and performance, to regulate and coordinate ongoing behaviour. Major depression is associated with neuropsychological...

Cognitive load from secondary tasks is a source of distraction causing injuries and fatalities on the roadway. The Detection Response Task (DRT) is an international standard for assessing cognitive load on drivers' attention that can be performed as a secondary task with little to no measurable effect on the primary driving task. We investigated whether decrements in DRT performance were related to the rate of information processing, levels of response caution, or the non-decision processing of drivers. We had pairs of participants take part in the DRT while performing a simulated driving task, manipulated cognitive load via the conversation between driver and passenger, and observed associated slowing in DRT response time. Fits of the single-bound diffusion model indicated that slowing was mediated by an increase in response caution. We propose the novel hypothesis that, rather than the DRT's sensitivity to cognitive load being a direct result of a loss of information processing capacity to other tasks, it is an indirect result of a general tendency to be more cautious when making responses in more demanding situations.

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.

In a Stroop task, participants can be presented with a color name printed in color and need to classify the print color while ignoring the word. The Stroop effect is typically calculated as the difference in mean response time (RT) between congruent (e.g., the word RED printed in red) and incongruent (GREEN in red) trials. Delta plots compare not just mean performance, but the entire RT distributions of congruent and incongruent conditions. However, both mean RT and delta plots have some limitations. Arm-reaching trajectories allow a more continuous measure for assessing the time course of the Stroop effect. We compared arm movements to congruent and incongruent stimuli in a standard Stroop task and a control task that encourages processing of each and every word. The Stroop effect emerged over time in the control task, but not in the standard Stroop, suggesting words may be processed differently in the two tasks.

The detection response task (DRT) is a measure of workload that can assess the cognitive demands of real-world multitasking. It can be configured to present simple stimuli of several modalities, including auditory and visual signals. However, the concurrent presentation of the DRT stimuli alongside another task could cause dual-task interference, and the extent of this interference could be different based on the DRT’s configuration. It is necessary to consider the characteristics of the DRT stimulus, such as modality, to identify a minimally intrusive stimulus. Fifty participants completed a computer-based one-dimensional tracking task alongside a DRT. The DRT’s stimuli varied in their modality (visual/auditory), while the tracking task varied in its workload demand (low/high). DRT performance was modelled using a shifted-Wald model, while the tracking task was assessed using systems factorial technology (SFT), a non-parametric methodology capable of capturing a cognitive system’s workload capacity. To allow the latter’s use, we developed a method of transforming continuous tracking data into a discrete form akin to response times. Analysis of DRT data found little evidence that the DRT’s modality affected processing efficiency, while SFT analysis found limited-capacity processing on the tracking task across both DRT modalities. These findings suggest DRT modality had little effect on the level of interference between the two tasks.

Best practice in understanding and caring for people with advanced Alzheimer’s disease presents extraordinary challenges. Their severe and deteriorating cognitive impairments are such that carers find progressive difficulty in authentically ascertaining and responding to interests, preferences, and needs. Deep assessment, a novel multifaceted framework drawn from research into the experiences of others with severe cognitive impairments, has potential to empower carers and other support professionals to develop an enhanced understanding of people with advanced Alzheimer’s disease and so deliver better calibrated care in attempts to maximize quality of life. Deep assessment uses a combination of techniques, namely, Behaviour State Observation, Triangulated Proxy Reporting, and Startle Reflex Modulation Measurement, to deliver a comprehensive and deep assessment of the inner states (awareness, preferences, likes, and dislikes) of people who cannot reliably self-report. This paper explains deep assessment and its current applications. It then suggests how it can be applied to people with advanced Alzheimer’s disease to develop others’ understanding of their inner states and to help improve their quality of life. An illustrative hypothetical vignette is used to amplify this framework. We discuss the potential utility and efficacy of this technique for this population and we also propose other human conditions that may benefit from research using a deep assessment approach.

The question of cognitive architecture-how cognitive processes are temporally organized-has arisen in many areas of psychology. This question has proved difficult to answer, with many proposed solutions turning out to be spurious. Systems factorial technology (TownsendNozawa, 1995) provided the first rigorous empirical and analytical method of identifying cognitive architecture, using the survivor interaction contrast (SIC) to determine when people are using multiple sources of information in parallel or in series. Although the SIC is based on rigorous nonparametric mathematical modeling of response time distributions, for many years inference about cognitive architecture has relied solely on visual assessment. Houpt and Townsend (2012) recently introduced null hypothesis significance tests, and here we develop both parametric and nonparametric (encompassing prior) Bayesian inference. We show that the Bayesian approaches can have considerable advantages. (PsycINFO Database Record

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 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.

Like many species, humans can perform non-verbal estimates of quantity through our innate approximate number system. However, the cognitive mechanisms that govern how we compare these estimates are not well understood. Little research has addressed how the human estimation-system evaluates multiple quantities, and fewer studies have considered the cost to cognitive workload when undertaking such a task. Here, we provide a novel application of Systems Factorial Technology (SFT; Townsend and Nozawa, 1995) to a comparative estimation task. Across a series of four experiments, we assess whether quantities i.e. non-overlapping red and blue discs, are estimated simultaneously (in parallel) or sequentially (in serial), and under what restrictions to cognitive workload. Our findings reveal that two item-sets may be estimated simultaneously through a parallel estimation system, under severe restrictions to cognitive workload capacity. These restrictions were so severe, as to make the parallel estimation of two quantities less efficient than the estimation of each quantity in succession. While the estimation of a single item-set may be colloquially considered an effortless process, our results show that the estimation of multiple item-sets is a rather demanding feat.

Systems Factorial Technology (SFT; Townsend & Nozawa, 1995 ) is a powerful framework that has allowed researchers to investigate the basic properties of cognitive processing systems for the past 20 years. Based on comprehensive mathematical underpinnings, SFT has been used to successfully investigate processing in simple detection, memory search, Stroop tasks, word processing and other domains through unique Response Time (RT) based analyses. SFT is thus undeniably one of the most important contributions to the field of mathematical psychology. Although SFT is very powerful, it is, by definition, intrinsically linked to the research design that underpins its mathematics. Therefore, SFT cannot currently be applied in other frameworks, such as unique identification of signals from a range of response options. In this chapter we explore another powerful approach, General Recognition Theory ( Ashby & Townsend, 1986 ), that can be applied in such tasks. Specifically, we investigate the utility of applying GRT to ask similar questions that researchers may pose under SFT. We present data from three new experiments, based on similar SFT experiments, but focusing on accuracy measures and GRT analyses. We also provide a comprehensive set of simulation results to investigate the potential link between basic cognitive processing properties in SFT and GRT. We conclude by highlighting the need for future research to further combine both accuracy and RT approaches to allow a more comprehensive account of cognitive processing.

In early studies employing the SFT, the stimuli were simple visual signals, mainly dots, lines, or letters of the alphabet. Although this feature facilitated focusing on theory development, it has reduced the impact of SFT on mainstream cognitive science. The goal of this chapter is to reconnect the SFT to cognitive psychology via an SFT-guided examination of four major phenomena of current cognitive science: the Stroop and Garner effects in attention, the Size-Congruity effect in numerical cognition, and the Redundant-Target effect in speeded signal detection. We show that, in each case, the SFT analysis led to novel insights, reformulating old problems and challenging established theories.

The emotional Stroop effect (ESE) is the result of longer naming latencies to ink colors of emotion words than to ink colors of neutral words. The difference shows that people are affected by the emotional content conveyed by the carrier words even though they are irrelevant to the color-naming task at hand. The ESE has been widely deployed with patient populations, as well as with non-selected populations, because the emotion words can be selected to match the tested pathology. The ESE is a powerful tool, yet it is vulnerable to various threats to its validity. This report refers to potential sources of confounding and includes a modal experiment that provides the means to control for them. The most prevalent threat to the validity of existing ESE studies is sustained effects and habituation wrought about by repeated exposure to emotion stimuli. Consequently, the order of exposure to emotion and neutral stimuli is of utmost importance. We show that in the standard design, only one specific order produces the ESE.

Does processing more than one stimulus concurrently impede or facilitate performance relative to processing just one stimulus? This fundamental question about workload capacity was surprisingly difficult to address empirically until Townsend and Nozawa (1995) developed a set of nonparametric analyses called systems factorial technology. We develop an alternative parametric approach based on the linear ballistic accumulator decision model (Brown & Heathcote, 2008), which uses the model's parameter estimates to measure processing capacity. We show that these two methods have complementary strengths, and that, in a data set where participants varied greatly in capacity, the two approaches provide converging evidence.

Systems factorial technology (SFT) is a theory-driven set of methodologies oriented toward identification of basic mechanisms, such as parallel versus serial processing, of perception and cognition. Studies employing SFT in visual search with small display sizes have repeatedly shown decisive evidence for parallel processing. The first strong evidence for serial processing was recently found in short-term memory search, using target-distractor (T-D) similarity as a key experimental variable (Townsend & Fific, 2004). One of the major goals of the present study was to employ T-D similarity in visual search to learn whether this mode of manipulating processing speed would affect the parallel versus serial issue in that domain. The result was a surprising and regular departure from ordinary parallel or serial processing. The most plausible account at present relies on the notion of positively interacting parallel channels.

In the redundant target effect, participants respond faster with two (redundant) targets. We compared the magnitude of this effect in younger and older adults, with and without distractors, in a simple visual-detection task. We employed additional measures that allow non-parametric assessment of performance (Townsend's capacity coefficient) and parametric estimates (Linear Ballistic Accumulator model). Older participants' latencies were slower, especially in the presence of distractors, and their calculated capacity indicators increased with distractors. Parametric estimates indicated that these increases were generated by the older adults' increased difficulty in inhibiting the distractors, and not the results of either improved detection of redundant-targets, or of a generalized slowing of processing.