High Cognitive Load Research Articles

Software framework concept with visual programming and digital twin for intuitive process creation with multiple robotic systems

With the progressive digitalization in industrial manufacturing, the usage of complex robotic systems in both intralogistics and production is expected to increase. This proposes a challenge for planners and shop floor workers, as programming and interacting with these various systems leads to a high cognitive load. Especially the broad range of different manufacturer specific software leads to a number of problems, e.g. the program-synchronization between different systems and the often necessary workshops for workers. These problems can lead to inefficient programming and planning operations, bad worker satisfaction and human errors. In this paper, we present a modular, system agnostic and human centered software framework that unifies the programming of different systems, to enable centralized and intuitive system programming for non-expert operators. Our software framework utilizes visual programming concepts together with an integrated digital twin of the factory and a novel graph-based programming interface. We explain our concept in detail and describe our validation through integration into a realistic industrial setup with three different systems. In addition, we provide an evaluation of our concept's usability with an experimental user study and discuss the results of the study and the software implementation. Our study results show that even non-technical users are able to use our software after a brief introduction to create complex processes that involve multiple machines working in parallel. All users reported high usability and expert users reported that the visual process editor has enough features to create processes for industrial applications. Finally, we conclude this paper by providing an outlook on future work and use-cases of our software.

Individual interest, self‐regulation, and self‐directed language learning with technology beyond the classroom

AbstractIndividual interest and self‐regulation are two pillars of self‐directed learning. Despite empirical evidence on the interaction between the two with respect to academic achievement, few studies have explored how individual interest and self‐regulation might interact and relate to self‐directed informal learning. This study surveyed 322 university students on self‐regulation and two interest constructs (interest in learning English and interest in pursuing personal interest in English), and tested how these factors related to their engagement in self‐directed use of technology for English learning beyond the classroom. Structural equation modelling analysis revealed that despite both being significant determinants, interest factors, and self‐regulation were associated differently with various types of self‐directed technological activities (instruction‐, information‐, entertainment‐ and socialization‐oriented activities). Self‐regulation was predictive of instruction‐, information‐ and socialization‐oriented activities, which have high cognitive load and require effort management for second‐language learners. Interest in English learning was consistently a significant predictor of all four types of technological activities. Interest in pursuing personal interest in English played a significant role in information‐ and entertainment‐oriented technological activities. The findings recommend greater attention to individual interest when promoting self‐directed informal learning. The findings further suggest adopting a differentiated approach to bolstering self‐directed learning for different purposes. Practitioner notesWhat is already known about this topic Self‐regulation is important to self‐directed learning. Subject‐matter interest and self‐regulation interplay to influence academic performance in formal learning contexts. What this paper adds Interest and self‐regulation interplayed to shape self‐direction in informal learning contexts. Self‐regulation was predictive of instruction‐, information‐ and socialization‐oriented activities. Interest factors added additional explanation power on self‐directed technological activities. Both subject‐matter interest and the integration of personal interest with subject learning were significant determinants. The integration of personal interest with subject learning mediated the influence of subject‐matter interest. Implications for practice and/or policy Educational interventions need to work simultaneously on both interest and self‐regulation to bolster self‐directed learning. Educators need to address different factors when boosting different types of technological activities. A relative stance needs to be taken since self‐regulation might play a less significant role in less taxing technological activities. It is important to deliberately integrate students' personal interests into English learning and help students perceive and act on the integration.

The Effect of Implementation Intentions on Prospective Memory Commission Errors under Different Cognitive Loads.

Prospective memory (PM) refers to the ability to remember to perform a planned event or activity at a specific time or situation in the future. Implementation intentions can promote a connection between PM cues and intended actions, thus improving an individual's PM performance. However, this simple and effective encoding strategy may also have negative effects. For example, an implementation intention may result in PM commission errors that occur when an individual makes a false PM response to repeated PM cues that are no longer relevant as the PM task has been completed. Existing studies have explored the effect of implementation intentions on PM commission errors under low cognitive load. However, the role of implementation intentions in promoting linkages between PM cues and actions tends to disintegrate under high cognitive loads. Therefore, this study aimed to explore the effect of implementation intentions on PM commission errors under different cognitive load conditions. In this study, 58 college students participated in a mixed experimental design of 2 (encoding methods: implementation intention, standard) × 2 (cognitive load conditions: low, high). The results showed that implementation intentions promoted PM commission errors under the low-cognitive-load condition only, and there was no difference in the performance of ongoing tasks between the implementation intention encoding and the standard encoding conditions. However, individuals in the implementation intention condition reacted more slowly when encountering previous PM cues. The results suggest that the effect of implementation intentions on PM commission errors relies upon automated processing as a whole. However, individuals in the implementation intention condition required more attentional resources to suppress the no-longer-relevant intended actions when previous PM cues appeared, supporting the dual-mechanism theory.

Indoor CO2 monitoring in a surgical intensive care unit under visitation restrictions during the COVID-19 pandemic.

Indoor CO2 concentration is an important metric of indoor air quality (IAQ). The dynamic temporal pattern of CO2 levels in intensive care units (ICUs), where healthcare providers experience high cognitive load and occupant numbers are frequently changing, has not been comprehensively characterized. We attempted to describe the dynamic change in CO2 levels in the ICU using an Internet of Things-based (IoT-based) monitoring system. Specifically, given that the COVID-19 pandemic makes hospital visitation restrictions necessary worldwide, this study aimed to appraise the impact of visitation restrictions on CO2 levels in the ICU. Since February 2020, an IoT-based intelligent indoor environment monitoring system has been implemented in a 24-bed university hospital ICU, which is symmetrically divided into areas A and B. One sensor was placed at the workstation of each area for continuous monitoring. The data of CO2 and other pollutants (e.g., PM2.5) measured under standard and restricted visitation policies during the COVID-19 pandemic were retrieved for analysis. Additionally, the CO2 levels were compared between workdays and non-working days and between areas A and B. The median CO2 level (interquartile range [IQR]) was 616 (524-682) ppm, and only 979 (0.34%) data points obtained in area A during standard visitation were ≥ 1,000 ppm. The CO2 concentrations were significantly lower during restricted visitation (median [IQR]: 576 [556-596] ppm) than during standard visitation (628 [602-663] ppm; p < 0.001). The PM2.5 concentrations were significantly lower during restricted visitation (median [IQR]: 1 [0-1] μg/m3) than during standard visitation (2 [1-3] μg/m3; p < 0.001). The daily CO2 and PM2.5 levels were relatively low at night and elevated as the occupant number increased during clinical handover and visitation. The CO2 concentrations were significantly higher in area A (median [IQR]: 681 [653-712] ppm) than in area B (524 [504-547] ppm; p < 0.001). The CO2 concentrations were significantly lower on non-working days (median [IQR]: 606 [587-671] ppm) than on workdays (583 [573-600] ppm; p < 0.001). Our study suggests that visitation restrictions during the COVID-19 pandemic may affect CO2 levels in the ICU. Implantation of the IoT-based IAQ sensing network system may facilitate the monitoring of indoor CO2 levels.

Involving Health Care Professionals in the Development of Electronic Health Records: Scoping Review.

Electronic health records (EHRs) are a promising approach to document and map (complex) health information gathered in health care worldwide. However, possible unintended consequences during use, which can occur owing to low usability or the lack of adaption to existing workflows (eg, high cognitive load), may pose a challenge. To prevent this, the involvement of users in the development of EHRs is crucial and growing. Overall, involvement is designed to be very multifaceted, for example, in terms of the timing, frequency, or even methods used to capture user preferences. Setting, users and their needs, and the context and practice of health care must be considered in the design and subsequent implementation of EHRs. Many different approaches to user involvement exist, each requiring a variety of methodological choices. The aim of the study was to provide an overview of the existing forms of user involvement and the circumstances they need and to provide support for the planning of new involvement processes. We conducted a scoping review to provide a database for future projects on which design of inclusion is worthwhile and to show the diversity of reporting. Using a very broad search string, we searched the PubMed, CINAHL, and Scopus databases. In addition, we searched Google Scholar. Hits were screened according to scoping review methodology and then examined, focusing on methods and materials, participants, frequency and design of the development, and competencies of the researchers involved. In total, 70 articles were included in the final analysis. There was a wide range of methods of involvement. Physicians and nurses were the most frequently included groups and, in most cases, were involved only once in the process. The approach of involvement (eg, co-design) was not specified in most of the studies (44/70, 63%). Further qualitative deficiencies in the reporting were evident in the presentation of the competences of members of the research and development teams. Think-aloud sessions, interviews, and prototypes were frequently used. This review provides insights into the diversity of health care professionals' involvement in the development of EHRs. It provides an overview of the different approaches in various fields of health care. However, it also shows the necessity of considering quality standards in the development of EHRs together with future users and the need for reporting this in future studies.

Working memory for time intervals: Another manifestation of the central tendency effect.

The relationship between working memory and time perception has been typically investigated using dual-task paradigms (e.g., testing timing performance during a concurrent task). To our knowledge, none of these studies used time intervals as the target stimulus to be remembered. The current study investigated the working memory for time intervals by asking participants to reproduce durations they experienced at different orders in a series of experienced intervals (n-back task). One of the experiments was conducted online and the other one in the lab setting. Results showed a central tendency bias and additive elongation of time reproductions with increasing working memory load. Our results also showed that participants assigned different weights to experienced intervals based on their order of presentation (higher weight to the target interval). We conclude that the recall of intervals from working memory under high cognitive load leads to a central tendency effect, which is known to be induced by the temporal context and present particularly in aging and in those with Parkinson's disease.

DE01 Swabs: a practical way to teach medical students about cutaneous infections

Abstract It is well established that dermatology is poorly understood among medical students and doctors of all grades. The combination of time allocated to teaching of dermatology, as well as the high impact of the hidden curriculum reinforcing dermatology as difficult and mysterious, lends itself to perpetuation of the zeitgeist. Cutaneous infections have a particularly high cognitive load due to their relatively short presentation time and wide varieties of manifestations. Investigation of cutaneous infections is also problematic with incorrect sampling undertaken for different infections. Junior doctors frequently default to black charcoal swabs for all skin infections, often getting feedback as inappropriate investigation after the patient has been discharged or are being read by different doctors altogether due to shift working. For 8 years, we have been running a practical tutorial session on skin infections at Swansea University Medical School. Old venesection prosthetic arms are decorated with simulation bacterial, fungal and viral infections. The bacterial pus is cold custard (or ‘pustard’) on swollen reddened sections. Herpetic vesicles are simulated with bubble wrap injected with Hibiscrub®. Tinea is simulated by dry polyvinyl acetate glue surrounded by red marker. The students have access to black charcoal swabs, red viral swabs, scalpels and fungal scraping cards. They also have dry universal containers and investigation forms. The 10–12 year-2 students are tasked with diagnosing each infective presentation with a short history and medical photography to back up the prosthetic representation. They then have to select the most appropriate investigative method and information to give to the microbiology department. Some students only have access to black charcoal swabs and need to improvise working out how to use the universal containers for their investigations. The knowledge is then shared at the end of the 40-min tutorial. This is conducted a day before the skin infection lecture, to reduce the cognitive load of that lecture. There has been consistently good feedback for this session, which allows students to think in real time about common clinical scenarios, making best use of laboratory services and improvising investigative techniques, where appropriate resources may not be available. The prosthetics have worked well year on year. Many of our first students are now practising doctors locally, and their dermatology knowledge is manifest in referrals. By practising the techniques in simulation, they are comfortable doing so in working life.

Development and validation of an assessment index for quantifying cognitive task load in pilots under simulated flight conditions using heart rate variability and principal component analysis

To investigate whether high cognitive task load (CTL) for aircraft pilots can be identified by analysing heart-rate variability, electrocardiograms were recorded while cadet pilots (n = 68) performed the plane tracking, anti-gravity pedalling, and reaction tasks during simulated flight missions. Data for standard electrocardiogram parameters were extracted from the R–R-interval series. In the research phase, low frequency power (LF), high frequency power (HF), normalised HF, and LF/HF differed significantly between high and low CTL conditions (p < .05 for all). A principal component analysis identified three components contributing 90.62% of cumulative heart-rate variance. These principal components were incorporated into a composite index. Validation in a separate group of cadet pilots (n = 139) under similar conditions showed that the index value significantly increased with increasing CTL (p < .05). The heart-rate variability index can be used to objectively identify high CTL flight conditions. Practitioner summary: We used principal component analysis of electrocardiogram data to construct a composite index for identifying high cognitive task load in pilots during simulated flight. We validated the index in a separate group of pilots under similar conditions. The index can be used to improve cadet training and flight safety. Abbreviations: ANOVA: a one-way analysis of variance; AP: anti-gravity pedaling task; CTL: cognitive task load; ECG: electrocardiograms; HR: heart rate; HRV: heart-rate variability; HRVI: heart-rate variability index; PT: plane-tracking task; RMSSD: root-mean square of differences between consecutive R–R intervals; RT: reaction task; SDNN: standard deviation of R-R intervals; HF: high frequency power; HFnu: normalized HF; LF: low frequency power; LFnu: normalized LF; PCA: principal component analysis.

Recognition and evaluation of mental workload in different stages of perceptual and cognitive information processing using a multimodal approach

This study explores the effects of different perceptual and cognitive information processing stages on mental workload by assessing multimodal indicators of mental workload such as the NASA-TLX, task performance, ERPs and eye movements. Repeated measures ANOVA of the data showed that among ERP indicators, P1, N1 and N2 amplitudes were sensitive to perceptual load (P-load), P3 amplitude was sensitive to P-load only in the prefrontal region during high cognitive load (C-load) states, and P3 amplitude in the occipital and parietal regions was sensitive to C-load. Among the eye movement indicators, blink frequency was sensitive to P-load in all C-load states, but to C-load in only low P-load states; pupil diameter and blink duration were sensitive to both P-load and C-load. Based on the above indicators, the k-nearest neighbours (KNN) algorithm was used to propose a classification method for the four different mental workload states with an accuracy of 97.89%. Practitioner summary: Based on the results of this study, it is possible to implement the monitoring of mental workload states and optimise brain task allocation in operations involving high mental workload, such as human-computer interaction.

Cognitive load causes kinematic changes in both elite and non-elite rowers

The current motor literature suggests that extraneous cognitive load may affect performance and kinematics in a primary motor task. A common response to increased cognitive demand, as observed in past studies, might be to reduce movement complexity and revert to previously learned movement patterns, in line with the progression-regression hypothesis. However, according to several accounts of automaticity, motor experts should be able to cope with dual task demands without detriment to their performance and kinematics. To test this, we conducted an experiment asking elite and non-elite rowers to use a rowing ergometer under conditions of varying task load. We employed single-task conditions with low cognitive load (i.e., rowing only) and dual-task conditions with high cognitive load (i.e., rowing and solving arithmetic problems). The results of the cognitive load manipulations were mostly in line with our hypotheses. Overall, participants reduced movement complexity, for example by reverting towards tighter coupling of kinematic events, in their dual-task performance as compared to single-task performance. The between-group kinematic differences were less clear. In contradiction to our hypotheses, we found no significant interaction between skill level and cognitive load, suggesting that the rowers' kinematics were affected by cognitive load irrespective of skill level. Overall, our findings contradict several past findings and automaticity theories, and suggest that attentional resources are required for optimal sports performance.

The effect of cognitive load on preference and intensity processing of sweet taste in the brain

Distracted eating can cause overconsumption. Whereas previous work has shown that cognitive load suppresses perceived taste intensity and increases subsequent consumption, the mechanism behind distraction-induced overconsumption remains unclear.To elucidate this, we performed two event-related fMRI experiments that examined how cognitive load affects neural responses and perceived intensity and preferred intensity, respectively, to solutions varying in sweetness. In Experiment 1 (N = 24), participants tasted weak sweet and strong sweet glucose solutions and rated their intensity while we concurrently varied cognitive load using a digit-span task. In Experiment 2 (N = 22), participants tasted five different glucose concentrations under varying cognitive load and then indicated whether they wanted to keep, decrease or increase its sweetness.Participants in Experiment 1 rated strong sweet solutions as less sweet under high compared to low cognitive load, which was accompanied by attenuated activation the right middle insula and bilateral DLPFC. Psychophysiological interaction analyses showed that cognitive load moreover altered connectivity between the middle insula and nucleus accumbens and DLPFC and middle insula while tasting strong sweet solutions.In Experiment 2, cognitive load did not affect participants’ preferred sweetness intensity. fMRI results revealed that cognitive load attenuated DLPFC activation for the strongest sweet solutions in the study.In conclusion, our behavioral and neuroimaging results suggest that cognitive load dampens the sensory processing of strong sweet solutions in particular, which may indicate higher competition for attentional resources for strong sweet than weak sweet solutions under high cognitive load. Implications for future research are discussed.

Identifying high cognitive load activities during simulated pediatric cardiac arrest using functional near-infrared spectroscopy

AimTo identify specific activities associated with high cognitive load during simulated pediatric out-of-hospital cardiac arrest (POHCA) resuscitation using physiological monitoring with functional near-infrared spectroscopy (fNIRS). MethodsWe recruited teams of emergency medical services (EMS) responders from fire departments located throughout the Portland, OR metropolitan area to participate in POHCA simulations. Teams consisted of both paramedics and emergency medical technicians (EMTs), with one paramedic serving as the person in charge (PIC). The PIC was outfitted with the OctaMon to collect fNIRS signals from the prefrontal cortex. Signals reported changes in oxygenated and deoxygenated hemoglobin concentrations, which were used to determine moments of increased cognitive activity. Increased cognitive activity was determined by significant increases in oxygenated hemoglobin and decreases in deoxygenated hemoglobin. Significant changes in fNIRS signals were associated with specific concurrent clinical tasks recorded by two independent researchers using video review. ResultsWe recorded cognitive activity of EMS providers in 18 POHCA simulations. We found that a proportion of PIC’s experienced relatively high cognitive load during medication administration, defibrillation, and rhythm checks compared to other events. ConclusionEMS providers commonly experienced increased cognitive activity during key resuscitation tasks that were related to safely coordinating team members around calculating and administering medications, defibrillation, and rhythm and pulse checks. Understanding more about activities that require high cognitive demand can inform future interventions that reduce cognitive load.

Kernel flow and the eye‐ brain connectome: Study design and objectives

AbstractBackgroundMore evidence suggests how the eye health may be crucial in older adults at risk of developing cognitive impairment (CI) and Alzheimer’s disease (AD). Ocular conditions and AD share several common factors, including older age behavioral and cardiometabolic disease. Poor vision can lead to reduced activation of central sensory pathways, which is associated with higher cognitive load and brain structure damage. We showed that CI is not limited to the brain but also affects the retina. However, despite recent advances in neuroimaging biomarkers (e.g., PET diagnostics), there remains a need for more readily available and affordable diagnostic testing for AD risk. While blood flow within the optic nerve head can be quantified using advanced optical imaging technologies, it is essential to measure what is going on in the brain at the same time.MethodWe propose a cross‐sectional and longitudinal, observational study evaluating structural and functional biomarkers of the retina and brain associated with AD disease risk and/or progression. The study objective is to collect structural and functional data of the retina and brain to facilitate the discovery of reliable and sensitive multimodal biomarkers of AD disease risk and/or progression. We will examine participants (N = 200) aged 55‐80; 50 cognitively healthy (CH), 50 with preclinical AD, 50 with mild CI (MCI), and 50 with mild AD. Assessments will include neuropsychological testing, medical/functional assessment, retinal imaging, brain activity, electroretinography, pupillometry, and contrast sensitivity. We will use a wearable, whole‐head coverage time‐domain functional near‐infrared spectroscopy system (Kernel Inc) to measure local changes in blood oxygenation and electroencephalography.ResultThe eye‐brain connectome is integral in understanding pathology in neurodegenerative diseases. We aim to use the eye‐brain data to develop screening and monitoring tools to identify and track AD risk and severity.ConclusionThis study will overcome limitations for performing functional brain imaging due to the lack of portability and user‐friendliness of neuroimaging devices. Our eye‐brain multimodal biomarker study could also facilitate a novel application for diagnostic assessment and therapeutic intervention to target neuroanatomical sites compromised early in AD, leading to a more robust technique to identify high‐risk individuals before cognitive decline with sufficient sensitivity and specificity.

Robust intuition? Exploring the difference in the strength of intuitions from perspective of attentional bias

The logical intuition hypothesis proposes a difference in the strength between logical and heuristic intuitions. The labels of logical and heuristic intuitions are exclusive to conventional reasoning research. This paper reports the result of testing intuition strength using the dot-probe methodology in a novel multiplication paradigm. Here, “logical intuition” and “heuristic intuition” were relabeled as “weaker intuition” (-1 × 5 = 5) and “stronger intuition” (1 × 5 = 5), respectively, to assess the assumptions about the difference in the strength of “Chinese multiplication mnemonics” intuitions. The dot-probe paradigm was utilized in the following experiments to measure attentional bias. This was assessed by calculating the difference in reaction time between incongruent (the target location is opposite to the probe location) and congruent (the target location is the same as the probe location) conditions. Experiment 1 found attentional bias directed attention to the correct answer for both weaker and stronger intuitions. Experiment 2 replicated and extended Experiment 1 with a secondary task to manipulate high and low cognitive loads. Consequently, stronger intuitions were unaffected by cognitive load and participants were biased toward the correct answer, whereas attentional bias for weaker intuitions only occurred in low load conditions. These results revealed that although both intuitions can guide attention, stronger intuition may guide attention bias in a high-load situation due to its robust automation. Our findings extend the logical intuition hypothesis that proposes a difference in the automated strengths of intuitions to mathematical and analytic thinking.

Colorslope: a balanced visualization of overview and details on ranks over time

Users are often interested in exploring ranks over time data to compare the performance or ranking of multiple observations with respect to each other. However, predominant visualization techniques suffer from a high cognitive load due to visual clutter. We propose Colorslope, a hybrid of Tufte’s slope graph and temporal heatmap, to depict ranks over time in one graph while maintaining an overview and details with scalability. Colorslope combines both canonical visualization methods’ complementary benefits: depicting overall trends and enabling the estimation of detailed values. We evaluated the efficacy and effectiveness of Colorslope by comparing it with a standard bump chart and temporal heatmap on various data sizes. We conclude that Colorslope contributes by (1) allowing users to identify extremes of the data and rate of change effectively in a relatively large number of series; (2) allowing the visualization to have better scalability in a larger amount of data (e.g., 30 ∼ 50) than a bump chart; and (3) allowing users to gain a better estimate of data values than a heatmap. For a certain size of ranks over time data, Colorslope provides an alternative solution to visualize multiple time series simultaneously that provides both an overview and a certain level of detail.

Is your mouse attracted by your eyes: Non-intrusive stress detection in off-the-shelf desktop environments

Increasing number of people work long hours with computers under high cognitive load. This could potentially cause mental stress in workplaces. Prolonged exposure to mental stress contributes to poor working experience and even severe health problems. Despite the growing demand, the existing intelligent stress detection methods are limited when applied to actual workplaces. They often measure physiological and physical signals, via intrusive devices, to detect stress. The intrusiveness hampers their accessibility and applicability in daily life and workplaces. To overcome that, behavior-based methods were proposed. Models that explore mouse and gaze behaviors during computer usages were demonstrated to be particularly effective. However, the current methods rely on using prior knowledge of the user interface (UI) layout to construct models. Their applicability thus is limited, especially in real workplaces where task UI is often dynamic. This paper presents a novel stress detection method to address the challenges. It attains non-intrusiveness and UI-agnostic by modeling the relative movement and coordination of mouse and gaze. The method is evaluated on a dynamic-UI task, namely, web searching. An accuracy of 78.8% is achieved using a commercial eye-tracker for gaze estimation, beating the state-of-the-art approaches by around 20%. We further use webcam to estimate gaze locations substituting for the eye-tracker, to enhance the model accessibility. The method yields 68.6% accuracy of stress detection without using any special devices. Experimental results demonstrate the effectiveness and applicability of our method. It opens up a new avenue for cognitive-aware adaptive user interface, intelligent working environment, and related applications.

Investigating the automaticity of links between body perception and trait concepts

ABSTRACT Social cognition has been argued to rely on automatic mechanisms, but little is known about how automatically the processing of body shapes is linked to other social processes, such as trait inference. In three pre-registered experiments, we tested the automaticity of links between body shape perception and trait inference by manipulating cognitive load during a response-competition task. In Experiment 1 (N = 52), participants categorised body shapes in the context of compatible or incompatible trait words, under high and low cognitive load. Bayesian multi-level modelling of reaction times indicated that interference caused by the compatibility of trait cues was insensitive to concurrent demands placed on working memory resources. These findings indicate that the linking of body shapes and traits is resource-light and more “automatic” in this sense. In Experiment 2 (N = 39) and 3 (N = 70), we asked participants to categorise trait words in the context of task-irrelevant body shapes. Under these conditions, no evidence of interference was found, regardless of concurrent load. These results suggest that while body shapes and trait concepts can be linked in an automatic manner, such processes are sensitive to wider contextual factors, such as the order in which information is presented.

Sow in tears and reap in joy: Eye tracking reveals age-related differences in the cognitive cost of spoken context processing.

Older adults have been found to use context to facilitate word recognition at least as efficiently as young adults. This may pose a conundrum, as context use is based on cognitive resources that are considered to decrease with aging. The goal of this study was to shed light on this question by testing age-related differences in context use and the cognitive demands associated with it. The eye movements of 30 young (21-27 years old) and 30 older adults (61-79 years old) were examined as they listened to spoken instructions to touch an image on a monitor. The predictability of the target word was manipulated between trials: nonpredictive (baseline), predictive (context), or predictive of two images (competition). In tandem, listeners were asked to retain one or four spoken digits (low or high cognitive load) for later recall. Separate analyses were conducted for the preceding sentence and the (final) target word. Sentence processing: Older adults were slower than young adults to accumulate evidence for target-word prediction (context condition), and they were more negatively affected by the increase in cognitive load (context and competition). Target-word recognition: No age-related differences were found in word recognition rate or the effect of cognitive load following predictive context (context and competition). Although older adults have greater difficulty processing context, they can use context to facilitate word recognition as efficiently as young adults. These results provide a better understanding of how cognitive processing changes with aging. They may help develop interventions aimed at improving communication in older adults. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Talking with hands and feet: Selective somatosensory attention and fMRI enable robust and convenient brain-based communication

In brain-based communication, voluntarily modulated brain signals (instead of motor output) are utilized to interact with the outside world. The possibility to circumvent the motor system constitutes an important alternative option for severely paralyzed. Most communication brain-computer interface (BCI) paradigms require intact visual capabilities and impose a high cognitive load, but for some patients, these requirements are not given. In these situations, a better-suited, less cognitively demanding information-encoding approach may exploit auditorily-cued selective somatosensory attention to vibrotactile stimulation. Here, we propose, validate and optimize a novel communication-BCI paradigm using differential fMRI activation patterns evoked by selective somatosensory attention to tactile stimulation of the right hand or left foot. Using cytoarchitectonic probability maps and multi-voxel pattern analysis (MVPA), we show that the locus of selective somatosensory attention can be decoded from fMRI-signal patterns in (especially primary) somatosensory cortex with high accuracy and reliability, with the highest classification accuracy (85.93%) achieved when using Brodmann area 2 (SI-BA2) at a probability level of 0.2. Based on this outcome, we developed and validated a novel somatosensory attention-based yes/no communication procedure and demonstrated its high effectiveness even when using only a limited amount of (MVPA) training data. For the BCI user, the paradigm is straightforward, eye-independent, and requires only limited cognitive functioning. In addition, it is BCI-operator friendly given its objective and expertise-independent procedure. For these reasons, our novel communication paradigm has high potential for clinical applications.

Offloading under cognitive load: Humans are willing to offload parts of an attentionally demanding task to an algorithm.

In the near future, humans will increasingly be required to offload tasks to artificial systems to facilitate daily as well as professional activities. Yet, research has shown that humans are often averse to offloading tasks to algorithms (so-called "algorithmic aversion"). In the present study, we asked whether this aversion is also present when humans act under high cognitive load. Participants performed an attentionally demanding task (a multiple object tracking (MOT) task), which required them to track a subset of moving targets among distractors on a computer screen. Participants first performed the MOT task alone (Solo condition) and were then given the option to offload an unlimited number of targets to a computer partner (Joint condition). We found that participants significantly offloaded some (but not all) targets to the computer partner, thereby improving their individual tracking accuracy (Experiment 1). A similar tendency for offloading was observed when participants were informed beforehand that the computer partner's tracking accuracy was flawless (Experiment 2). The present findings show that humans are willing to (partially) offload task demands to an algorithm to reduce their own cognitive load. We suggest that the cognitive load of a task is an important factor to consider when evaluating human tendencies for offloading cognition onto artificial systems.