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Neglecting a critical auditory alarm is a major obstacle to maintaining a safe environment, especially in aviation. Earlier studies have indicated that tasks with a higher perceptual or cognitive load in the visual modality influence the processing of auditory stimuli. It is unclear, however, whether other factors, such as memory failure, active neglect, or expectancy influence the effect of cognitive load on auditory alarm detection sensitivity during aeronautical decision-making. In this study, we investigated this issue in three laboratory experiments using the technique of signal detection analysis, in which participants were asked to make a landing decision based on indicators of the instrument landing system while also trying to detect an audible alarm. We found that the sensitivity of auditory alarm detection was reduced under conditions of high cognitive load and that this effect persisted even when the auditory detection response occurred first (before the landing decision response) and when the probability of an auditory alarm was 40%. However, the sensitivity of auditory detection was not influenced by cognitive load under high expectancy conditions (60% probability of alarm presentation). Furthermore, the value of the response bias was reduced under high cognitive load conditions when the probability of an auditory alarm was low (20%). With an increase in the level of expectancy (40% and 60% probability of alarm presentation), it was found that cognitive load did not influence the response bias. These findings indicate that visual cognitive load affects the sensitivity to an auditory alarm only at a low expectancy level (20% and 40% probability of alarm presentation). The effect of cognitive load on the sensitivity to an auditory alarm was not due to memory failure or active neglect and the response bias was more sensitive to the expectancy factor.
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http://dx.doi.org/10.1016/j.apergo.2021.103629 | DOI Listing |
J Dent Educ
September 2025
Department of Oral and Maxillofacial Surgery, Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, P. R. China.
Background: Virtual reality (VR) and artificial intelligence (AI) technologies have advanced significantly over the past few decades, expanding into various fields, including dental education.
Purpose: To comprehensively review the application of VR and AI technologies in dentistry training, focusing on their impact on cognitive load management and skill enhancement. This study systematically summarizes the existing literature by means of a scoping review to explore the effects of the application of these technologies and to explore future directions.
Trends Cogn Sci
September 2025
Booth School of Business, University of Chicago, Chicago, IL 60637, USA; Data Science Institute, University of Chicago, Chicago, IL 60637, USA.
Over the last decade, new research has shown how human collectives can develop technologies that no single individual could discover on their own. However, this research often overlooks how technology can become so complex that individuals cannot operate it on their own. At this level of technological complexity, distributing cognition is a necessary process for reducing cognitive load on individuals.
View Article and Find Full Text PDFCurr Biol
August 2025
Department of Psychology, The University of Chicago, Chicago, IL 60637, USA; Institute for Mind and Biology, The University of Chicago, Chicago, IL 60637, USA.
Working memory (WM) is a core component of intellectual ability. Traditional behavioral accounts have argued that there remain distinct memory systems based on the type and sensory modality of information being stored. However, more recent work has provided evidence for a class of neural activity that indexes the number of visual items stored in a content-independent fashion.
View Article and Find Full Text PDFNurse Educ Today
August 2025
School of Nursing, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100144, China; School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China; Key Laboratory of Machine Perception (Ministry of
Background: Healthcare-related regret (HRR) is frequently encountered by healthcare professionals, even in the early clinical stages. Effective coping strategies are essential for mental well-being, professional performance, and career satisfaction. However, the specific coping mechanisms used by Master of Nursing specialist (MNS) students during clinical internships are not well understood.
View Article and Find Full Text PDFPLoS Comput Biol
September 2025
Department of Psychology and Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States of America.
Real-world decision-making often involves navigating large action spaces with state-dependent action values, taxing the limited cognitive resources at our disposal. While previous studies have explored cognitive constraints on generating action consideration sets or refining state-action mappings (policy complexity), their interplay remains underexplored. In this work, we present a resource-rational framework for policy compression that integrates both constraints, offering a unified perspective on decision-making under cognitive limitations.
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