ArticleNeuroimage. Reports2024
Measuring cognitive load in multitasking using mobile fNIRS.
Article in Neuroimage. Reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Cognitive Load Across Interaction Formats in Digital Attention Assessment for Children: Within-Subject Neuroimaging and Behavioral Comparison Study.JMIR serious games · 2026Article
- A Miniaturized and Modular Wearable Functional Near-Infrared Spectroscopy (fNIRS) Sensing Module for High-Density Cerebral Hemodynamic Monitoring.Biosensors · 2026Article
- The role of AI and team topologies in enhancing decision-making flexibility by reducing cognitive overload.Frontiers in behavioral neuroscience · 2026Review
- Wearable technologies for assisted mobility in the real world.Nature communications · 2025Review
- Advancing Cognitive Load Detection in Simulated Driving Scenarios Through Deep Learning and fNIRS Data.Sensors (Basel, Switzerland) · 2025Article
- Associations between declines in uneven terrain walking speed and visuospatial working memory in older adults.Frontiers in aging neuroscience · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cognitive load, or the mental effort required to process and retain information, is a critical factor in high-stakes environments where task demands often exceed working memory capacity, leading to performance declines and errors. However, most cognitive load research has relied on controlled, single-task paradigms, limiting its applicability to real-world multitasking situations. Addressing this gap, we used a mobile, two-channel functional near-infrared spectroscopy (fNIRS) device to measure cognitive load in a complex multitasking environment, simulating real-world cognitive demands. Thirty-one undergraduate participants engaged in single-task and multitask conditions to simulate real-world cognitive demands. Results showed that subjective cognitive load ratings were higher, performance scores were lower, and error rates increased in the multitask condition compared to the single-task condition. However, contrary to expectations, prefrontal cortex activation did not increase in the multitask condition, suggesting a "cognitive disengagement" effect, where the brain limits engagement to manage overload. This finding challenges the traditional one-to-one association between cognitive load and prefrontal activation, as seen in simpler validation studies. Our study highlights the value of mobile fNIRS for assessing cognitive load in ecologically valid settings and provides insights that could inform strategies for optimizing performance in high-stakes environments like aviation and healthcare.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.