Cognitive Load Assessment in Multitasking: An fNIRS Study of Prefrontal Cortex Activation for Ergonomic Insight
DOI: 10.25077/josi.v24.n2.p305-323.2025
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Summary
This study investigates how multitasking demands modulate prefrontal cortex (PFC) activation, addressing the limitations of traditional neuroimaging techniques like fMRI and EEG, which are restricted by motion artifacts and rigid environments. The authors propose functional near-infrared spectroscopy (fNIRS) as a practical alternative for assessing cognitive load in ecologically valid, dynamic settings. The research aims to determine if increased multitasking complexity specifically recruits PFC subregions, particularly the dorsolateral prefrontal cortex (dlPFC), and to validate fNIRS as a tool for real-time cognitive load monitoring in high-stakes industries such as aviation and healthcare. The study employed a repeated-measures design with 30 participants (mean age 32.04 years) who completed tasks from the Multi-Attribute Task Battery (MATB). The MATB simulated multitasking through three subtasks: system monitoring, target tracking, and resource management. Task demand was manipulated into low and high conditions by adjusting event rates and difficulty levels; the communication subtask was omitted to reduce sensory load for non-expert participants. Brain activity was recorded using an eight-channel fNIRS system positioned over the bilateral PFC. Data preprocessing involved motion artifact correction, band-pass filtering, and conversion to oxygenated hemoglobin (HbO) concentrations. Statistical analysis used paired-sample t-tests with Bonferroni correction to compare HbO responses between conditions, while AtlasViewer was used to project activation onto cortical surfaces. Results confirmed successful manipulation of task demand, with significantly lower performance scores and higher subjective workload ratings in the high-demand condition. Neuroimaging data revealed that high-demand multitasking elicited significantly greater HbO responses across all channels compared to low-demand conditions. Specifically, the superior and middle frontal gyri, associated with the dlPFC, showed marked increases in activation during high-load tasks. Cortical mapping indicated that this activation was predominantly localized in the right PFC. In contrast, low-demand conditions produced weaker, more spatially restricted activation in lower PFC regions. These findings align with resource-based models of attention, suggesting that the brain allocates greater cognitive resources, particularly in the right PFC, to manage increased task complexity and executive control demands. The study concludes that fNIRS is a viable, motion-tolerant tool for detecting real-time cognitive load during complex multitasking. The observed lateralization and specific recruitment of the right dlPFC provide neurophysiological evidence for how the brain manages competing demands. These findings have significant implications for ergonomic design and adaptive systems, offering a method to monitor mental overload in real-world operational environments. By bridging laboratory research and practical application, the study supports the use of fNIRS-based neurofeedback to enhance performance and resilience in high-stakes, dynamic work contexts.
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-08-09 |
| archive | success | canonical_url | — | — | 1 | 2026-08-09 |
| extract | success | cached | — | — | 3 | 2026-08-10 |
| clean | success | clean | — | — | 1 | 2026-08-09 |
| chunk | success | chunk | — | — | 1 | 2026-08-09 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-08-09 |
| promote | success | — | — | — | 1 | 2026-08-09 |
| summarize | success | llm | qwen3.6-27b-nvidia | summ-v5 | 2 | 2026-08-10 |
| tag | success | vector_similarity | — | — | 11 | 2026-08-11 |
| verify | success | — | — | — | 2 | 2026-08-10 |
Summary generated by qwen3.6-27b-nvidia on 2026-08-10; verification: verified.
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- Empirical Findings: physiological data