Prefrontal hemodynamic responses during video learning across academic disciplines: An fNIRS study
Year: 2026
Type: article
Abstract: Different academic disciplines involve different types of knowledge and learning processes, which may be reflected in variation in prefrontal hemodynamic responses during learning. To simulate real learning scenarios, we used multidisciplinary instructional videos and functional near-infrared spectroscopy(fNIRS) to examine changes in prefrontal hemodynamics. Thirty-five participants completed video learning tasks classified according to the soft–hard dimension of Biglan’s framework. A General Linear Model (GLM) was applied to estimate [Formula: see text] coefficients for eight prefrontal channels. Results revealed significant differences between soft and hard disciplines in [Formula: see text] values in channels corresponding primarily to Brodmann areas BA10(frontopolar cortex), BA11(orbitofrontal cortex), and BA46(dorsolateral prefrontal cortex). Specifically, soft disciplines (social sciences and humanities) showed significantly larger [Formula: see text] estimates in channels 5 and 6(BA10/11) compared with hard disciplines (natural sciences and applied sciences). Within the same disciplinary context, participants with post-test accuracy below 70% exhibited significantly higher [Formula: see text] values in multiple BA10 channels than participants with higher accuracy, indicating greater prefrontal engagement under equivalent task demands. These findings describe differences across disciplines and across performance levels in GLM prefrontal hemodynamic responses during naturalistic video learning, providing quantitative evidence that disciplinary context and learner proficiency are associated with variation in prefrontal engagement.
Authors: Dan Liang, Hui Xie, Huiting Yang, Jiangshan He, Chunli Jia, Yuqiang Yang, Lianghua Zhang, Ziqi Ren, Mingzhe Jiang, Defu Yang, Lei Zheng, Xueli Chen
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
SDG: Quality education
Open Access status: gold
Estimated APC paid: $1,500
Award: G3585627653
OpenAlex ID: W7155168999
