Comprehensive list of academic papers, tools, and data sources used in this study.
Primary Academic References
Ansani, A., Marini, M., & Mallia, L. (2025). AI performer bias in music evaluation: The impact of authorship labels on aesthetic judgments. Psychology of Aesthetics, Creativity, and the Arts, 19(1), 45-58.
Agbangla, N. F., Audiffren, M., Pylouster, J., & Albinet, C. T. (2022). Load-dependent prefrontal cortex activation assessed by continuous-wave near-infrared spectroscopy during two executive tasks with three cognitive loads in young adults. Brain Sciences, 12(11), 1462.
Ayaz, H., Shewokis, P. A., Bunce, S., Izzetoglu, K., Willems, B., & Onaral, B. (2012). Optical brain monitoring for operator training and mental workload assessment. NeuroImage, 59(1), 36–47.
Baayen, R. H., Davidson, D. J., & Bates, D. M. (2008). Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory and Language, 59(4), 390–412.
Fishburn, F. A., Norr, M. E., Medvedev, A. V., & Vaidya, C. J. (2014). Sensitivity of fNIRS to cognitive load and state. Frontiers in Human Neuroscience, 8, Article 76.
Holper, L., Shallert, T., Siebenmorgen, M., Mühlberger, A., & de Haas, B. (2022). Using fNIRS to identify transparency- and reliability-sensitive markers of trust across multiple timescales in collaborative human-human-agent triads. Frontiers in Neuroergonomics, 3, Article 838625.
Zhang, W., Xie, C., Jiang, L., Yang, L., Hu, Z., & Hao, N. (2025). Neural correlates of evaluative bias against artificial intelligence-labeled versus human-labeled artworks. Social Cognitive and Affective Neuroscience, 20(1), nsaf071.