Artificial Intelligence-Generated Content (AIGC) can improve production efficiency and reduce creation costs, but consumer evaluations of AIGC applications remain mixed. Based on the Associative-Propositional Evaluation (APE) model, we used event-related potentials (ERPs) to examine consumers’ automatic neural responses and behavioral judgments of AIGC applications across different levels of emotional engagement.Pairing positive adjectives with AIGC content elicited more negative N2 amplitudes, which reflects early cognitive conflict or mismatch during associative-dominant processing. In high-emotional-engagement scenarios, negative adjectives triggered more negative N2 amplitudes than in low-emotional conditions, showing that early evaluative processing is modulated by the application context.Behaviorally, acceptance rates for negative adjectives were higher than for positive adjectives in low-emotional scenarios, meaning implicit responses differ across emotional contexts.These findings offer preliminary neurophysiological evidence for AIGC evaluation, but the results should be interpreted with caution.
The N2 component primarily indexes early cognitive conflict, and is not a process-specific marker of definitive attitude valence. The study uses a small, non-probability volunteer sample, which limits the generalizability of the findings. Future research needs to replicate these effects with larger, more representative populations to validate the results.
This research project was supported by the National Social Sciences funded general projects, PRC (Grant No. 22BGL006), and Humanities and Social Sciences Planning Project of the Ministry of Education, PRC (Grant No. 20YJA630054), and National Social Sciences later funded projects, PRC (Grant No. 21FGLB041). School of Business, Huaqiao University, Quanzhou, 362021, China Chen Shouren College of Business, Quanzhou Normal University, Quanzhou, 362021, China College of Architecture and Urban Planning, Tongji University, Shanghai, 200092, China The authors declare no competing interests. The study was conducted in accordance with the Declaration of Helsinki, and approved by Ethics Committee of Huaqiao University(M2023009 approval on 19 April 2023).All participants signed an informed consent form before the experiment and received compensation upon completion.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it.
The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Lv, D., Sun, R., Qin, S. et al. Neural responses to AIGC based on the associative propositional evaluation model. Sci Rep (2026). https://doi.org/10.1038/s41598-026-68985-7 DOI: https://doi.org/10.1038/s41598-026-68985-7
Extract — continue reading at the source.
