ORIGINAL RESEARCH article
Front. Psychol.
Sec. Emotion Science
Volume 16 - 2025 | doi: 10.3389/fpsyg.2025.1665506
Multimodal Modeling of Emotion Regulation in Interactive Art Therapy: EEG and PANAS- -Based Dynamic Simulation
Provisionally accepted
Chen Xiaowei1,2
Miaomiao Zeng3*- 1MARA University of Technology, Shah Alam, Malaysia
- 2Zhejiang Shuren University, Hangzhou, China
- 3Zhaoqing University, Zhaoqing, China
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Abstract: Introduction: Emotion regulation within immersive art therapy emerges from the complex interplay of cognitive control, physiological arousal, and affective appraisal. Although this relationship has theoretical significance, the predictive connections between neurophysiological markers and subjective affective dynamics have yet to be thoroughly investigated. Methods: This study proposes a dual-model framework that integrates linear regression and nonlinear simulation to examine how electroencephalographic (EEG) features and PANAS-based self-reports jointly predict emotional change. EEG and affective data were collected from 50 participants following exposure to an interactive installation. Three predictors were derived: Theta_Change (cognitive load), Gamma_Change (physiological arousal), and Affective_Shift (subjective valence change). Results: Bootstrapped regression analysis (n = 1000) identified Affective_Shift as the most robust predictor of both positive affect change (Δ_Positive: β = 1.69, 95% CI [–0.53, 3.90]) and negative affect change (Δ_Negative: β = –3.96, 95% CI [–5.84, –2.16]). Gamma_Change also contributed significantly to positive emotional outcomes, while Theta_Change exhibited nonlinear effects contingent on initial affective states. Dynamic simulations conceptually illustrated stable emotional payoff trajectories and adaptive EEG shifts, offering an exploratory model of feedback-sensitive affective regulation. Discussion: Together, these findings support a multidimensional model of emotion regulation that integrates subjective evaluation with neurophysiological indicators. The results are consistent with Gross's process model, Russell's circumplex theory, and Kuppens's emotion dynamics framework. The proposed computational approach provides a mechanistic understanding and actionable insights for designing affect-aware, adaptive environments in therapeutic and artistic domains.
Keywords: Emotion Regulation, Interactive Art Therapy, EEG, affective shift, PANAS, Nonlinear simulation, Dynamic simulation, Feedback adaptation
Received: 14 Jul 2025; Accepted: 30 Sep 2025.
Copyright: © 2025 Xiaowei and Zeng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Miaomiao Zeng, 2008020009@zqu.edu.cn
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