University Centre of Statistics in the Biomedical Sciences (CUSSB), Vita-Salute San Raffaele University, Milan, Italy.
Department of Clinical Neurosciences, IRCCS San Raffaele Turro, Milan, Italy.
PLoS One. 2018 Nov 16;13(11):e0207123. doi: 10.1371/journal.pone.0207123. eCollection 2018.
Correctly recognizing emotions is an essential skill to manage interpersonal relationships in everyday life. Facial expression represents the most powerful mean to convey important information on emotional and cognitive states during interactions with others. In this paper, we analyze physiological responses triggered by an emotion recognition test, which requires the processing of facial cues. In particular, we evaluate the modulation of several Heart Rate Variability indices, collected during the Reading the Mind in the Eyes Test, accounting for test difficulty (derived from a Rasch analysis), test performances, demographic and psychological characteristics of the participants. The main idea is that emotion recognition is associated with the Autonomic Nervous System and, as a consequence, with the Heart Rate Variability. The principal goal of our study was to explore the complexity of the collected measures and their possible interactions by applying a class of flexible models, i.e., the latent class mixed models. Actually, this modelling strategy allows for the identification of clusters of subjects characterized by similar longitudinal trajectories. Both univariate and multivariate latent class mixed models were used. In fact, while the interpretation of the Heart Rate Variability indices is very difficult when considered individually, a joint evaluation provides a better description of the Autonomic Nervous System state.
正确识别情绪是日常生活中管理人际关系的一项基本技能。面部表情是在与他人互动时传达情感和认知状态重要信息的最有力手段。在本文中，我们分析了情绪识别测试引发的生理反应，该测试需要处理面部提示。具体来说，我们评估了在阅读眼睛中的思维测试过程中收集的几种心率变异性指标的调制，这些指标考虑了测试难度（源自拉什分析）、测试表现、参与者的人口统计学和心理特征。主要思想是，情绪识别与自主神经系统有关，因此与心率变异性有关。我们研究的主要目标是通过应用一类灵活的模型（即潜在类别混合模型）来探索所收集措施的复杂性及其可能的相互作用。实际上，这种建模策略允许识别具有相似纵向轨迹的受试者聚类。使用了单变量和多变量潜在类别混合模型。事实上，当单独考虑心率变异性指数时，其解释非常困难，而联合评估则可以更好地描述自主神经系统状态。
