对情绪面孔的神经生理学反应预测青少年情绪的动态波动。

Psychophysiology Pub Date : 2024-04-01 Epub Date: 2023-10-31 DOI:10.1111/psyp.14476
Allison M Letkiewicz, Carter J Funkhouser, Akina Umemoto, Esha Trivedi, Aishwarya Sritharan, Emily Zhang, Savannah N Buchanan, Fiona Helgren, Grace O Allison, Jürgen Kayser, Stewart A Shankman, Randy P Auerbach
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摘要

准确识别和解释他人情绪的能力对青春期的社交和情绪功能至关重要。事实上,之前的研究已经确定,基于实验室的面部情绪识别和对情绪面孔的参与指数可以预测青少年的情绪状态。然而,使用生态敏感的方法,社会情感信息处理是否与现实世界的情感动态有关,很少被评估。在本研究中,青少年(N = 62;13-18岁)完成面部识别任务,包括快乐、愤怒和悲伤的刺激,同时获取脑电图数据。参与者还提供了一周的生态瞬时评估(EMA)数据,探究他们当前的幸福、愤怒和悲伤水平,从而得出情绪指数(平均水平、惰性、不稳定性)。分析的重点是(1)准确度和(2)长期接触(LPP)情绪面孔和EMA报告的情绪之间的关系。与快乐面孔接触的时间越长,对快乐变化的抵抗力越小(即快乐惯性越小),而与愤怒面孔接触的次数越长,则对愤怒变化的抵抗越大(即愤怒惯性越大)。结果表明,实验室测量捕捉到的社会情绪过程对青少年情感状态具有现实意义,并突出了新治疗方法(如及时干预)的潜在可行目标。未来的研究应该继续评估社会情感信息过程和青少年情感状态动态波动之间的关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Neurophysiological responses to emotional faces predict dynamic fluctuations in affect in adolescents.

The ability to accurately identify and interpret others' emotions is critical for social and emotional functioning during adolescence. Indeed, previous research has identified that laboratory-based indices of facial emotion recognition and engagement with emotional faces predict adolescent mood states. Whether socioemotional information processing relates to real-world affective dynamics using an ecologically sensitive approach, however, has rarely been assessed. In the present study, adolescents (N = 62; ages 13-18) completed a Facial Recognition Task, including happy, angry, and sad stimuli, while EEG data were acquired. Participants also provided ecological momentary assessment (EMA) data probing their current level of happiness, anger, and sadness for 1-week, resulting in indices of emotion (mean-level, inertia, instability). Analyses focused on relations between (1) accuracy for and (2) prolonged engagement with (LPP) emotional faces and EMA-reported emotions. Greater prolonged engagement with happy faces was related to less resistance to changes in happiness (i.e., less happiness inertia), whereas greater prolonged engagement with angry faces associated with more resistance to changes in anger (i.e., greater anger inertia). Results suggest that socioemotional processes captured by laboratory measures have real-world implications for adolescent affective states and highlight potentially actionable targets for novel treatment approaches (e.g., just-in-time interventions). Future studies should continue to assess relations among socioemotional informational processes and dynamic fluctuations in adolescent affective states.

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