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在虚拟现实中处理情绪:使用加权相位滞后指数的EEG功能连接.

Yicai Bai, Chao Jiang, Jinglu Hu

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |December 3, 2025
    PubMed
    概括

    虚拟现实诱导的情绪和EEG数据显示,默认模式网络 (DMN) 是情绪处理的关键. 积极的情绪显示大脑网络在DMN和视觉网络中的同步增加.

    科学领域:

    • 神经科学是一个神经科学.
    • 认知科学 认知科学
    • 心理学 心理学 心理学

    背景情况:

    • 了解情绪的神经基础对于治疗抑郁症等情绪障碍至关重要.
    • 现有的研究强调了需要详细调查不同情绪状态期间的大脑活动的必要性.

    研究的目的:

    • 通过使用电脑电图 (EEG) 探索不同情绪状态背后的神经机制.
    • 确定涉及情绪处理的特定大脑网络及其功能连接.

    主要方法:

    • 招募了42名健康参与者,并通过虚拟现实 (VR) 诱导情绪.
    • 在诱导情绪状态期间记录了脑电图 (EEG) 数据.
    • 应用加权阶段滞后指数 (wPLI) 来分析在七个功能子网络中的大脑网络连接.

    主要成果:

    • 默认模式网络 (DMN) 显示出与情绪状态最强的关联.
    • 积极的情绪与DMN (theta和alpha波段) 内的相同步增加相关.
    • 在theta频段中观察到在积极情绪期间视觉网络中增强相位同步.

    结论:

    • 默认模式网络 (DMN) 和视觉网络在处理情绪方面发挥着重要作用.

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  • 这些网络内部和网络之间的连接模式表明了情绪状态.
  • 研究结果提供了关于积极情绪的神经相关的见解,以及情绪障碍干预的潜在目标.