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在面部情绪处理过程中对fMRI数据进行状态基础动态功能连接性分析

Maryam Gholam Tamimi¹, Mohammad Reza Daliri²

¹Neuroscience and Neuroengineering Research Laboratory, Biomedical Engineering Department, School of Electrical Engineering, Iran University of Science and Technology (IUST), Iran, 16846-13114, Tehran.

Brain imaging and behavior

|September 24, 2025

概括

这项研究揭示了在情绪处理过程中有三个不同的动态功能连接 (dFC) 状态. 关键的大脑网络,如面对面,边缘和视觉网络,显示了改变的连接模式,为情绪动态提供了新的见解.

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:

情感是人类互动和沟通的基础.
情绪处理 (EP) 涉及复杂的大脑网络动态.
了解EP的时间动态仍然是一个重大的研究挑战.

研究的目的:

在情绪处理任务期间调查动态功能连接 (dFC) 的变化.
使用功能磁共振成像 (fMRI) 识别不同的大脑连接状态及其时间动态.
探索不同情绪状况的区域连接的依赖状态的变化.

主要方法:

利用了来自100名健康参与者的人类结合体项目 (HCP) 的fMRI数据.
应用了滑窗相关性 (SWC) 和k-平均数聚类用于dFC分析.
采用隐藏的马尔科夫模型 (HMM) 来分析已识别的连接状态之间的过渡概率和停留时间.

主要成果:

确定了三种不同的dFC状态,其中涉及前端对象,边缘和视觉网络的过渡概率存在显著差异.
在面部和形状条件下观察到网络内部和网络间连接的状态依赖的变化.
临界,默认模式,前端双层,视觉,时间-双层和皮层下网络的关键双边区域显示出显著的dFC变化.

结论:

该研究成功地在情绪处理过程中识别出了不同的动态功能连接状态.
研究结果突出显示了大脑网络的时间动态,特别是情感任务中的前端对象,边缘和视觉系统.
这项研究为理解情绪处理背后的大脑活动复杂的时间组织提供了一个新的框架.

关键词:

动态功能连接的动态功能连接面部的情绪处理是面部的情绪处理.功能连接状态的功能连接状态.功能性磁共振成像技术功能性磁共振成像技术滑窗相关性滑窗相关性

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