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Research on Functional Brain Networks Topological Properties by Real-time Fmri Emotion Self-regulation Training

机译:实时Fmri情绪自我调节训练对功能性脑网络拓扑特性的研究

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Various neuroimaging studies had demonstrated that multiple brain regions would activate during execute cognitive task. Meanwhile, Real-time functional magnetic resonance imaging neurofeedback (rtfMRI-NF) can assist subject self-regulation brain activity. However, the neural mechanisms about rtfMRI-NF were unclear. To investigate this problem, we combined graph theory with resting state fMRI to explore the topological properties of functional brain networks. In our study, subjects were provided with ongoing functional connectivity information which was related to emotion regulation. Our results showed that rtfMRI-NF training could alter the small-world properties and nodal degree in the temporal lobe, frontal lobe, limbic system. Together, our results suggested that rtfMRI-NF training was associated with alters in the topological properties of functional brain networks.
机译:各种神经影像研究表明,在执行认知任务期间,多个大脑区域会激活。同时,实时功能磁共振成像神经反馈(rtfMRI-NF)可以帮助受试者自我调节大脑活动。但是,关于rtfMRI-NF的神经机制尚不清楚。为了研究此问题,我们将图论与静止状态功能磁共振成像相结合,以探索功能性大脑网络的拓扑特性。在我们的研究中,为受试者提供了与情绪调节有关的持续功能连接信息。我们的结果表明,rtfMRI-NF训练可以改变颞叶,额叶,边缘系统的小世界特性和结节程度。在一起,我们的结果表明rtfMRI-NF训练与功能性大脑网络的拓扑特性的变化有关。

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