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A Cortical Folding Pattern-Guided Model of Intrinsic Functional Brain Networks in Emotion Processing

机译:情绪处理中内在功能性脑网络的皮质折叠模式指导模型。

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摘要

There have been increasing studies demonstrating that emotion processing in humans is realized by the interaction within or among the large-scale intrinsic functional brain networks. Identifying those meaningful intrinsic functional networks based on task-based functional magnetic resonance imaging (task fMRI) with specific emotional stimuli and responses, and exploring the underlying functional working mechanisms of interregional neural communication within the intrinsic functional networks are thus of great importance to understand the neural basis of emotion processing. In this paper, we propose a novel cortical folding pattern-guided model of intrinsic networks in emotion processing: gyri serve as global functional connection centers that perform interregional neural communication among distinct regions via long distance dense axonal fibers, and sulci serve as local functional units that directly communicate with neighboring gyri via short distance fibers and indirectly communicate with other distinct regions via the neighboring gyri. We test the proposed model by adopting a computational framework of dictionary learning and sparse representation of emotion task fMRI data of 68 subjects in the publicly released Human Connectome Project. The proposed model provides novel insights of functional mechanisms in emotion processing.
机译:越来越多的研究表明,人类的情感加工是通过大规模的内在功能性大脑网络内部或内部的相互作用来实现的。因此,基于具有特定情绪刺激和反应的基于任务的功能磁共振成像(任务功能磁共振成像),识别那些有意义的内在功能网络,并探索内在功能网络内区域间神经通讯的潜在功能工作机制,对于理解该功能至关重要。情绪处理的神经基础。在本文中,我们提出了一种新颖的皮质折叠模式引导的情感处理内在网络模型:gyri作为全局功能连接中心,通过长距离密集的轴突纤维在不同区域之间执行区域间神经通信,而sulci作为局部功能单元它们通过短距离光纤直接与相邻的陀螺通信,并通过相邻的陀螺与其他不同区域间接通信。我们通过采用字典学习和稀疏表示的68个受试者的情感任务功能核磁共振数据的稀疏表示来测试该提议的模型,该方案在公开发布的人类Connectome项目中进行。提出的模型提供了情感处理中功能机制的新颖见解。

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