2018年第45卷第5期目录
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封面故事:人类一些脑区比如后扣带回、内侧前额叶、双侧顶下叶在静息状态下的活动比在主动任务条件下强,这些脑区组成的网络被称为默认网络.静息态功能磁共振研究发现默认网络与精神分裂症、抑郁症等多种精神疾病有关.但这些研究大多采用功能连接的分析方式,无法揭示默认网络内各脑区的相互作用关系.张献昌等基于7T静息态功能磁共振数据,采用动态因果模型的分析方法,研究了默认网络主要结点的有向连接方式.实验结果发现,默认网络中后扣带回接受内侧前额叶、双侧顶下叶的信息输入,扮演信息集合中心的角色,而双侧顶下叶对内侧前额叶、后扣带回都有信息输入,在默认网络内可能起到信息驱动和调节的功能.本研究首次报道了基于 7T 功能磁共振数据得到的默认网络有向连接图谱,有助于更深入理解默认网络的功能和指导相关精神疾病的早期诊断.
(张献昌,薛 蓉,左真涛.人脑默认网络方向图:基于7TfMRI的动态因果模型,本期第536~543页)
Cover Story:The default mode network (DMN) has been reported to be involved in a variety of important cognitive functions and received increasing attention in neuroscience recently. Its dysfunction is also reported to be associated with multiple psychiatric disorders. However, the causal information flow (effective connectivity) within the default mode network remains poorly understood. In this study, we explored the effective connectivity pattern between 4 key DMN brain areas based on a high resolution 7T resting state fMRI dataset using a cutting-edge spectral dynamic causal modelling technique. Results showed that there was a distinct effective connectivity pattern among the DMN nodes. We found medial prefrontal cortex(MPFC) and bilateral inferior parietal cortex(IPC) sent information to the posterior cingulate cortex(PCC), which suggested that the PCC might be a hub region that collected information from other DMN areas. Besides, a causal influence was found from bilateral IPC to MPFC, and from left IPC to right IPC. This work was the first 7T fMRI study that investigated effective connectivity pattern among DMN nodes, which may promote our understandings about the functions of DMN and benefit future research in DMN-related psychiatric disorders.
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综述与专论
研究快报
研究报告
技术与方法
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