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Robust and Stable Small-World Topology of Brain Intrinsic Organization during Pre- and Post-Task Resting States

机译:任务前和任务后休息状态下大脑固有组织的鲁棒和稳定的小世界拓扑

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摘要

Brain functional network studies have demonstrated the small-world topology as the nature of large-scale spontaneous brain activity. Studies have also revealed that the temporal coherence of spontaneous activity could be reshaped during task-dependent (or post-task) resting states within local spatial patterns such as task-related and the default-mode networks. However, to our best knowledge, it is still a lack of rigorous investigations that whether the small-world topology of spontaneous intrinsic organization remains robust and stable during different resting states. To address the problem, we recorded blood oxygen level-dependent (BOLD) signals from two rests (namely, pre- and post-task resting states) before and after a simple semantic-matching task, and investigated the preceding task influences on the topology of the large-scale spontaneous intrinsic organization during the post-task resting state. The major findings are that the small-world configuration of spontaneous intrinsic organization remains robust and stable during resting states regardless of preceding task influences.
机译:大脑功能网络研究已证明小世界拓扑是大规模自发性大脑活动的本质。研究还表明,自发活动的时间连贯性可以在局部空间模式(例如与任务相关的网络和默认模式网络)内的任务相关(或任务后)静止状态期间重塑。然而,据我们所知,仍然缺乏严格的研究,即在不同的静止状态下,自发的内在组织的小世界拓扑结构是否保持健壮和稳定。为了解决该问题,我们在简单的语义匹配任务之前和之后记录了来自两个休止(即任务前和任务后的休止状态)的血氧水平依赖性(BOLD)信号,并研究了先前任务对拓扑的影响任务后休息状态下大规模自发内在组织的变化主要发现是,无论先前的任务影响如何,自发的内在组织的小世界结构在静止状态下都保持稳健和稳定。

著录项

  • 来源
    《Brain informatics》|2011年|p.136-147|共12页
  • 会议地点 Lanzhou(CN);Lanzhou(CN)
  • 作者单位

    International WIC Institute, Beijing University of Technology, China,Beijing Municipal Lab of Brain Informatics, China;

    International WIC Institute, Beijing University of Technology, China,Beijing Municipal Lab of Brain Informatics, China,Dept. of Computer Science, Hong Kong Baptist University, China;

    International WIC Institute, Beijing University of Technology, China,Beijing Municipal Lab of Brain Informatics, China,Dept. of Life Science and Informatics, Maebashi Institute of Technology, Japan;

    International WIC Institute, Beijing University of Technology, China,Beijing Municipal Lab of Brain Informatics, China,Dept. of Psychology, Carnegie Mellon University, USA;

    International WIC Institute, Beijing University of Technology, China,Beijing Municipal Lab of Brain Informatics, China;

    Dept. of Radiology, Xuanwu Hospital, Capital Medical University, China,Beijing Municipal Lab of Brain Informatics, China;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 信息处理(信息加工);神经生理学;
  • 关键词

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