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关于静息态功能连接MRI全局信号回归的共识

Towards a consensus regarding global signal regression for resting state functional connectivity MRI.

作者信息

Murphy Kevin, Fox Michael D

机构信息

Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, CF24 4HQ, United Kingdom; Cardiff University Brain Research Imaging Centre (CUBRIC), School of Physics and Astronomy, Cardiff University, Cardiff, CF24 4HQ, United Kingdom.

Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, Boston, MA, United States.

出版信息

Neuroimage. 2017 Jul 1;154:169-173. doi: 10.1016/j.neuroimage.2016.11.052. Epub 2016 Nov 22.

Abstract

The number of resting state functional connectivity MRI studies continues to expand at a rapid rate along with the options for data processing. Of the processing options, few have generated as much controversy as global signal regression and the subsequent observation of negative correlations (anti-correlations). This debate has motivated new processing strategies and advancement in the field, but has also generated significant confusion and contradictory guidelines. In this article, we work towards a consensus regarding global signal regression. We highlight several points of agreement including the fact that there is not a single "right" way to process resting state data that reveals the "true" nature of the brain. Although further work is needed, different processing approaches likely reveal complementary insights about the brain's functional organisation.

摘要

静息态功能连接磁共振成像(MRI)研究的数量随着数据处理选项的增加而持续快速增长。在这些处理选项中,很少有像全局信号回归以及随后观察到的负相关(反相关)那样引发如此多的争议。这场争论推动了该领域新的处理策略和进展,但也产生了重大的困惑和相互矛盾的指导方针。在本文中,我们致力于就全局信号回归达成共识。我们强调了几个共识点,包括没有单一的“正确”方法来处理静息态数据以揭示大脑的“真实”本质这一事实。尽管还需要进一步的研究,但不同的处理方法可能会揭示关于大脑功能组织的互补性见解。

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