多站点动态功能连接网络数据的协调

Biozid Bostami, V. Calhoun, H. V. D. Horn, V. Vergara
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引用次数: 5

摘要

神经科学研究已经开始受益于将来自不同地点的大量数据结合起来,以增加统计能力。将来自不同地点的数据汇集到一个单一的分析中,由于扫描仪协议、成像协议和采集方法等方面的差异,会引入额外的地点效应的可变性。这些地点效应会降低统计能力或导致错误的结论。协调是结合数据的过程,目的是减少站点的可变性。最近,一种名为ComBat的数据协调方法已被证明在功能性MRI和静态功能连接的背景下很有帮助。然而,ComBat尚未应用于动态功能网络连通性(dFNC)的分析。在这里,我们探讨了从两个不同的轻度创伤性脑损伤(mTBI)研究中收集的战斗协调对dFNC数据的影响。结果表明,dFNC的战斗协调可以减少站点效应,从而对跨站点的患者效应进行更稳健的分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Harmonization of Multi-site Dynamic Functional Connectivity Network Data
Neuroscience studies have begun to benefit from combining large numbers of data from different sites to increase statistical power. Pooling data from various sites into a single analysis introduces additional variability from site-effects due to differences in scanner protocols, imaging protocol, and acquisition methods, among others. These site-effects can reduce statistical power or lead to erroneous conclusions. Harmonization is the process of combining data aiming at reducing site variability. One recent approach for harmonizing data called ComBat has been shown to be helpful in the context of functional MRI and static functional connectivity. However, ComBat has not been applied to the analysis of dynamic functional network connectivity (dFNC). Here we explore the impact of ComBat harmonization on dFNC data collected from two different mild traumatic brain injury (mTBI) studies. Results show that ComBat harmonization of dFNC can reduce site effects producing a more robust analysis of patient effects across sites.
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