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静息态功能磁共振成像研究中去噪的关键事件相关评估

A Critical, Event-Related Appraisal of Denoising in Resting-State fMRI Studies.

作者信息

Power Jonathan D, Lynch Charles J, Adeyemo Babatunde, Petersen Steven E

机构信息

Sackler Institute for Developmental Psychobiology, Department of Psychiatry, Weill Cornell Medicine, 1300 York Avenue, New York, NY 10065, USA.

Brain and Mind Research Institute, Weill Cornell Medicine, 1300 York Avenue, New York, NY 10065, USA.

出版信息

Cereb Cortex. 2020 Sep 3;30(10):5544-5559. doi: 10.1093/cercor/bhaa139.

Abstract

This article advances two parallel lines of argument about resting-state functional magnetic resonance imaging (fMRI) signals, one empirical and one conceptual. The empirical line creates a four-part organization of the text: (1) head motion and respiration commonly cause distinct, major, unwanted influences (artifacts) in fMRI signals; (2) head motion and respiratory changes are, confoundingly, both related to psychological and clinical and biological variables of interest; (3) many fMRI denoising strategies fail to identify and remove one or the other kind of artifact; and (4) unremoved artifact, due to correlations of artifacts with variables of interest, renders studies susceptible to identifying variance of noninterest as variance of interest. Arising from these empirical observations is a conceptual argument: that an event-related approach to task-free scans, targeting common behaviors during scanning, enables fundamental distinctions among the kinds of signals present in the data, information which is vital to understanding the effects of denoising procedures. This event-related perspective permits statements like "Event X is associated with signals A, B, and C, each with particular spatial, temporal, and signal decay properties". Denoising approaches can then be tailored, via performance in known events, to permit or suppress certain kinds of signals based on their desirability.

摘要

本文针对静息态功能磁共振成像(fMRI)信号提出了两条并行的论证思路,一条是实证性的,一条是概念性的。实证性思路构建了文本的四部分结构:(1)头部运动和呼吸通常会在fMRI信号中产生明显的、主要的、不必要的影响(伪影);(2)令人困惑的是,头部运动和呼吸变化都与感兴趣的心理、临床和生物学变量相关;(3)许多fMRI去噪策略无法识别和去除其中一种或另一种伪影;(4)由于伪影与感兴趣变量的相关性,未去除的伪影会使研究容易将非感兴趣的方差识别为感兴趣的方差。基于这些实证观察产生了一个概念性论点:即采用与事件相关的方法进行无任务扫描,针对扫描过程中的常见行为,能够对数据中存在的各种信号进行基本区分,而这些信息对于理解去噪程序的效果至关重要。这种与事件相关的观点允许做出如下表述:“事件X与信号A、B和C相关,每个信号都具有特定的空间、时间和信号衰减特性”。然后,可以根据已知事件中的表现来定制去噪方法,以便根据信号的可取性允许或抑制某些类型的信号。

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