Nalci Alican, Luo Wenjing, Liu Thomas T
Center for Functional MRI, University of California San Diego, 9500 Gilman Drive MC 0677, La Jolla, CA, 92093, USA; Department of Electrical and Computer Engineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA.
Center for Functional MRI, University of California San Diego, 9500 Gilman Drive MC 0677, La Jolla, CA, 92093, USA.
Neuroimage. 2019 Nov 15;202:116005. doi: 10.1016/j.neuroimage.2019.07.018. Epub 2019 Jul 20.
In resting-state functional MRI, the correlation between blood-oxygenation-level-dependent (BOLD) signals across brain regions is used to estimate the functional connectivity (FC) of the brain. FC estimates are prone to the influence of nuisance factors including scanner-related artifacts and physiological modulations of the BOLD signal. Nuisance regression is widely performed to reduce the effect of nuisance factors on FC estimates on a per-scan basis. However, a dedicated analysis of nuisance effects on the variability of FC metrics across a collection of scans has been lacking. This work investigates the effects of nuisance factors on the variability of FC estimates across a collection of scans both before and after nuisance regression. Inter-scan variations in FC estimates are shown to be significantly correlated with the geometric norms of various nuisance terms, including head motion measurements, signals derived from white-matter and cerebrospinal regions, and the whole-brain global signal (GS) both before and after nuisance regression. In addition, it is shown that GS regression (GSR) can introduce GS norm-related fluctuations that are negatively correlated with inter-scan FC estimates. The empirical results are shown to be largely consistent with the predictions of a theoretical framework previously developed for the characterization of dynamic FC measures. This work shows that caution must be exercised when interpreting inter-scan FC measures across scans both before and after nuisance regression.
在静息态功能磁共振成像中，利用全脑各区域血氧水平依赖（BOLD）信号之间的相关性来估计大脑的功能连接性（FC）。FC估计容易受到多种干扰因素的影响，包括与扫描仪相关的伪影以及BOLD信号的生理调制。为了减少每次扫描中干扰因素对FC估计的影响，人们广泛采用干扰回归方法。然而，目前缺乏对一系列扫描中干扰因素对FC指标变异性影响的专门分析。本研究探讨了干扰因素在干扰回归前后对一系列扫描中FC估计变异性的影响。结果表明，在干扰回归前后，FC估计的扫描间变化与各种干扰项的几何范数显著相关，这些干扰项包括头部运动测量值、来自白质和脑脊液区域的信号以及全脑全局信号（GS）。此外，研究还表明，全局信号回归（GSR）会引入与GS范数相关的波动，这些波动与扫描间FC估计呈负相关。实证结果在很大程度上与先前为动态FC测量表征而开发的理论框架的预测一致。这项研究表明，在解释干扰回归前后一系列扫描中的扫描间FC测量结果时必须谨慎。
