Department of Psychological and Brain Sciences, Indiana University, 1101 E. 10th St., Bloomington, IN 47405, United States.
Department of Psychological and Brain Sciences, Indiana University, 1101 E. 10th St., Bloomington, IN 47405, United States.
Neuroimage. 2018 May 1;171:376-392. doi: 10.1016/j.neuroimage.2017.12.082. Epub 2017 Dec 26.
Residual noise in the BOLD signal remains problematic for fMRI - particularly for techniques such as functional connectivity, where findings can be spuriously influenced by noise sources that can covary with individual differences. Many such potential noise sources - for instance, motion and respiration - can have a temporally lagged effect on the BOLD signal. Thus, here we present a tool for assessing residual lagged structure in the BOLD signal that is associated with nuisance signals, using a construction similar to a peri-event time histogram. Using this method, we find that framewise displacements - both large and very small - were followed by structured, prolonged, and global changes in the BOLD signal that depend on the magnitude of the preceding displacement and extend for tens of seconds. This residual lagged BOLD structure was consistent across datasets, and independently predicted considerable variance in the global cortical signal (as much as 30-40% in some subjects). Mean functional connectivity estimates varied similarly as a function of displacements occurring many seconds in the past, even after strict censoring. Similar patterns of residual lagged BOLD structure were apparent following respiratory fluctuations (which covaried with framewise displacements), implicating respiration as one likely mechanism underlying the displacement-linked structure observed. Global signal regression largely attenuates this artifactual structure. These findings suggest the need for caution in interpreting results of individual difference studies where noise sources might covary with the individual differences of interest, and highlight the need for further development of preprocessing techniques for mitigating such structure in a more nuanced and targeted manner.
BOLD 信号中的残余噪声仍然是 fMRI 的一个问题 - 特别是对于功能连接等技术,这些技术的发现可能会受到与个体差异相关的噪声源的虚假影响。许多这样的潜在噪声源 - 例如运动和呼吸 - 可能会对 BOLD 信号产生时间滞后的影响。因此,在这里,我们提出了一种工具,用于评估与烦扰信号相关的 BOLD 信号中的残余滞后结构,该工具使用类似于事件前时间直方图的结构。使用这种方法,我们发现帧位移 - 无论是大的还是非常小的 - 都会导致 BOLD 信号的结构化、延长和全局变化,这些变化取决于先前位移的幅度,并持续数十秒。这种残余滞后的 BOLD 结构在数据集之间是一致的,并且独立地预测了全局皮质信号的相当大的方差(在某些受试者中高达 30-40%)。平均功能连接估计值也会随着过去发生的位移的函数而变化,即使在严格的剔除之后也是如此。在呼吸波动(与帧位移相关)之后,也出现了类似的残余滞后 BOLD 结构模式,暗示呼吸是观察到的与位移相关的结构的一个可能机制。全局信号回归在很大程度上减轻了这种人为结构。这些发现表明,在解释可能与感兴趣的个体差异相关的噪声源的个体差异研究结果时需要谨慎,并且强调需要进一步开发预处理技术,以更细致和有针对性的方式减轻这种结构。