Webb J Taylor, Ferguson Michael A, Nielsen Jared A, Anderson Jeffrey S
Department of Bioengineering, University of Utah, Salt Lake City, Utah, United States of America.
Program in Neuroscience, University of Utah, Salt Lake City, Utah, United States of America.
PLoS One. 2013 Dec 13;8(12):e84279. doi: 10.1371/journal.pone.0084279. eCollection 2013.
A number of studies have tried to exploit subtle phase differences in BOLD time series to resolve the order of sequential activation of brain regions, or more generally the ability of signal in one region to predict subsequent signal in another region. More recently, such lag-based measures have been applied to investigate directed functional connectivity, although this application has been controversial. We attempted to use large publicly available datasets (FCON 1000, ADHD 200, Human Connectome Project) to determine whether consistent spatial patterns of Granger Causality are observed in typical fMRI data. For BOLD datasets from 1,240 typically developing subjects ages 7-40, we measured Granger causality between time series for every pair of 7,266 spherical ROIs covering the gray matter and 264 seed ROIs at hubs of the brain's functional network architecture. Granger causality estimates were strongly reproducible for connections in a test and replication sample (n=620 subjects for each group), as well as in data from a single subject scanned repeatedly, both during resting and passive video viewing. The same effect was even stronger in high temporal resolution fMRI data from the Human Connectome Project, and was observed independently in data collected during performance of 7 task paradigms. The spatial distribution of Granger causality reflected vascular anatomy with a progression from Granger causality sources, in Circle of Willis arterial inflow distributions, to sinks, near large venous vascular structures such as dural venous sinuses and at the periphery of the brain. Attempts to resolve BOLD phase differences with Granger causality should consider the possibility of reproducible vascular confounds, a problem that is independent of the known regional variability of the hemodynamic response.
许多研究试图利用血氧水平依赖(BOLD)时间序列中的细微相位差异来解析脑区顺序激活的顺序,或者更广泛地说,解析一个区域的信号预测另一个区域后续信号的能力。最近,这种基于滞后的测量方法已被应用于研究定向功能连接,尽管这种应用一直存在争议。我们试图使用大型公开可用数据集(FCON 1000、ADHD 200、人类连接体项目)来确定在典型的功能磁共振成像(fMRI)数据中是否观察到格兰杰因果关系的一致空间模式。对于来自1240名年龄在7至40岁的典型发育受试者的BOLD数据集,我们测量了覆盖灰质的7266个球形感兴趣区域(ROI)与脑功能网络架构中心的264个种子ROI中每对时间序列之间的格兰杰因果关系。格兰杰因果关系估计在测试和复制样本(每组n = 620名受试者)中的连接以及在静息和被动观看视频期间重复扫描的单个受试者的数据中都具有很强的可重复性。在来自人类连接体项目的高时间分辨率fMRI数据中,同样的效果甚至更强,并且在7种任务范式执行期间收集的数据中独立观察到。格兰杰因果关系的空间分布反映了血管解剖结构,从大脑 Willis 动脉环血流分布中的格兰杰因果关系源到硬脑膜静脉窦等大静脉血管结构附近以及脑外周的汇。用格兰杰因果关系解析BOLD相位差异的尝试应考虑可重复的血管混淆的可能性,这是一个独立于已知的血液动力学反应区域变异性的问题。