Signal and Image Processing Institute, University of Southern California, Los Angeles, CA 90089, United States.
Signal and Image Processing Institute, University of Southern California, Los Angeles, CA 90089, United States.
Neuroimage. 2018 May 15;172:740-752. doi: 10.1016/j.neuroimage.2018.01.058. Epub 2018 Feb 8.
We describe BrainSync, an orthogonal transform that allows direct comparison of resting fMRI (rfMRI) time-series across subjects. For this purpose, we exploit the geometry of the rfMRI signal space to propose a novel orthogonal transformation that synchronizes rfMRI time-series across sessions and subjects. When synchronized, rfMRI signals become approximately equal at homologous locations across subjects. The method is based on the observation that rfMRI data exhibit similar connectivity patterns across subjects, as reflected in the pairwise correlations between different brain regions. We show that if the data for two subjects have similar correlation patterns then their time courses can be approximately synchronized by an orthogonal transformation. This transform is unique, invertible, efficient to compute, and preserves the connectivity structure of the original data for all subjects. Analogously to image registration, where we spatially align structural brain images, this temporal synchronization of brain signals across a population, or within-subject across sessions, facilitates cross-sectional and longitudinal studies of rfMRI data. The utility of the BrainSync transform is illustrated through demonstrative simulations and applications including quantification of rfMRI variability across subjects and sessions, cortical functional parcellation across a population, timing recovery in task fMRI data, comparison of task and resting state data, and an application to complex naturalistic stimuli for annotation prediction.
我们描述了 BrainSync，这是一种正交变换，可以在不同个体之间直接比较静息 fMRI（rfMRI）时间序列。为此，我们利用 rfMRI 信号空间的几何形状来提出一种新颖的正交变换，该变换可以在不同的会话和个体之间同步 rfMRI 时间序列。当同步时，rfMRI 信号在不同个体的同源位置变得几乎相等。该方法基于这样的观察结果，即 rfMRI 数据在不同个体之间表现出相似的连接模式，这反映在不同大脑区域之间的成对相关性中。我们表明，如果两个个体的数据具有相似的相关模式，那么它们的时间序列可以通过正交变换进行近似同步。该变换是唯一的、可逆的、计算效率高的，并且为所有个体保留了原始数据的连接结构。类似于图像配准，我们在空间上对齐结构脑图像，在人群中或个体内跨会话对脑信号进行这种时间同步，促进了 rfMRI 数据的横断面和纵向研究。通过演示性模拟和应用，包括跨个体和会话的 rfMRI 变异性的量化、人群中的皮质功能分割、任务 fMRI 数据中的定时恢复、任务和静息状态数据的比较，以及对复杂自然刺激进行注释预测的应用，展示了 BrainSync 变换的实用性。
