Nenning Karl-Heinz, Liu Hesheng, Ghosh Satrajit S, Sabuncu Mert R, Schwartz Ernst, Langs Georg
Department of Biomedical Imaging and Image-guided Therapy, Computational Imaging Research Lab, Medical University of Vienna, Vienna, Austria.
A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, USA.
Neuroimage. 2017 Aug 1;156:456-465. doi: 10.1016/j.neuroimage.2017.04.028. Epub 2017 Apr 14.
Aligning brain structures across individuals is a central prerequisite for comparative neuroimaging studies. Typically, registration approaches assume a strong association between the features used for alignment, such as macro-anatomy, and the variable observed, such as functional activation or connectivity. Here, we propose to use the structure of intrinsic resting state fMRI signal correlation patterns as a basis for alignment of the cortex in functional studies. Rather than assuming the spatial correspondence of functional structures between subjects, we have identified locations with similar connectivity profiles across subjects. We mapped functional connectivity relationships within the brain into an embedding space, and aligned the resulting maps of multiple subjects. We then performed a diffeomorphic alignment of the cortical surfaces, driven by the corresponding features in the joint embedding space. Results show that functional alignment based on resting state fMRI identifies functionally homologous regions across individuals with higher accuracy than alignment based on the spatial correspondence of anatomy. Further, functional alignment enables measurement of the strength of the anatomo-functional link across the cortex, and reveals the uneven distribution of this link. Stronger anatomo-functional dissociation was found in higher association areas compared to primary sensory- and motor areas. Functional alignment based on resting state features improves group analysis of task based functional MRI data, increasing statistical power and improving the delineation of task-specific core regions. Finally, a comparison of the anatomo-functional dissociation between cohorts is demonstrated with a group of left and right handed subjects.
在个体间对齐脑结构是比较神经影像学研究的核心前提。通常，配准方法假定用于对齐的特征（如大体解剖结构）与观察到的变量（如功能激活或连接性）之间存在紧密关联。在此，我们提议在功能研究中使用内在静息态功能磁共振成像（fMRI）信号相关模式的结构作为皮质对齐的基础。我们并非假定个体间功能结构的空间对应关系，而是识别出跨个体具有相似连接模式的位置。我们将脑内的功能连接关系映射到一个嵌入空间，并对齐多个个体的所得图谱。然后，在联合嵌入空间中相应特征的驱动下，对皮质表面进行微分同胚对齐。结果表明，基于静息态fMRI的功能对齐比基于解剖结构空间对应关系的对齐能更准确地识别个体间功能同源区域。此外，功能对齐能够测量整个皮质上解剖 - 功能联系的强度，并揭示这种联系的不均匀分布。与初级感觉和运动区域相比，在高级联合区域发现了更强的解剖 - 功能分离。基于静息态特征的功能对齐改善了基于任务的功能MRI数据的组分析，提高了统计功效并改善了任务特定核心区域的描绘。最后，通过一组左利手和右利手受试者展示了不同队列之间解剖 - 功能分离的比较。
