Sparse representation of HCP grayordinate data reveals novel functional architecture of cerebral cortex

Abstract

The recently publicly released Human Connectome Project (HCP) grayordinate-based fMRI data not only has high spatial and temporal resolution, but also offers group-corresponding fMRI signals across a large population for the first time in the brain imaging field, thus significantly facilitating mapping the functional brain architecture with much higher resolution and in a group-wise fashion. In this article, we adopt the HCP grayordinate task-based fMRI (tfMRI) data to systematically identify and characterize task-based heterogeneous functional regions (THFRs) on cortical surface, i.e., the regions that are activated during multiple tasks conditions and contribute to multiple task-evoked systems during a specific task performance, and to assess the spatial patterns of identified THFRs on cortical gyri and sulci by applying a computational framework of sparse representations of grayordinate brain tfMRI signals. Experimental results demonstrate that both consistent task-evoked networks and intrinsic connectivity networks across all subjects and tasks in HCP grayordinate data are effectively and robustly reconstructed via the proposed sparse representation framework. Moreover, it is found that there are relatively consistent THFRs locating at bilateral parietal lobe, frontal lobe, and visual association cortices across all subjects and tasks. Particularly, those identified THFRs locate significantly more on gyral regions than on sulcal regions. These results based on sparse representation of HCP grayordinate data reveal novel functional architecture of cortical gyri and sulci, and might provide a foundation to better understand functional mechanisms of the human cerebral cortex in the future.