Connectome-scale functional intrinsic connectivity networks in macaques

There have been extensive studies of intrinsic connectivity networks (ICNs) in the human brains using resting-state functional magnetic resonance imaging (fMRI) in the literature. However, the functional organization of ICNs in macaque brains has been less explored so far, despite growing interests in the field. In this work, we propose a computational framework to identify connectome-scale group-wise consistent ICNs in macaques via sparse representation of whole-brain resting-state fMRI data. Experimental results demonstrate that 70 group-wise consistent ICNs are successfully identified in macaque brains via the proposed framework. These 70 ICNs are interpreted based on two publicly available parcellation maps of macaque brains and our work significantly expand currently known macaque ICNs already reported in the literature. In general, this set of connectome-scale group-wise consistent ICNs can potentially benefit a variety of studies in the neuroscience and brain-mapping fields, and they provide a foundation to better understand brain evolution in the future.