Cortical depth-dependent human fMRI of resting-state networks using EPIK

Recent laminar-fMRI studies have provided substantial understanding of the evoked cortical responses in multiple sub-systems; in contrast, the laminar component of resting-state networks spread over the whole brain has been less studied due to technical limitations. Animal studies strongly suggest that the supragranular layers of the cortex play a critical role in maintaining network resonance; however, whether this is true in the human cerebral cortex remains unclear. Here, we used EPIK, which offers unprecedented coverage at sub-millimetre resolution, to investigate cortical broad resting-state dynamics with depth specificity in healthy volunteers. Our results show that human network connectivity is primarily supported by intermediate and superficial layers of the cortex, and that the preferred cortical depth used for communication can vary from one network to another. We validated our results by comparing two resting-state fMRI scans, which were highly consistent, and one task fMRI scan, which exhibited certain laminar differences. The evaluation of laminar-fMRI across the brain encompasses unprecedented computational challenges; nonetheless, it enables a new dimension of the human neocortex to be investigated which may be key in the characterization of neurological disorders from a novel perspective. Significance statement Resting-state networks sustain conscious awareness and diverse cognitive processing in the absence of tasks. In contrast to cortical areas , the cortical depth -specific signals across different networks have been poorly investigated, mainly due to the small brain coverage enforced in high-resolution imaging methods. Here, using an optimized fMRI sequence, we demonstrate the critical involvement of the supragranular layers of the cerebral cortex in the maintenance of the resting-state dynamics. Given the cytoarchitectonics of the human neocortex, and based on our results, the cortical thickness constitutes an important dimension to characterize the resting-state oscillations in the healthy brain and its functional study may facilitate the identification of novel targets in neurological diseases. ### Competing Interest Statement The authors have declared no competing interest.