Connectivity-based localization of human hypothalamic nuclei in functional images of standard voxel size
Ogawa, Akitoshi et al. (2020), Connectivity-based localization of human hypothalamic nuclei in functional images of standard voxel size, Dryad, Dataset, https://doi.org/10.5061/dryad.3j9kd51g0
Despite their critical roles in autonomic functions, individual hypothalamic nuclei have not been extensively investigated in humans using functional magnetic resonance imaging, partly due to the difficulty in resolving individual nuclei contained in the small structure of the hypothalamus. Areal parcellation analyses enable discrimination of individual hypothalamic nuclei but require a higher spatial resolution, which necessitates long scanning time or large amounts of data to compensate for the low signal-to-noise ratio in 3T or 1.5T scanners. In this study, we present analytic procedures to estimate likely locations of individual nuclei in the standard 2-mm resolution based on our higher resolution dataset. The spatial profiles of functional connectivity with the cerebral cortex for each nucleus in the medial hypothalamus were calculated using our higher resolution dataset. Voxels in the hypothalamus in standard resolution images from the Human Connectome Project (HCP) database that predominantly shared connectivity profiles with the same nucleus were subsequently identified. Voxels representing individual nuclei, as identified with the analytic procedures, were reproducible across 20 HCP datasets of 20 subjects each. Furthermore, the identified voxels were spatially separate. These results suggest that these analytic procedures are capable of refining voxels that represent individual hypothalamic nuclei in standard resolution. Our results highlight the potential utility of these procedures in various settings such as patient studies, where lengthy scans are infeasible.
Japan Society for the Promotion of Science, Award: 19K07807