Connectivity-based localization of human hypothalamic nuclei in functional images of standard voxel size

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.