In-vivo data-driven parcellation of Heschl’s gyrus using structural connectivity

Abstract

Abstract The human auditory cortex around Heschl’s gyrus (HG) exhibits diverging patterns across individuals owing to the heterogeneity of its substructures. In this study, we investigated the subregions of the human auditory cortex using data-driven machine-learning techniques at the individual level and assessed their structural and functional profiles. We studied an openly accessible large dataset of the Human Connectome Project and identified the subregions of the HG in humans using data-driven clustering techniques with individually calculated imaging features of cortical folding and structural connectivity information obtained via diffusion magnetic resonance imaging tractography. We characterized the structural and functional profiles of each HG subregion according to the cortical morphology, microstructure, and functional connectivity at rest. We found three subregions. The first subregion (HG1) occupied the central portion of HG, the second subregion (HG2) occupied the medial-posterior-superior part of HG, and the third subregion (HG3) occupied the lateral-anterior-inferior part of HG. The HG3 exhibited strong structural and functional connectivity to the association and paralimbic areas, and the HG1 exhibited a higher myelin density and larger cortical thickness than other subregions. A functional gradient analysis revealed a gradual axis expanding from the HG2 to the HG3. Our findings clarify the individually varying structural and functional organization of human HG subregions and provide insights into the substructures of the human auditory cortex.