The transcriptomic architecture of the human cerebral cortex

Abstract

For over a century, scientists have been attempting to map the human cerebral cortex, however, they have not taken into account the complex molecular structure of the cortex, which is only beginning to be understood. Here, we parcellate the human cerebral cortex using a machine learning (ML) approach to define its transcriptomic architecture, revealing a multi-resolution organization across individuals. The transcriptomically-derived spatial patterns of gene expression separate the cortex into three major regions, frontal, temporal and parietooccipital, with smaller subregions appearing at lower levels of the transcriptomic hierarchy. The core regions, which remain stable across different hierarchical levels, are physiologically associated with language, emotion regulation, social cognition, motor and visuospatial processing and planning. Importantly, some core regions cross structural and anatomical boundaries identified in previous parcellations of the cortex, revealing that the transcriptomic architecture of the cortex is closely linked to human-specific higher cognitive function.