BigBrain: Automated cortical parcellation and comparison with existing brain atlases

Abstract

Most available 3D human brain atlases provide information only at a macroscopic level, while 2D atlases are often at a microscopic level but lack 3D integration. A 3D atlas defined upon fine-grain anatomical detail of cortical layers and cells is necessary to fully understand neurobiological processes. “BigBrain,” a high-resolution 3D model of a human brain at nearly cellular resolution, was released in 2013. This unique dataset enables the extraction of microscopic data for utilization in brain mapping, modeling and simulation. We propose an automated 3D cortical parcellation of the BigBrain volume into functionally-meaningful areas in order to create a modern high-resolution 3D cytoarchitectural atlas that will complement existing brain atlases. We use a distance metrics-based framework for BigBrain parcellation, and perform comparative analyses of our results with existing atlases (Brodmann and JuBrain atlases). This work has immediate application in teaching, neurosurgery, cognitive neuroscience, and imaging-based brain mapping.