The human connectome is the complete structural description of the network of connections and elements that form the 'wiring diagram' of the brain. Due to the current scarcity of information regarding laminar end points of white matter tracts inside cortical grey matter, tractography remains focused on cortical partitioning into regions, while ignoring radial partitioning into laminar components. To overcome this biased representation of the cortex as a single homogenous unit, we use a recent data-derived model of cortical laminar connectivity, which has been further explored and corroborated in the macaque brain by comparison to published studies. The model integrates multimodal MRI imaging datasets of both white matter connectivity and grey matter laminar composition into a laminar-level connectome. In this study, we model the laminar connectome of healthy human brains (N = 30) and explore them via a set of complex network measures. Our analysis demonstrates a subdivision of network hubs that appear in the standard connectome into each individual component of the laminar connectome, giving a fresh look into the role of laminar components in cortical connectivity and offering new prospects in the fields of both structural and functional connectivity.
Keywords: Anatomical mapping; Brain network analysis; Computational models; Connectomics; Cortical layers; Neuronal structures.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.