title: Within brain area tractography suggests local modularity using high resolution connectomics.
abstract: Previous structural brain connectivity studies have mainly focussed on the macroscopic scale of around 1,000 or fewer brain areas (network nodes). However, it has recently been demonstrated that high resolution structural connectomes of around 50,000 nodes can be generated reproducibly. In this study, we infer high resolution brain connectivity matrices using diffusion imaging data from the Human Connectome Project. With such high resolution we are able to analyse networks within brain areas in a single subject. We show that the global network has a scale invariant topological organisation, which means there is a hierarchical organisation of the modular architecture. Specifically, modules within brain areas are spatially localised. We find that long range connections terminate between specific modules, whilst short range connections via highly curved association fibers terminate within modules. We suggest that spatial locations of white matter modules overlap with cytoarchitecturally distinct grey matter areas and may serve as the structural basis for function specialisation within brain areas. Future studies might elucidate how brain diseases change this modular architecture within brain areas.
authors.affiliation: Institute of Neuroscience, Newcastle University, United Kingdom.|Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing Science, Newcastle University, United Kingdom.|Institute of Neurology, University College London, United Kingdom.
authors.forename: Peter N
authors.initials: PN
authors.lastname: Taylor
authors.affiliation: Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing Science, Newcastle University, United Kingdom.
authors.forename: Yujiang
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Institute of Neuroscience, Newcastle University, United Kingdom.|Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing Science, Newcastle University, United Kingdom.
authors.forename: Marcus
authors.initials: M
authors.lastname: Kaiser
mesh_terms: D000328:Adult; D001921:Brain / Q000000981:diagnostic imaging / Q000502:physiology*; D063132:Connectome; D056324:Diffusion Tensor Imaging; D005260:Female; D066128:Gray Matter / Q000502:physiology; D006801:Humans; D008297:Male; D066127:White Matter / Q000502:physiology