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Mapping Anatomical Connectivity Patterns of Human Cerebral Cortex Using In Vivo Diffusion Tensor Imaging Tractography

Authors
  • Gong, Gaolang1
  • He, Yong2
  • Concha, Luis1
  • Lebel, Catherine1
  • Gross, Donald W.3
  • Evans, Alan C.2
  • Beaulieu, Christian1
  • 1 Department of Biomedical Engineering, 1098 Research Transition Facility, University of Alberta, Edmonton T6G 2V2, AB, Canada
  • 2 McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal H3A 2B4, QC, Canada
  • 3 Division of Neurology, Department of Medicine, University of Alberta, Edmonton T6G 2V2, AB, Canada
Type
Published Article
Journal
Cerebral Cortex
Publisher
Oxford University Press
Publication Date
Jun 20, 2008
Volume
19
Issue
3
Pages
524–536
Identifiers
DOI: 10.1093/cercor/bhn102
PMID: 18567609
PMCID: PMC2722790
Source
PubMed Central
Keywords
License
Unknown

Abstract

The characterization of the topological architecture of complex networks underlying the structural and functional organization of the brain is a basic challenge in neuroscience. However, direct evidence for anatomical connectivity networks in the human brain remains scarce. Here, we utilized diffusion tensor imaging deterministic tractography to construct a macroscale anatomical network capturing the underlying common connectivity pattern of human cerebral cortex in a large sample of subjects (80 young adults) and further quantitatively analyzed its topological properties with graph theoretical approaches. The cerebral cortex was divided into 78 cortical regions, each representing a network node, and 2 cortical regions were considered connected if the probability of fiber connections exceeded a statistical criterion. The topological parameters of the established cortical network (binarized) resemble that of a “small-world” architecture characterized by an exponentially truncated power-law distribution. These characteristics imply high resilience to localized damage. Furthermore, this cortical network was characterized by major hub regions in association cortices that were connected by bridge connections following long-range white matter pathways. Our results are compatible with previous structural and functional brain networks studies and provide insight into the organizational principles of human brain anatomical networks that underlie functional states.

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