MR connectomics: Principles and challenges.
MR connectomics is an emerging framework in neuro-science that combines diffusion MRI and whole brain tractography methodologies with the analytical tools of network science. In the present work we review the current methods enabling structural connectivity mapping with MRI and show how such data can be used to infer new information of both brain structure and function. We also list the technical challenges that should be addressed in the future to achieve high-resolution maps of structural connectivity. From the resulting tremendous amount of data that is going to be accumulated soon, we discuss what new challenges must be tackled in terms of methods for advanced network analysis and visualization, as well data organization and distribution. This new framework is well suited to investigate key questions on brain complexity and we try to foresee what fields will most benefit from these approaches.
Hagmann
Patric
P
Department of Radiology, University Hospital Center and University of Lausanne (CHUV-UNIL), Switzerland; Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland. Patric.hagmann@epfl.ch
Cammoun
Leila
L
Gigandet
Xavier
X
Gerhard
Stephan
S
Grant
P Ellen
PE
Wedeen
Van
V
Meuli
Reto
R
Thiran
Jean-Philippe
JP
Honey
Christopher J
CJ
Sporns
Olaf
O
D000818:Animals; D001921:Brain / Q000033:anatomy & histology; D001931:Brain Mapping; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D056324:Diffusion Tensor Imaging; D006801:Humans; D008279:Magnetic Resonance Imaging; D009415:Nerve Net / Q000033:anatomy & histology; D009434:Neural Pathways / Q000033:anatomy & histology*