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Building connectomes using diffusion MRI: why, how and but

Sotiropoulos, Stamatios N.; Zalesky, Andrew

Building connectomes using diffusion MRI: why, how and but Thumbnail


Authors

Andrew Zalesky



Abstract

Why has diffusion MRI become a principal modality for mapping connectomes in vivo? How do different image acquisition parameters, fiber tracking algorithms and other methodological choices affect connectome estimation? What are the main factors that dictate the success and failure of connectome reconstruction? These are some of the key questions that we aim to address in this review. We provide an overview of the key methods that can be used to estimate the nodes and edges of macroscale connectomes, and we discuss open problems and inherent limitations. We argue that diffusion MRI-based connectome mapping methods are still in their infancy and caution against blind application of deep white matter tractography due to the challenges inherent to connectome reconstruction. We review a number of studies that provide evidence of useful microstructural and network properties that can be extracted in various independent and biologically-relevant contexts. Finally, we highlight some of the key deficiencies of current macroscale connectome mapping methodologies and motivate future developments.

Citation

Sotiropoulos, S. N., & Zalesky, A. (in press). Building connectomes using diffusion MRI: why, how and but. NMR in Biomedicine, https://doi.org/10.1002/nbm.3752

Journal Article Type Article
Acceptance Date May 3, 2017
Online Publication Date Jun 27, 2017
Deposit Date May 8, 2017
Publicly Available Date Jun 27, 2017
Journal NMR in Biomedicine
Print ISSN 0952-3480
Electronic ISSN 1099-1492
Publisher Wiley
Peer Reviewed Peer Reviewed
DOI https://doi.org/10.1002/nbm.3752
Keywords Tractography, connections, parcellation, white matter fibres, tracers, brain network
Public URL https://nottingham-repository.worktribe.com/output/868243
Publisher URL http://onlinelibrary.wiley.com/doi/10.1002/nbm.3752/abstract
Contract Date May 8, 2017

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