The Human Connectome Project's neuroimaging approach

Glasser, Matthew F.; Smith, Stephen M.; Marcus, Daniel S.; Andersson, Jesper L.R.; Auerbach, Edward J.; Behrens, Timothy E.J.; Coalson, Timothy S.; Harms, Michael P.; Jenkinson, Mark; Moeller, Steen; Robinson, Emma C.; Sotiropoulos, Stamatios N.; Xu, Junqian; Yacoub, Essa; Ugurbil, Kamil; Van Essen, David C.

doi:10.1038/nn.4361

Authors

Matthew F. Glasser

Stephen M. Smith

Daniel S. Marcus

Jesper L.R. Andersson

Edward J. Auerbach

Timothy E.J. Behrens

Timothy S. Coalson

Michael P. Harms

Mark Jenkinson

Steen Moeller

Emma C. Robinson

STAMATIOS SOTIROPOULOS Stamatios.Sotiropoulos@nottingham.ac.uk
Professor of Computational Neuroimaging

Junqian Xu

Essa Yacoub

Kamil Ugurbil

David C. Van Essen

Abstract

Noninvasive human neuroimaging has yielded many discoveries about the brain. Numerous methodological advances have also occurred, though inertia has slowed their adoption. This paper presents an integrated approach to data acquisition, analysis and sharing that builds upon recent advances, particularly from the Human Connectome Project (HCP). The 'HCP-style' paradigm has seven core tenets: (i) collect multimodal imaging data from many subjects; (ii) acquire data at high spatial and temporal resolution; (iii) preprocess data to minimize distortions, blurring and temporal artifacts; (iv) represent data using the natural geometry of cortical and subcortical structures; (v) accurately align corresponding brain areas across subjects and studies; (vi) analyze data using neurobiologically accurate brain parcellations; and (vii) share published data via user-friendly databases. We illustrate the HCP-style paradigm using existing HCP data sets and provide guidance for future research. Widespread adoption of this paradigm should accelerate progress in understanding the brain in health and disease.

Citation

Glasser, M. F., Smith, S. M., Marcus, D. S., Andersson, J. L., Auerbach, E. J., Behrens, T. E., …Van Essen, D. C. (2016). The Human Connectome Project's neuroimaging approach. Nature Neuroscience, 19(9), https://doi.org/10.1038/nn.4361

Journal Article Type	Article
Acceptance Date	Jul 18, 2016
Publication Date	Aug 26, 2016
Deposit Date	Apr 5, 2018
Publicly Available Date	Apr 5, 2018
Journal	Nature Neuroscience
Print ISSN	1097-6256
Electronic ISSN	1546-1726
Publisher	Nature Publishing Group
Peer Reviewed	Peer Reviewed
Volume	19
Issue	9
DOI	https://doi.org/10.1038/nn.4361
Keywords	Language; Neural circuits; Sensory processing
Public URL	https://nottingham-repository.worktribe.com/output/804345
Publisher URL	https://www.nature.com/articles/nn.4361