The Human Connectome Project's neuroimaging approach release_wwg4h7gmw5eshc5bc3zsmt6zmy

by Matthew F Glasser, Stephen 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 N Sotiropoulos (+4 others)

Published in Nature Neuroscience by Springer Nature.

2016   Volume 19, Issue 9, p1175-1187

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.
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Type  article-journal
Stage   published
Date   2016-08-26
Language   en ?
DOI  10.1038/nn.4361
PubMed  27571196
PMC  PMC6172654
Wikidata  Q36115766
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ISSN-L:  1097-6256
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