Imaging human connectomes at the macroscale
R. Cameron Craddock,Saad Jbabdi,Chao-Gan Yan,Chao-Gan Yan,Chao-Gan Yan,Joshua T. Vogelstein,F. Xavier Castellanos,F. Xavier Castellanos,Adriana Di Martino,Clare Kelly,Keith Heberlein,Stan Colcombe,Michael P. Milham,Michael P. Milham +13 more
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TLDR
This Review provides a survey of magnetic resonance imaging–based measurements of functional and structural connectivity and highlights emerging areas of development and inquiry and the importance of integrating structural and functional perspectives on brain architecture.Abstract:
At macroscopic scales, the human connectome comprises anatomically distinct brain areas, the structural pathways connecting them and their functional interactions. Annotation of phenotypic associations with variation in the connectome and cataloging of neurophenotypes promise to transform our understanding of the human brain. In this Review, we provide a survey of magnetic resonance imaging–based measurements of functional and structural connectivity. We highlight emerging areas of development and inquiry and emphasize the importance of integrating structural and functional perspectives on brain architecture.read more
Citations
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Journal ArticleDOI
Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268
Journal ArticleDOI
The WU-Minn Human Connectome Project: An Overview
TL;DR: Progress made during the first half of the Human Connectome Project project in refining the methods for data acquisition and analysis provides grounds for optimism that the HCP datasets and associated methods and software will become increasingly valuable resources for characterizing human brain connectivity and function, their relationship to behavior, and their heritability and genetic underpinnings.
Journal ArticleDOI
The challenge of mapping the human connectome based on diffusion tractography
Klaus H. Maier-Hein,Peter F. Neher,Jean-Christophe Houde,Marc-Alexandre Côté,Eleftherios Garyfallidis,Jidan Zhong,Maxime Chamberland,Fang-Cheng Yeh,Ying-Chia Lin,Qing Ji,Wilburn E. Reddick,John O. Glass,David Qixiang Chen,Yuanjing Feng,Chengfeng Gao,Ye Wu,Jieyan Ma,H Renjie,Qiang Li,Carl-Fredrik Westin,Samuel Deslauriers-Gauthier,J. Omar Ocegueda Gonzalez,Michael Paquette,Samuel St-Jean,Gabriel Girard,François Rheault,Jasmeen Sidhu,Chantal M. W. Tax,Fenghua Guo,Hamed Y. Mesri,Szabolcs David,Martijn Froeling,Anneriet M. Heemskerk,Alexander Leemans,Arnaud Boré,Basile Pinsard,Christophe Bedetti,Matthieu Desrosiers,Simona M. Brambati,Julien Doyon,Alessia Sarica,Roberta Vasta,Antonio Cerasa,Aldo Quattrone,Jason D. Yeatman,Ali R. Khan,Wes Hodges,Simon Alexander,David Romascano,Muhamed Barakovic,Anna Auría,Oscar Esteban,Alia Lemkaddem,Jean-Philippe Thiran,Hasan Ertan Cetingul,Benjamin L. Odry,Boris Mailhe,Mariappan S. Nadar,Fabrizio Pizzagalli,Gautam Prasad,Julio E. Villalon-Reina,Justin Galvis,Paul M. Thompson,Francisco De Santiago Requejo,Pedro Luque Laguna,Luis Miguel Lacerda,Rachel Barrett,Flavio Dell'Acqua,Marco Catani,Laurent Petit,Emmanuel Caruyer,Alessandro Daducci,Tim B. Dyrby,Tim Holland-Letz,Claus C. Hilgetag,Bram Stieltjes,Maxime Descoteaux +76 more
TL;DR: The encouraging finding that most state-of-the-art algorithms produce tractograms containing 90% of the ground truth bundles (to at least some extent) is reported, however, the same tractograms contain many more invalid than valid bundles, and half of these invalid bundles occur systematically across research groups.
Journal ArticleDOI
The hubs of the human connectome are generally implicated in the anatomy of brain disorders
Nicolas Crossley,Andrea Mechelli,Jessica Scott,Francesco Carletti,Peter T. Fox,Philip McGuire,Edward T. Bullmore +6 more
TL;DR: Using network analysis of DTI data from healthy volunteers, and meta-analyses of published MRI studies in 26 brain disorders, Crossley et al. show that lesions across disorders tend to be concentrated at hubs.
Journal ArticleDOI
Benchmarking of participant-level confound regression strategies for the control of motion artifact in studies of functional connectivity.
Rastko Ciric,Daniel H. Wolf,Jonathan D. Power,David R. Roalf,Graham L. Baum,Kosha Ruparel,Russell T. Shinohara,Mark A. Elliott,Simon B. Eickhoff,Christos Davatzikos,Ruben C. Gur,Raquel E. Gur,Danielle S. Bassett,Theodore D. Satterthwaite +13 more
TL;DR: A systematic evaluation of 14 participant‐level confound regression methods for functional connectivity highlights the heterogeneous efficacy of existing methods, and suggests that different confounding regression strategies may be appropriate in the context of specific scientific goals.
References
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Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain
Nathalie Tzourio-Mazoyer,B. Landeau,D. Papathanassiou,Fabrice Crivello,Octave Etard,Nicolas Delcroix,Bernard Mazoyer,Marc Joliot +7 more
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An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.
Rahul S. Desikan,Florent Ségonne,Bruce Fischl,Bruce Fischl,Brian T. Quinn,Bradford C. Dickerson,Deborah Blacker,Randy L. Buckner,Randy L. Buckner,Anders M. Dale,R. Paul Maguire,Bradley T. Hyman,Marilyn S. Albert,Ronald J. Killiany +13 more
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