Connectome Inference
Connectome Inference is a computational method that distinguishes itself by reconstructing the complete set of neural connections within a nervous system from empirical neuroimaging or anatomical data.
43
Publications
3K
Citations
218
Authors
126
Institutions
Publications per year
2017–2026
32
Parents
43
A symmetric multivariate leakage correction for MEG connectomes
Giles L. Colclough, Matthew J. Brookes, Stephen M. Smith et al. · NeuroImage · 2015 · 490 citations · Full text
Discovering dynamic brain networks from big data in rest and task
Diego Vidaurre, Romesh Abeysuriya, Robert Becker et al. · NeuroImage · 2017 · 392 citations · Full text
Evaluation and statistical inference for human connectomes
Franco Pestilli, Jason D. Yeatman, Ariel Rokem et al. · Nature Methods · 2014 · 286 citations · Full text
High-resolution data-driven model of the mouse connectome
Joseph E. Knox, Kameron Decker Harris, Nile Graddis et al. · Network Neuroscience · 2018 · 129 citations · Full text
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126

Johns Hopkins University
Baltimore, United States
4 h-index
19 publications
625 citations
University College London
London, United Kingdom
4 h-index
5 publications
228 citations
Wellcome Centre for Integrative Neuroimaging
Oxford, United Kingdom
3 h-index
16 publications
5K citations
University of Washington
Seattle, United States
3 h-index
4 publications
184 citations
University of Oxford
Oxford, United Kingdom
2 h-index
10 publications
4.2K citations
Massachusetts Institute of Technology
Cambridge, United States
2 h-index
2 publications
99 citations
Yale University
New Haven, United States
2 h-index
5 publications
417 citations
Allen Institute
Seattle, United States
2 h-index
14 publications
1.1K citations
1–8 of 126
7 publications · 1.2K citations
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4 publications · 245 citations
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Repository · 4 publications · 65 citations
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LNCS · Book series · 3 publications · 83 citations
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NetNeuro · 3 publications · 164 citations
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