Open AccessImproving power in functional magnetic resonance imaging by moving beyond cluster-level inference
Author(s) -
Stephanie Noble,
Amanda F. Mejia,
Andrew Zalesky,
Linda C. Mayes
Publication year - 2022
Publication title -
proceedings of the national academy of sciences of the united states of america
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.2203020119
Subject(s) - inference , statistical power , computer science , connectome , resampling , neuroimaging , statistical inference , scale (ratio) , benchmarking , human connectome project , false discovery rate , functional magnetic resonance imaging , artificial intelligence , machine learning , data mining , statistics , psychology , functional connectivity , mathematics , neuroscience , biology , biochemistry , physics , quantum mechanics , marketing , business , gene