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Improved estimation of subject-level functional connectivity using full and partial correlation with empirical Bayes shrinkage

  • Published:2018-05 Issue: Volume:172 Page:478-491
  • ISSN:1053-8119
  • Container-title:NeuroImage
  • language:en
  • Short-container-title:NeuroImage

Author:

Mejia Amanda F.,Nebel Mary Beth,Barber Anita D.,Choe Ann S.,Pekar James J.,Caffo Brian S.,Lindquist Martin A.

Funder

NIH Institutes and Centers

McDonnell Center for Systems Neuroscience at Washington University

NIH

National Institute of Biomedical Imaging and Bioengineering

National Institute of Mental Health

Craig H. Neilsen Foundation

Publisher

Elsevier BV

Subject

Cognitive Neuroscience,Neurology

Reference58 articles.

1. Deriving reproducible biomarkers from multi-site resting-state data: an autism-based example;Abraham;NeuroImage,2017

2. Factors affecting characterization and localization of interindividual differences in functional connectivity using MRI;Airan;Hum. Brain Mapp.,2016

3. Tracking whole-brain connectivity dynamics in the resting state;Allen;Cerebr. Cortex,2014

4. Reproducibility of single-subject functional connectivity measurements;Anderson;Am. J. Neuroradiol.,2011

5. Group comparison of resting-state fMRI data using multi-subject ICA and dual regression;Beckmann;NeuroImage,2009

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