Literature DB >> 28599964

Resting-state fMRI correlations: From link-wise unreliability to whole brain stability.

Mario Pannunzi1, Rikkert Hindriks2, Ruggero G Bettinardi2, Elisabeth Wenger3, Nina Lisofsky4, Johan Martensson5, Oisin Butler3, Elisa Filevich6, Maxi Becker4, Martyna Lochstet3, Simone Kühn4, Gustavo Deco7.   

Abstract

The functional architecture of spontaneous BOLD fluctuations has been characterized in detail by numerous studies, demonstrating its potential relevance as a biomarker. However, the systematic investigation of its consistency is still in its infancy. Here, we analyze within- and between-subject variability and test-retest reliability of resting-state functional connectivity (FC) in a unique data set comprising multiple fMRI scans (42) from 5 subjects, and 50 single scans from 50 subjects. We adopt a statistical framework that enables us to identify different sources of variability in FC. We show that the low reliability of single links can be significantly improved by using multiple scans per subject. Moreover, in contrast to earlier studies, we show that spatial heterogeneity in FC reliability is not significant. Finally, we demonstrate that despite the low reliability of individual links, the information carried by the whole-brain FC matrix is robust and can be used as a functional fingerprint to identify individual subjects from the population.
Copyright © 2017 Elsevier Inc. All rights reserved.

Mesh:

Year:  2017        PMID: 28599964     DOI: 10.1016/j.neuroimage.2017.06.006

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  26 in total

1.  Reliable local dynamics in the brain across sessions are revealed by whole-brain modeling of resting state activity.

Authors:  Patricio Donnelly-Kehoe; Victor M Saenger; Nina Lisofsky; Simone Kühn; Morten L Kringelbach; Jens Schwarzbach; Ulman Lindenberger; Gustavo Deco
Journal:  Hum Brain Mapp       Date:  2019-03-18       Impact factor: 5.038

2.  Precision Functional Mapping of Individual Human Brains.

Authors:  Evan M Gordon; Timothy O Laumann; Adrian W Gilmore; Dillan J Newbold; Deanna J Greene; Jeffrey J Berg; Mario Ortega; Catherine Hoyt-Drazen; Caterina Gratton; Haoxin Sun; Jacqueline M Hampton; Rebecca S Coalson; Annie L Nguyen; Kathleen B McDermott; Joshua S Shimony; Abraham Z Snyder; Bradley L Schlaggar; Steven E Petersen; Steven M Nelson; Nico U F Dosenbach
Journal:  Neuron       Date:  2017-07-27       Impact factor: 17.173

3.  Connectome-based predictive modeling of attention: Comparing different functional connectivity features and prediction methods across datasets.

Authors:  Kwangsun Yoo; Monica D Rosenberg; Wei-Ting Hsu; Sheng Zhang; Chiang-Shan R Li; Dustin Scheinost; R Todd Constable; Marvin M Chun
Journal:  Neuroimage       Date:  2017-11-06       Impact factor: 6.556

4.  Multivariate approaches improve the reliability and validity of functional connectivity and prediction of individual behaviors.

Authors:  Kwangsun Yoo; Monica D Rosenberg; Stephanie Noble; Dustin Scheinost; R Todd Constable; Marvin M Chun
Journal:  Neuroimage       Date:  2019-04-27       Impact factor: 6.556

5.  Functional Brain Networks Are Dominated by Stable Group and Individual Factors, Not Cognitive or Daily Variation.

Authors:  Caterina Gratton; Timothy O Laumann; Ashley N Nielsen; Deanna J Greene; Evan M Gordon; Adrian W Gilmore; Steven M Nelson; Rebecca S Coalson; Abraham Z Snyder; Bradley L Schlaggar; Nico U F Dosenbach; Steven E Petersen
Journal:  Neuron       Date:  2018-04-18       Impact factor: 17.173

6.  Methamphetamine acutely alters frontostriatal resting state functional connectivity in healthy young adults.

Authors:  Jessica Weafer; Kathryne Van Hedger; Sarah K Keedy; Nkemdilim Nwaokolo; Harriet de Wit
Journal:  Addict Biol       Date:  2019-05-16       Impact factor: 4.280

7.  The individual functional connectome is unique and stable over months to years.

Authors:  Corey Horien; Xilin Shen; Dustin Scheinost; R Todd Constable
Journal:  Neuroimage       Date:  2019-02-02       Impact factor: 6.556

8.  The Lifespan Human Connectome Project in Development: A large-scale study of brain connectivity development in 5-21 year olds.

Authors:  Leah H Somerville; Susan Y Bookheimer; Randy L Buckner; Gregory C Burgess; Sandra W Curtiss; Mirella Dapretto; Jennifer Stine Elam; Michael S Gaffrey; Michael P Harms; Cynthia Hodge; Sridhar Kandala; Erik K Kastman; Thomas E Nichols; Bradley L Schlaggar; Stephen M Smith; Kathleen M Thomas; Essa Yacoub; David C Van Essen; Deanna M Barch
Journal:  Neuroimage       Date:  2018-08-22       Impact factor: 6.556

9.  Extending the Human Connectome Project across ages: Imaging protocols for the Lifespan Development and Aging projects.

Authors:  Michael P Harms; Leah H Somerville; Beau M Ances; Jesper Andersson; Deanna M Barch; Matteo Bastiani; Susan Y Bookheimer; Timothy B Brown; Randy L Buckner; Gregory C Burgess; Timothy S Coalson; Michael A Chappell; Mirella Dapretto; Gwenaëlle Douaud; Bruce Fischl; Matthew F Glasser; Douglas N Greve; Cynthia Hodge; Keith W Jamison; Saad Jbabdi; Sridhar Kandala; Xiufeng Li; Ross W Mair; Silvia Mangia; Daniel Marcus; Daniele Mascali; Steen Moeller; Thomas E Nichols; Emma C Robinson; David H Salat; Stephen M Smith; Stamatios N Sotiropoulos; Melissa Terpstra; Kathleen M Thomas; M Dylan Tisdall; Kamil Ugurbil; Andre van der Kouwe; Roger P Woods; Lilla Zöllei; David C Van Essen; Essa Yacoub
Journal:  Neuroimage       Date:  2018-09-24       Impact factor: 6.556

10.  Effect sizes and test-retest reliability of the fMRI-based neurologic pain signature.

Authors:  Xiaochun Han; Yoni K Ashar; Philip Kragel; Bogdan Petre; Victoria Schelkun; Lauren Y Atlas; Luke J Chang; Marieke Jepma; Leonie Koban; Elizabeth A Reynolds Losin; Mathieu Roy; Choong-Wan Woo; Tor D Wager
Journal:  Neuroimage       Date:  2021-12-20       Impact factor: 6.556

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