Literature DB >> 33615097

Test-retest reliability of the human functional connectome over consecutive days: identifying highly reliable portions and assessing the impact of methodological choices.

Scott L Tozzi1, Scott L Fleming2, Zachary D Taylor3, Cooper D Raterink3, Leanne M Williams1.   

Abstract

Countless studies have advanced our understanding of the human brain and its organization by using functional magnetic resonance imaging (fMRI) to derive network representations of human brain function. However, we do not know to what extent these "functional connectomes" are reliable over time. In a large public sample of healthy participants (N = 833) scanned on two consecutive days, we assessed the test-retest reliability of fMRI functional connectivity and the consequences on reliability of three common sources of variation in analysis workflows: atlas choice, global signal regression, and thresholding. By adopting the intraclass correlation coefficient as a metric, we demonstrate that only a small portion of the functional connectome is characterized by good (6-8%) to excellent (0.08-0.14%) reliability. Connectivity between prefrontal, parietal, and temporal areas is especially reliable, but also average connectivity within known networks has good reliability. In general, while unreliable edges are weak, reliable edges are not necessarily strong. Methodologically, reliability of edges varies between atlases, global signal regression decreases reliability for networks and most edges (but increases it for some), and thresholding based on connection strength reduces reliability. Focusing on the reliable portion of the connectome could help quantify brain trait-like features and investigate individual differences using functional neuroimaging.
© 2020 Massachusetts Institute of Technology.

Entities:  

Keywords:  Functional connectivity; Reliability; Resting state; fMRI

Year:  2020        PMID: 33615097      PMCID: PMC7888485          DOI: 10.1162/netn_a_00148

Source DB:  PubMed          Journal:  Netw Neurosci        ISSN: 2472-1751


  46 in total

Review 1.  Intraclass correlations: uses in assessing rater reliability.

Authors:  P E Shrout; J L Fleiss
Journal:  Psychol Bull       Date:  1979-03       Impact factor: 17.737

Review 2.  Test-retest reliabilities of resting-state FMRI measurements in human brain functional connectomics: a systems neuroscience perspective.

Authors:  Xi-Nian Zuo; Xiu-Xia Xing
Journal:  Neurosci Biobehav Rev       Date:  2014-05-27       Impact factor: 8.989

3.  The reliability paradox: Why robust cognitive tasks do not produce reliable individual differences.

Authors:  Craig Hedge; Georgina Powell; Petroc Sumner
Journal:  Behav Res Methods       Date:  2018-06

Review 4.  Task-based dynamic functional connectivity: Recent findings and open questions.

Authors:  Javier Gonzalez-Castillo; Peter A Bandettini
Journal:  Neuroimage       Date:  2017-08-03       Impact factor: 6.556

Review 5.  Network neuroscience.

Authors:  Danielle S Bassett; Olaf Sporns
Journal:  Nat Neurosci       Date:  2017-02-23       Impact factor: 24.884

6.  Functional System and Areal Organization of a Highly Sampled Individual Human Brain.

Authors:  Timothy O Laumann; Evan M Gordon; Babatunde Adeyemo; Abraham Z Snyder; Sung Jun Joo; Mei-Yen Chen; Adrian W Gilmore; Kathleen B McDermott; Steven M Nelson; Nico U F Dosenbach; Bradley L Schlaggar; Jeanette A Mumford; Russell A Poldrack; Steven E Petersen
Journal:  Neuron       Date:  2015-07-23       Impact factor: 17.173

7.  The Contribution of Network Organization and Integration to the Development of Cognitive Control.

Authors:  Scott Marek; Kai Hwang; William Foran; Michael N Hallquist; Beatriz Luna
Journal:  PLoS Biol       Date:  2015-12-29       Impact factor: 8.029

8.  Quantifying person-level brain network functioning to facilitate clinical translation.

Authors:  T M Ball; A N Goldstein-Piekarski; J M Gatt; L M Williams
Journal:  Transl Psychiatry       Date:  2017-10-17       Impact factor: 6.222

9.  Ridding fMRI data of motion-related influences: Removal of signals with distinct spatial and physical bases in multiecho data.

Authors:  Jonathan D Power; Mark Plitt; Stephen J Gotts; Prantik Kundu; Valerie Voon; Peter A Bandettini; Alex Martin
Journal:  Proc Natl Acad Sci U S A       Date:  2018-02-12       Impact factor: 11.205

Review 10.  The frontoparietal network: function, electrophysiology, and importance of individual precision mapping.

Authors:  Scott Marek; Nico U F Dosenbach
Journal:  Dialogues Clin Neurosci       Date:  2018-06       Impact factor: 5.986

View more
  1 in total

1.  Relating whole-brain functional connectivity to self-reported negative emotion in a large sample of young adults using group regularized canonical correlation analysis.

Authors:  Leonardo Tozzi; Elena Tuzhilina; Matthew F Glasser; Trevor J Hastie; Leanne M Williams
Journal:  Neuroimage       Date:  2021-05-02       Impact factor: 7.400

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.