Literature DB >> 19166942

Measuring fMRI reliability with the intra-class correlation coefficient.

Alejandro Caceres1, Deanna L Hall, Fernando O Zelaya, Steven C R Williams, Mitul A Mehta.   

Abstract

The intra-class class correlation coefficient (ICC) is a prominent statistic to measure test-retest reliability of fMRI data. It can be used to address the question of whether regions of high group activation in a first scan session will show preserved subject differentiability in a second session. With this purpose, we present a method that extends voxel-wise ICC analysis. We show that voxels with high group activation have more probability of being reliable, if a subsequent session is performed, than typical voxels across the brain or across white matter. We also find that the existence of some voxels with high ICC but low group activation can be explained by stable signals across sessions that poorly fit the HRF model. At a region of interest level, we show that our voxel-wise ICC calculation is more robust than previous implementations under variations of smoothing and cluster size. The method also allows formal comparisons between the reliabilities of given brain regions; aimed at establishing which ROIs discriminate best between individuals. The method is applied to an auditory and a verbal working memory task. A reliability toolbox for SPM5 is provided at http://brainmap.co.uk.

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Year:  2008        PMID: 19166942     DOI: 10.1016/j.neuroimage.2008.12.035

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


  117 in total

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Authors:  Fernando O Zelaya; Evangelos Zois; Christopher Muller-Pollard; David J Lythgoe; Sarah Lee; Caroline Andrews; Trevor Smart; Patricia Conrod; William Vennart; Steven C R Williams; Mitul A Mehta; Laurence J Reed
Journal:  MAGMA       Date:  2011-11-24       Impact factor: 2.310

2.  A comprehensive testing protocol for MRI neuroanatomical segmentation techniques: Evaluation of a novel lateral ventricle segmentation method.

Authors:  Matthew J Kempton; Tracy S A Underwood; Simon Brunton; Floris Stylios; Anne Schmechtig; Ulrich Ettinger; Marcus S Smith; Simon Lovestone; William R Crum; Sophia Frangou; Steven C R Williams; Andrew Simmons
Journal:  Neuroimage       Date:  2011-07-30       Impact factor: 6.556

3.  Test-retest reliability of effective connectivity in the face perception network.

Authors:  Stefan Frässle; Frieder Michel Paulus; Sören Krach; Andreas Jansen
Journal:  Hum Brain Mapp       Date:  2015-11-27       Impact factor: 5.038

4.  Test-retest reliability of an fMRI paradigm for studies of cardiovascular reactivity.

Authors:  Lei K Sheu; J Richard Jennings; Peter J Gianaros
Journal:  Psychophysiology       Date:  2012-05-17       Impact factor: 4.016

5.  Reliability measures of functional magnetic resonance imaging in a longitudinal evaluation of mild cognitive impairment.

Authors:  Theodore P Zanto; Judy Pa; Adam Gazzaley
Journal:  Neuroimage       Date:  2013-09-07       Impact factor: 6.556

6.  Test-retest reliability of the novel 5-HT1B receptor PET radioligand [11C]P943.

Authors:  Aybala Saricicek; Jason Chen; Beata Planeta; Barbara Ruf; Kalyani Subramanyam; Kathleen Maloney; David Matuskey; David Labaree; Lorenz Deserno; Alexander Neumeister; John H Krystal; Jean-Dominique Gallezot; Yiyun Huang; Richard E Carson; Zubin Bhagwagar
Journal:  Eur J Nucl Med Mol Imaging       Date:  2014-11-27       Impact factor: 9.236

7.  Intraclass correlation: Improved modeling approaches and applications for neuroimaging.

Authors:  Gang Chen; Paul A Taylor; Simone P Haller; Katharina Kircanski; Joel Stoddard; Daniel S Pine; Ellen Leibenluft; Melissa A Brotman; Robert W Cox
Journal:  Hum Brain Mapp       Date:  2017-12-07       Impact factor: 5.038

Review 8.  Event-Related Potentials as Biomarkers of Behavior Change Mechanisms in Substance Use Disorder Treatment.

Authors:  Rebecca J Houston; Nicolas J Schlienz
Journal:  Biol Psychiatry Cogn Neurosci Neuroimaging       Date:  2017-09-23

9.  Repeatability of language fMRI lateralization and localization metrics in brain tumor patients.

Authors:  Shruti Agarwal; Jun Hua; Haris I Sair; Sachin Gujar; Chetan Bettegowda; Hanzhang Lu; Jay J Pillai
Journal:  Hum Brain Mapp       Date:  2018-08-04       Impact factor: 5.038

10.  Genetically determined measures of striatal D2 signaling predict prefrontal activity during working memory performance.

Authors:  Alessandro Bertolino; Paolo Taurisano; Nicola Marco Pisciotta; Giuseppe Blasi; Leonardo Fazio; Raffaella Romano; Barbara Gelao; Luciana Lo Bianco; Madia Lozupone; Annabella Di Giorgio; Grazia Caforio; Fabio Sambataro; Artor Niccoli-Asabella; Audrey Papp; Gianluca Ursini; Lorenzo Sinibaldi; Teresa Popolizio; Wolfgang Sadee; Giuseppe Rubini
Journal:  PLoS One       Date:  2010-02-22       Impact factor: 3.240

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