Literature DB >> 20880670

Between- and within-scanner variability in the CaliBrain study n-back cognitive task.

Victoria Gradin1, Viktoria-Eleni Gountouna, Gordon Waiter, Trevor S Ahearn, David Brennan, Barrie Condon, Ian Marshall, David J McGonigle, Alison D Murray, Heather Whalley, Jonathan Cavanagh, Donald Hadley, Katherine Lymer, Andrew McIntosh, Thomas William Moorhead, Dominic Job, Joanna Wardlaw, Stephen M Lawrie, John Douglas Steele.   

Abstract

Psychiatric neuroimaging techniques are likely to improve understanding of the brain in health and disease, but studies tend to be small, based in one imaging centre and of unclear generalisability. Multicentre studies have great appeal but face problems if functional magnetic resonance imaging (fMRI) data from different centres are to be combined. Fourteen healthy volunteers had two brain scans on different days at three scanners. Considerable effort was first made to use similar scanning sequences and standardise task implementation across centres. The n-back cognitive task was used to investigate between- and within-scanner reproducibility and reliability. Both the functional imaging and behavioural results were in good accord with the existing literature. We found no significant differences in the activation/deactivation maps between scanners, or between repeat visits to the same scanners. Between- and within-scanner reproducibility and reliability was very similar. However, the smoothness of images from the scanners differed, suggesting that smoothness equalization might further reduce inter-scanner variability. Our results for the n-back task suggest it is possible to acquire fMRI data from different scanners which allows pooling across centres, when the same field strength scanners are used and scanning sequences and paradigm implementations are standardised.
Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Mesh:

Year:  2010        PMID: 20880670     DOI: 10.1016/j.pscychresns.2010.08.010

Source DB:  PubMed          Journal:  Psychiatry Res        ISSN: 0165-1781            Impact factor:   3.222


  12 in total

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Journal:  Hum Brain Mapp       Date:  2016-03-09       Impact factor: 5.038

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4.  Brain-derived neurotrophic factor Val66Met genotype and ovarian steroids interactively modulate working memory-related hippocampal function in women: a multimodal neuroimaging study.

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6.  Reliability of functional magnetic resonance imaging activation during working memory in a multi-site study: analysis from the North American Prodrome Longitudinal Study.

Authors:  Jennifer K Forsyth; Sarah C McEwen; Dylan G Gee; Carrie E Bearden; Jean Addington; Brad Goodyear; Kristin S Cadenhead; Heline Mirzakhanian; Barbara A Cornblatt; Doreen M Olvet; Daniel H Mathalon; Thomas H McGlashan; Diana O Perkins; Aysenil Belger; Larry J Seidman; Heidi W Thermenos; Ming T Tsuang; Theo G M van Erp; Elaine F Walker; Stephan Hamann; Scott W Woods; Maolin Qiu; Tyrone D Cannon
Journal:  Neuroimage       Date:  2014-04-13       Impact factor: 6.556

7.  Statistical harmonization corrects site effects in functional connectivity measurements from multi-site fMRI data.

Authors:  Meichen Yu; Kristin A Linn; Philip A Cook; Mary L Phillips; Melvin McInnis; Maurizio Fava; Madhukar H Trivedi; Myrna M Weissman; Russell T Shinohara; Yvette I Sheline
Journal:  Hum Brain Mapp       Date:  2018-07-01       Impact factor: 5.038

8.  fMRI reliability: influences of task and experimental design.

Authors:  Craig M Bennett; Michael B Miller
Journal:  Cogn Affect Behav Neurosci       Date:  2013-12       Impact factor: 3.526

9.  Brain-Age Prediction Using Shallow Machine Learning: Predictive Analytics Competition 2019.

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Journal:  Front Psychiatry       Date:  2020-12-02       Impact factor: 4.157

Review 10.  Whole Brain Magnetic Resonance Image Atlases: A Systematic Review of Existing Atlases and Caveats for Use in Population Imaging.

Authors:  David Alexander Dickie; Susan D Shenkin; Devasuda Anblagan; Juyoung Lee; Manuel Blesa Cabez; David Rodriguez; James P Boardman; Adam Waldman; Dominic E Job; Joanna M Wardlaw
Journal:  Front Neuroinform       Date:  2017-01-19       Impact factor: 4.081

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