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Ten simple rules for neuroimaging meta-analysis

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Müller, Veronika I., Cieslik, Edna C., Laird, Angela R., Fox, Peter T., Radua, Joaquim, Mataix-Cols, David, Tench, Christopher R., Yarkoni, Tal, Nichols, Thomas E., Turkeltaub, Peter E., Wager, Tor D. and Eickhoff, Simon B. (2017) Ten simple rules for neuroimaging meta-analysis. Neuroscience and biobehavioral reviews, 84 . pp. 151-161. doi:10.1016/j.neubiorev.2017.11.012 ISSN 1873-7528.

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Official URL: https://doi.org/10.1016/j.neubiorev.2017.11.012

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Abstract

Neuroimaging has evolved into a widely used method to investigate the functional neuroanatomy, brain-behaviour relationships, and pathophysiology of brain disorders, yielding a literature of more than 30,000 papers. With such an explosion of data, it is increasingly difficult to sift through the literature and distinguish spurious from replicable findings. Furthermore, due to the large number of studies, it is challenging to keep track of the wealth of findings. A variety of meta-analytical methods (coordinate-based and image-based) have been developed to help summarise and integrate the vast amount of data arising from neuroimaging studies. However, the field lacks specific guidelines for the conduct of such meta-analyses. Based on our combined experience, we propose best-practice recommendations that researchers from multiple disciplines may find helpful. In addition, we provide specific guidelines and a checklist that will hopefully improve the transparency, traceability, replicability and reporting of meta-analytical results of neuroimaging data. [Abstract copyright: Copyright © 2017. Published by Elsevier Ltd.]

Item Type: Journal Article
Subjects: R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
Divisions: Faculty of Science, Engineering and Medicine > Science > Statistics
SWORD Depositor: Library Publications Router
Library of Congress Subject Headings (LCSH): Neurosciences -- Methodology, Neuroanatomy, Human behavior, Physiology, Pathological, Tomography, Emission, Magnetic resonance imaging, Meta-analysis
Journal or Publication Title: Neuroscience and biobehavioral reviews
Publisher: Elsevier
ISSN: 1873-7528
Official Date: January 2017
Dates:
DateEvent
January 2017Published
24 November 2017Available
20 November 2017Accepted
Volume: 84
Page Range: pp. 151-161
DOI: 10.1016/j.neubiorev.2017.11.012
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access (Creative Commons)
Date of first compliant deposit: 2 October 2018
Date of first compliant Open Access: 2 October 2018
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
EI 816/4-1, LA 3071/3-1[DFG] Deutsche Forschungsgemeinschafthttp://dx.doi.org/10.13039/501100001659
R01-MH07445National Institute of Mental Healthhttp://dx.doi.org/10.13039/100000025
Helmholtz Portfolio Theme “Supercomputing and Modelling for the Human Brain”Forschungszentrum Jülichhttp://dx.doi.org/10.13039/501100003163
7202070 (HBP SGA1)H2020 European Research Councilhttp://dx.doi.org/10.13039/100010663
100309/Z/12/ZWellcome Trusthttp://dx.doi.org/10.13039/100010269
R01 NS075066-01A[NIHR] National Institute for Health Researchhttp://dx.doi.org/10.13039/501100000272
R01DA035484[NIHR] National Institute for Health Researchhttp://dx.doi.org/10.13039/501100000272
2R01MH076136[NIHR] National Institute for Health Researchhttp://dx.doi.org/10.13039/501100000272

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