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@ARTICLE{Mller:840398,
author = {Müller, Veronika and Cieslik, Edna and Laird, Angela R and
Fox, Peter T and Radua, Joaquim and Mataix-Cols, David and
Tench, Christopher R and Yarkoni, Tal and Nichols, Thomas E
and Turkeltaub, Peter E and Wager, Tor D and Eickhoff,
Simon},
title = {{T}en simple rules for neuroimaging meta-analysis},
journal = {Neuroscience $\&$ biobehavioral reviews},
volume = {84},
issn = {0149-7634},
address = {Amsterdam [u.a.]},
publisher = {Elsevier Science},
reportid = {FZJ-2017-07931},
pages = {151–161},
year = {2017},
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.},
cin = {INM-7},
ddc = {150},
cid = {I:(DE-Juel1)INM-7-20090406},
pnm = {574 - Theory, modelling and simulation (POF3-574) / HBP
SGA1 - Human Brain Project Specific Grant Agreement 1
(720270)},
pid = {G:(DE-HGF)POF3-574 / G:(EU-Grant)720270},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:29180258},
UT = {WOS:000419419000012},
doi = {10.1016/j.neubiorev.2017.11.012},
url = {https://juser.fz-juelich.de/record/840398},
}