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@ARTICLE{Tahmasian:864413,
author = {Tahmasian, Masoud and Sepehry, Amir A. and Samea, Fateme
and Khodadadifar, Tina and Soltaninejad, Zahra and
Javaheripour, Nooshin and Khazaie, Habibolah and Zarei,
Mojtaba and Eickhoff, Simon B. and Eickhoff, Claudia R.},
title = {{P}ractical recommendations to conduct a neuroimaging
meta‐analysis for neuropsychiatric disorders},
journal = {Human brain mapping},
volume = {40},
number = {17},
issn = {1097-0193},
address = {New York, NY},
publisher = {Wiley-Liss},
reportid = {FZJ-2019-04197},
pages = {5142-5154},
year = {2019},
note = {AAS was not financially founded for this project. S.B.E. is
supported by the Deutsche Forschungsgemeinschaft (EI
816/11‐1), the National Institute of Mental Health
(R01‐MH074457), the Helmholtz Portfolio Theme
“Supercomputing and Modeling for the Human Brain” and
the European Union's Horizon 2020 Research and Innovation
Programme under grant agreement no. 7202070 (HBP SGA1) and
under grant agreement no. 785907 (HBP SGA2).},
abstract = {Over the past decades, neuroimaging has become widely used
to investigate structural and functional brain abnormality
in neuropsychiatric disorders. The results of individual
neuroimaging studies, however, are frequently inconsistent
due to small and heterogeneous samples, analytical
flexibility, and publication bias toward positive findings.
To consolidate the emergent findings toward clinically
useful insight, meta-analyses have been developed to
integrate the results of studies and identify areas that are
consistently involved in pathophysiology of particular
neuropsychiatric disorders. However, it should be considered
that the results of meta-analyses could also be divergent
due to heterogeneity in search strategy, selection criteria,
imaging modalities, behavioral tasks, number of experiments,
data organization methods, and statistical analysis with
different multiple comparison thresholds. Following an
introduction to the problem and the concepts of quantitative
summaries of neuroimaging findings, we propose practical
recommendations for clinicians and researchers for
conducting transparent and methodologically sound
neuroimaging meta-analyses. This should help to consolidate
the search for convergent regional brain abnormality in
neuropsychiatric disorders.},
cin = {INM-7 / INM-1},
ddc = {610},
cid = {I:(DE-Juel1)INM-7-20090406 / I:(DE-Juel1)INM-1-20090406},
pnm = {574 - Theory, modelling and simulation (POF3-574) / SMHB -
Supercomputing and Modelling for the Human Brain
(HGF-SMHB-2013-2017) / HBP SGA2 - Human Brain Project
Specific Grant Agreement 2 (785907)},
pid = {G:(DE-HGF)POF3-574 / G:(DE-Juel1)HGF-SMHB-2013-2017 /
G:(EU-Grant)785907},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:31379049},
UT = {WOS:000478841400001},
doi = {10.1002/hbm.24746},
url = {https://juser.fz-juelich.de/record/864413},
}