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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},
}