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Review
. 2019 Dec 1;40(17):5142-5154.
doi: 10.1002/hbm.24746. Epub 2019 Aug 4.

Practical recommendations to conduct a neuroimaging meta-analysis for neuropsychiatric disorders

Masoud Tahmasian  1 , Amir A Sepehry  2 , Fateme Samea  3 , Tina Khodadadifar  4 , Zahra Soltaninejad  3 , Nooshin Javaheripour  1 , Habibolah Khazaie  5 , Mojtaba Zarei  1 , Simon B Eickhoff  6   7 , Claudia R Eickhoff  7   8
Affiliations
Review

Practical recommendations to conduct a neuroimaging meta-analysis for neuropsychiatric disorders

Masoud Tahmasian et al. Hum Brain Mapp. .

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.

Keywords: guideline; meta-analysis; neuroimaging; neuropsychiatric disorders; systematic review.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
This shows evidence synthesis on a continuum based on the extent of statistical data analysis and applications [Color figure can be viewed at http://wileyonlinelibrary.com]
Figure 2
Figure 2
(a) Number of published neuroimaging meta‐analysis based on all applied methods in PubMed. (b) Number of published neuroimaging meta‐analysis per year in PubMed. ALE, activation likelihood estimation; GPR, Gaussian‐process regression; KDR, Kernel density analysis; PVM, parametric voxel‐based meta‐analysis; SDM, signed differential mapping [Color figure can be viewed at http://wileyonlinelibrary.com]
Figure 3
Figure 3
Flowchart illustrating the main steps of performing a neuroimaging meta‐analysis [Color figure can be viewed at http://wileyonlinelibrary.com]
See this image and copyright information in PMC

References

    1. Borenstein, M. , Hedges, L. V. , Higgins, J. P. T. , & Rothstein, H. R. (2009). Introduction to meta‐analysis. Chichester, England: John Wiley & Sons.
    1. Brandl, F. , Avram, M. , Weise, B. , Shang, J. , Simoes, B. , Bertram, T. , … Sorg, C. (2019). Specific substantial dysconnectivity in schizophrenia: A transdiagnostic multimodal meta‐analysis of resting‐state functional and structural magnetic resonance imaging studies. Biological Psychiatry, 85, 573–583. - PubMed
    1. Brett, M. , Christoff, K. , Cusack, R. , & Lancaster, J. (2001). Using the Talairach atlas with the MNI template. NeuroImage, 13, 85.
    1. Button, K. S. , Ioannidis, J. P. , Mokrysz, C. , Nosek, B. A. , Flint, J. , Robinson, E. S. , & Munafo, M. R. (2013). Power failure: Why small sample size undermines the reliability of neuroscience. Nature Reviews. Neuroscience, 14, 365–376. - PubMed
    1. Carter, R. (2014). The brain book. London, England: Dorling Kindersley.

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