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Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI
Published on: November 27, 2019
Practical recommendations to conduct a neuroimaging meta-analysis for neuropsychiatric disorders
Masoud Tahmasian1, Amir A Sepehry2, Fateme Samea3
1Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran.
None:
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.
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