Improving the Eligibility of Task-Based FMRI Studies for Meta-Analysis: A Review and Reporting Recommendations

Overview

Journal Neuroinformatics

Specialties Medical Informatics
Neurology

Date 2023 Nov 4

PMID 37924428

Authors

Freya Acar

Camille Maumet

Talia Heuten

Maya Vervoort

Han Bossier

Ruth Seurinck

Beatrijs Moerkerke

Affiliations

Soon will be listed here.

Abstract

Decisions made during the analysis or reporting of an fMRI study influence the eligibility of that study to be entered into a meta-analysis. In a meta-analysis, results of different studies on the same topic are combined. To combine the results, it is necessary that all studies provide equivalent pieces of information. However, in task-based fMRI studies we see a large variety in reporting styles. Several specific meta-analysis methods have been developed to deal with the reporting practices occurring in task-based fMRI studies, therefore each requiring a specific type of input. In this manuscript we provide an overview of the meta-analysis methods and the specific input they require. Subsequently we discuss how decisions made during the study influence the eligibility of a study for a meta-analysis and finally we formulate some recommendations about how to report an fMRI study so that it complies with as many meta-analysis methods as possible.

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