Six actions to improve detection of critical features for neuroimaging coordinate-based meta-analysis preparation. (June 2022)

• Record Type: Journal Article
• Authors: Manuello, Jordi; Costa, Tommaso; Cauda, Franco; Liloia, Donato
• Is Part Of: Neuroscience and biobehavioral reviews. Volume 137(2022)
• Publication Date: 2022-06
• Subjects: Systematic review -- Meta-analysis -- Guideline -- Quantitative summary -- Human brain mapping -- Neuroimaging -- Meta-data; Psychophysiology -- Periodicals; Human behavior -- Periodicals; Animal behavior -- Periodicals; Neurology -- Periodicals; Behavior -- Periodicals; Ethology -- Periodicals; Neurology -- Periodicals; Psychophysiologie -- Périodiques; Comportement humain -- Périodiques; Animaux -- Mœurs et comportement -- Périodiques; Neurologie -- Périodiques; Animal behavior; Human behavior; Neurology; Psychophysiology; Periodicals; Electronic journals; 573.8
• DOI: 10.1016/j.neubiorev.2022.104659
• Languages: English
• ISSNs: 0149-7634

Abstract

Abstract: Coordinate-based meta-analysis (CBMA) is a research strategy widely used in the field of human brain imaging. Although dedicated tools as BrainMap or Neurosynth had been developed in past years, some of the crucial steps necessary to identify and compose the dataset are still user-based, resulting in a not standardized approach to literature search, as well as in time-consuming and prone to errors procedures. In particular, this concern involves the assessment of voxel-wise whole brain analyses in contrast to ROI-based ones, and the identification of available lists of peaks of effect (i.e., x, y, z coordinates of the foci). Here, we propose six simple actions that can be undertaken by any researcher and by the publishing system, allowing to limit the risk of erroneous decisions on the inclusion of experimental data in the meta-analytic dataset. This straightforward and useful strategy would reduce possible bias in CBMA, therefore allowing to obtain more reliable results. Highlights: We propose six actions which can simplify data preparation for CBMA. These actions have to be undertaken by both the scientific community and the publishing system. This straightforward and useful strategy would reduce possible bias in CBMA.