Evidence map›Paper›PMID 37528293›Full record

ArticleBehavior research methods2024

CBMAT: a MATLAB toolbox for data preparation and post hoc analyses in neuroimaging meta-analyses.

Jordi Manuello, Donato Liloia, Annachiara Crocetta, Franco Cauda, Tommaso Costa

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Article in Behavior research methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Jordi ManuelloGCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy.
Donato LiloiaGCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy. donato.liloia@unito.it.
Annachiara CrocettaGCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy.
Franco CaudaGCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy.
Tommaso CostaGCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coordinate-based meta-analysis (CBMA) is a powerful technique in the field of human brain imaging research. Due to its intense usage, several procedures for data preparation and post hoc analyses have been proposed so far. However, these steps are often performed manually by the researcher, and are therefore potentially prone to error and time-consuming. We hence developed the Coordinate-Based Meta-Analyses Toolbox (CBMAT) to provide a suite of user-friendly and automated MATLAB® functions allowing one to perform all these procedures in a fast, reproducible and reliable way. Besides the description of the code, in the present paper we also provide an annotated example of using CBMAT on a dataset including 34 experiments. CBMAT can therefore substantially improve the way data are handled when performing CBMAs. The code can be downloaded from https://github.com/Jordi-Manuello/CBMAT.git .

Indexed as

Meta-Analysis as TopicNeuroimagingSoftwareBrainHumansActivation likelihood estimationBrainMapCoordinate-based meta-analysesData preparationMATLABQuantitative synthesisValidation analyses

Identifiers

PMID37528293
PMCPMC11519206

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.