GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy.
FOCUS Lab, Department of Psychology, University of Turin, Turin, Italy.
Behav Res Methods. 2024 Aug;56(5):4325-4335. doi: 10.3758/s13428-023-02185-3. Epub 2023 Aug 1.
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 .
基于坐标的荟萃分析(CBMA)是人类大脑成像研究领域的一种强大技术。由于其广泛的应用,迄今为止已经提出了几种用于数据准备和事后分析的程序。然而,这些步骤通常由研究人员手动执行,因此可能容易出错且耗时。因此,我们开发了基于坐标的荟萃分析工具箱(CBMAT),提供了一套用户友好且自动化的 MATLAB®函数,可快速、可重复且可靠地执行所有这些步骤。除了代码的描述外,在本文中,我们还提供了一个使用 CBMAT 对包含 34 个实验的数据集的注释示例。因此,CBMAT 可以大大改善执行 CBMA 时处理数据的方式。代码可以从 https://github.com/Jordi-Manuello/CBMAT.git 下载。