BayesFactorFMRI: Implementing Bayesian second-level fMRI analysis with multiple comparison correction and Bayesian meta-analysis of fMRI images with multiprocessing (V1.0.0)

BayesFactorFMRI is a tool developed with R and Python to allow neuroimaging researchers to conduct Bayesian second-level analysis of fMRI data and Bayesian meta-analysis of fMRI images with multiprocessing. This tool was developed to expedite computationally intensive Bayesian fMRI analysis through multiprocessing. Its GUI allows researchers who are not experts in computer programming to feasibly perform Bayesian fMRI analysis. BayesFactorFMRI is available via or GitHub for download. It would be widely reused by neuroimaging researchers who intend to analyse their fMRI data with Bayesian analysis with better sensitivity compared with classical analysis while saving time by distributing analysis tasks into multiple processes.

Please refer to and cite these articles when you use BayesFactorFMRI:

Journal of Open Research Software paper.
Bayesian multiple comparison correction: Han, H. (2020). Implementation of Bayesian multiple comparison correction in the second-level analysis of fMRI data: With pilot analyses of simulation and real fMRI datasets based on voxelwise inference. Cognitive Neuroscience, 11(3), 157-169. http://bit.ly/2S6Uka2
Bayesian meta-analysis: Han, H., & Park, J. (2019). Bayesian meta-analysis of fMRI image data. Cognitive Neuroscience, 10(2), 66-76. http://bit.ly/2RCbxZY