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BayesFactorFMRI: Implementing Bayesian Second-Level fMRI Analysis with Multiple Comparison Correction and Bayesian Meta-Analysis of fMRI Images with Multiprocessing Cover

BayesFactorFMRI: Implementing Bayesian Second-Level fMRI Analysis with Multiple Comparison Correction and Bayesian Meta-Analysis of fMRI Images with Multiprocessing

Journal of Open Research Software

Volume 9 (2021): Issue 1

By: Hyemin Han

Open Access

|Feb 2021

Abstract

BayesFactorFMRI is a tool developed with R and Python to allow neuroimaging researchers to conduct Bayesian second-level analysis and Bayesian meta-analysis of fMRI image data with multiprocessing. This tool expedites 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 Zenodo and 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 improving performance by distributing analysis tasks into multiple processors.

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DOI: https://doi.org/10.5334/jors.328 | Journal eISSN: 2049-9647

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Language: English

Submitted on: Mar 17, 2020

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Accepted on: Sep 8, 2020

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Published on: Feb 2, 2021

Published by: Ubiquity Press

In partnership with: Paradigm Publishing Services

Publication frequency: 1 issue per year

Keywords:

Bayesian analysis,

multiple comparison correction,

multiprocessing

© 2021 Hyemin Han, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.

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