Hyemin Han

This paper proposes a method to adjust the Cauchy prior distribution in Bayesian second-level fMRI analysis using a priori information from previous studies, resulting in improved performance.

BayesFactorFMRI provides a tool for Bayesian second-level fMRI analysis and meta-analysis with multiprocessing, improving sensitivity and performance over classical methods.

The paper develops and tests a Bayesian multiple comparison correction method for fMRI analysis, showing better sensitivity and acceptable selectivity in simulated and real datasets.

The paper evaluates multiple comparison correction methods in fMRI studies using moral judgment data, finding that voxel-wise thresholding with family-wise error correction provides the most accurate overlap with existing results.