A method to adjust a prior distribution in Bayesian second-level fMRI analysis
نویسندگان
چکیده
Previous research has shown the potential value of Bayesian methods in fMRI (functional magnetic resonance imaging) analysis. For instance, results from Bayes factor-applied second-level analysis showed a higher hit rate compared with frequentist analysis, suggesting greater sensitivity. Although method reported more positives as result sensitivity, it was able to maintain reasonable level selectivity term false positive rate. Moreover, employment multiple comparison correction update default prior distribution significantly improved performance However, previous studies have utilized and did not consider nature each individual study. Thus, present study, adjust Cauchy based on priori information, which can be acquired relevant studies, proposed tested. A adjusted contrast, noise strength, proportion true that were estimated meta-analysis studies. In both simulated images real contrast two used evaluate method. The adjustment resulted
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ژورنال
عنوان ژورنال: PeerJ
سال: 2021
ISSN: ['2167-8359']
DOI: https://doi.org/10.7717/peerj.10861