20 citations · 20 across the 4 of their papers we have counts for
4 papers
Scalable Bayesian Image-on-Scalar Regression for Population-Scale Neuroimaging Data Analysis
Yuliang Xu, Timothy D. Johnson, Thomas E. Nichols +1
Bayesian Image-on-Scalar Regression (ISR) provides flexible, uncertainty-aware neuroimaging analysis. However, applying ISR to large-scale datasets such as the UK Biobank is challe…
Scalable Scalar-on-Image Cortical Surface Regression with a Relaxed-Thresholded Gaussian Process Prior
Anna Menacher, Thomas E. Nichols, Timothy D. Johnson +1
In addressing the challenge of analysing the large-scale Adolescent Brain Cognition Development (ABCD) fMRI dataset, involving over 5,000 subjects and extensive neuroimaging data,…
Bayesian Image Mediation Analysis
Yuliang Xu, Timothy D Johnson, Mary Heitzeg +1
Mediation analysis aims to separate the indirect effect through mediators from the direct effect of the exposure on the outcome. It is challenging to perform mediation analysis wit…
Bayesian log-Gaussian Cox process regression: applications to meta-analysis of neuroimaging working memory studies
Pantelis Samartsidis, Claudia R. Eickhoff, Simon B. Eickhoff +5
Working memory (WM) was one of the first cognitive processes studied with functional magnetic resonance imaging. With now over 20 years of studies on WM, each study with tiny sampl…