Create imaging-based priors for use in Bayesian models that can be applied in smaller more targeted imaging studies
Approved Research ID: 33278
Approval date: June 17th 2020
(1) We seek to use the data to create imaging-based priors for use in Bayesian models that can be applied in smaller more targeted imaging studies with the goal to improve the statistical power of these analyses; (2) We seek to study brain-based mediators of various behavioral variables using a newly developed approach for high-dimensional mediation analysis; (3) We seek to study individual differences in time-varying brain connectivity across the cohort; (4) We seek to use machine learning and related pattern-recognition algorithms to develop brain models of the functional representations underlying chronic pain. (5) We seek to create a biobank of MRI brain structural volumes, DTI indices, and resting state fMRI synchrony, where new samples can be shifted, in order to correct "batch" effects. (6) We seek to create a bank of brain iron atlases using quantitative susceptibility mapping (QSM) MRI with the UK Biobank resources.
(7). We seek to correlate brain age gap with accelerometry measures.