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Approved Research

Create imaging-based priors for use in Bayesian models that can be applied in smaller more targeted imaging studies

Principal Investigator: Professor Martin Lindquist
Approved Research ID: 33278
Approval date: June 17th 2020

Lay summary

(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.

Scope extension:

(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.

(8) We seek to assess MRI-audiometric and MRI-vestibular measures relevant to hearing loss and vestibular dysfunction. We will use structural and functional MRI methods to map traditional audiometry such as air and bone conduction thresholds to assess hearing loss. Further, we will utilize the MRI methods to assess vestibular and balance dysfunction in the goal to understand abnormalities of gait and mobility.