Evaluation of noise regression techniques in resting-state fMRI studies using data of 434 older adults.

ABSTRACT: Subject motion is a well-known confound in resting-state functional MRI (rs-fMRI) and the analysis of functional connectivity. Consequently, several clean-up strategies have been established to minimize the impact of subject motion. Physiological signals in response to cardiac activity and respiration are also known to alter the apparent rs-fMRI connectivity. Comprehensive comparisons of common noise regression techniques showed that the "Independent Component Analysis based strategy for Automatic Removal of Motion Artifacts" (ICA-AROMA) was a preferred pre-processing technique for teenagers and adults. However, motion and physiological noise characteristics may differ substantially for older adults. Here, we present a comprehensive comparison of noise-regression techniques for older adult

SUBMITTER: Scheel N 

PROVIDER: S-EPMC9626831 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature