Denoising brain networks using a fixed mathematical phase change in independent component analysis of magnitude-only fMRI data.

ABSTRACT: Brain networks extracted by independent component analysis (ICA) from magnitude-only fMRI data are usually denoised using various amplitude-based thresholds. By contrast, spatial source phase (SSP) or the phase information of ICA brain networks extracted from complex-valued fMRI data, has provided a simple yet effective way to perform the denoising using a fixed phase change. In this work, we extend the approach to magnitude-only fMRI data to avoid testing various amplitude thresholds for denoising magnitude maps extracted by ICA, as most studies do not save the complex-valued data. The main idea is to generate a mathematical SSP map for a magnitude map using a mapping framework, and the mapping framework is built using complex-valued fMRI data with a known SSP map. Here we leverage the fa

SUBMITTER: Zhang CY 

PROVIDER: S-EPMC10619417 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature