Deriving frequency-dependent spatial patterns in MEG-derived resting state sensorimotor network: A novel multiband ICA technique.

ABSTRACT: Recently, independent components analysis (ICA) of resting state magnetoencephalography (MEG) recordings has revealed resting state networks (RSNs) that exhibit fluctuations of band-limited power envelopes. Most of the work in this area has concentrated on networks derived from the power envelope of beta bandpass-filtered data. Although research has demonstrated that most networks show maximal correlation in the beta band, little is known about how spatial patterns of correlations may differ across frequencies. This study analyzed MEG data from 18 healthy subjects to determine if the spatial patterns of RSNs differed between delta, theta, alpha, beta, gamma, and high gamma frequency bands. To validate our method, we focused on the sensorimotor network, which is well-characterized and robus

SUBMITTER: Nugent AC 

PROVIDER: S-EPMC5224967 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature