ICA-based artefact removal and accelerated fMRI acquisition for improved resting state network imaging.

ABSTRACT: The identification of resting state networks (RSNs) and the quantification of their functional connectivity in resting-state fMRI (rfMRI) are seriously hindered by the presence of artefacts, many of which overlap spatially or spectrally with RSNs. Moreover, recent developments in fMRI acquisition yield data with higher spatial and temporal resolutions, but may increase artefacts both spatially and/or temporally. Hence the correct identification and removal of non-neural fluctuations is crucial, especially in accelerated acquisitions. In this paper we investigate the effectiveness of three data-driven cleaning procedures, compare standard against higher (spatial and temporal) resolution accelerated fMRI acquisitions, and investigate the combined effect of different acquisitions and differen

SUBMITTER: Griffanti L 

PROVIDER: S-EPMC4154346 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature