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

• Published in: NeuroImage (Orlando, Fla.) Vol. 95; pp. 232 - 247
• Main Authors: Griffanti, Ludovica, Salimi-Khorshidi, Gholamreza, Beckmann, Christian F., Auerbach, Edward J., Douaud, Gwenaëlle, Sexton, Claire E., Zsoldos, Enikő, Ebmeier, Klaus P., Filippini, Nicola, Mackay, Clare E., Moeller, Steen, Xu, Junqian, Yacoub, Essa, Baselli, Giuseppe, Ugurbil, Kamil, Miller, Karla L., Smith, Stephen M.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 15.07.2014; Elsevier Limited
• Subjects: Aged; Algorithms; Artefact removal; Brain; Brain - physiology; Brain Mapping - methods; Female; Functional connectivity; Functional magnetic resonance imaging (fMRI); Humans; Image Processing, Computer-Assisted - methods; Magnetic Resonance Imaging - methods; Male; Middle Aged; Multiband acceleration; Neural Pathways - physiology; NMR; Noise; Nuclear magnetic resonance; Rest; Resting-state; Time series; Functional connectivity; Multiband acceleration; Resting-state; Functional magnetic resonance imaging (fMRI); Artefact removal

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 yi...