Evaluation of ICA-AROMA and alternative strategies for motion artifact removal in resting state fMRI

• Published in: NeuroImage (Orlando, Fla.) Vol. 112; pp. 278 - 287
• Main Authors: Pruim, Raimon H.R., Mennes, Maarten, Buitelaar, Jan K., Beckmann, Christian F.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 15.05.2015; Elsevier Limited
• Subjects: Adult; Algorithms; Brain research; Child; Connectivity; Databases, Factual; Datasets; Functional MRI; Grants; Humans; Image Processing, Computer-Assisted - methods; Image Processing, Computer-Assisted - statistics & numerical data; Independent component analysis; Magnetic Resonance Imaging - methods; Magnetic Resonance Imaging - statistics & numerical data; Motion; Neural Pathways - anatomy & histology; Neural Pathways - physiology; Noise; Principal Component Analysis; Regression Analysis; Rest - physiology; Resting state; Time series; Motion; Connectivity; Functional MRI; Resting state; Artifact; Independent component analysis

We proposed ICA-AROMA as a strategy for the removal of motion-related artifacts from fMRI data (Pruim et al., 2015). ICA-AROMA automatically identifies and subsequently removes data-driven derived components that represent motion-related artifacts. Here we present an extensive evaluation of ICA-AROM...