The effect of preprocessing pipelines in subject classification and detection of abnormal resting state functional network connectivity using group ICA

• Published in: NeuroImage (Orlando, Fla.) Vol. 145; no. Pt B; pp. 365 - 376
• Main Authors: Vergara, Victor M., Mayer, Andrew R., Damaraju, Eswar, Hutchison, Kent, Calhoun, Vince D.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 15.01.2017; Elsevier Limited
• Subjects: Adolescent; Adult; Aged; Alzheimer's disease; Brain - diagnostic imaging; Brain Concussion - diagnostic imaging; Classification; Connectome - methods; Female; Humans; Magnetic Resonance Imaging - methods; Male; Middle Aged; Pipelines; Smoking; Studies; Support Vector Machine; Traumatic brain injury; Young Adult

Resting state functional network connectivity (rsFNC) derived from functional magnetic resonance (fMRI) imaging is emerging as a possible biomarker to identify several brain disorders. Recently it has been pointed out that methods used to preprocess head motion variance might not fully remove all un...