Benchmarking of participant-level confound regression strategies for the control of motion artifact in studies of functional connectivity

NeuroImage

Volumn 154, Issue , 2017, Pages 174-187

  Ciric, Rastko ^a   Wolf, Daniel H ^a   Power, Jonathan D ^b   Roalf, David R ^a   Baum, Graham L ^a   Ruparel, Kosha ^a   Shinohara, Russell T ^a   Elliott, Mark A ^c   Eickhoff, Simon B ^d,e   Davatzikos, Christos ^c   Gur, Ruben C ^a,c   Gur, Raquel E ^a,c   Bassett, Danielle S ^f   Satterthwaite, Theodore D ^a  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b WEILL CORNELL MEDICAL COLLEGE   (United States)

^c UNIVERSITY OF PENNSYLVANIA   (United States)

^d Department of Orthopedic Surgery   (Germany)

^e FORSCHUNGSZENTRUM JÜLICH   (Germany)

^f UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

Artifact; Confound; fMRI; Functional connectivity; Motion; Noise

Indexed keywords

ADOLESCENT; ADULT; ARTICLE; BOLD SIGNAL; BRAIN FUNCTION; BRAIN REGION; CEREBROSPINAL FLUID ANALYSIS; CHILD; CONNECTOME; ECHO PLANAR IMAGING; FEMALE; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN; HUMAN EXPERIMENT; IMAGE ANALYSIS; IMAGE PROCESSING; MALE; MOTION ANALYSIS SYSTEM; NERVE CELL NETWORK; NORMAL HUMAN; OUTCOME ASSESSMENT; PERFORMANCE; PRIORITY JOURNAL; BENCHMARKING; NUCLEAR MAGNETIC RESONANCE IMAGING; PROCEDURES; YOUNG ADULT;

ADOLESCENT; ADULT; BENCHMARKING; CHILD; CONNECTOME; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; YOUNG ADULT;

EID: 85016190559     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2017.03.020     Document Type: Article

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