The connectivity domain: Analyzing resting state fMRI data using feature-based data-driven and model-based methods

NeuroImage

Volumn 134, Issue , 2016, Pages 494-507

  Iraji, Armin ^a   Calhoun, Vince D ^b,c   Wiseman, Natalie M ^d   Davoodi Bojd, Esmaeil ^e   Avanaki, Mohammad R N ^a,d   Haacke, E Mark ^a,f   Kou, Zhifeng ^a,f  

^a Wayne State University   (United States)

^b MIND RESEARCH NETWORK   (United States)

^c MSC01 1070   (United States)

^d WAYNE STATE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^e HENRY FORD HEALTH SYSTEM   (United States)

^f WAYNE STATE UNIVERSITY   (United States)

Author keywords

Connectivity domain; Feature based analysis; General linear model (GLM); Independent component analysis (ICA); Model based method; Resting state functional MRI (rsfMRI)

Indexed keywords

ADULT; ARTICLE; BOLD SIGNAL; BRAIN FUNCTION; CONNECTIVITY DOMAIN; CONNECTOME; DATA PROCESSING; FEASIBILITY STUDY; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN; INDEPENDENT COMPONENT ANALYSIS; INTERMETHOD COMPARISON; MODEL; NORMAL HUMAN; PRIORITY JOURNAL; RESTING STATE NETWORK; ANATOMY AND HISTOLOGY; BRAIN; MIDDLE AGED; MULTIVARIATE ANALYSIS; NERVE TRACT; NUCLEAR MAGNETIC RESONANCE IMAGING; PHYSIOLOGY; PROCEDURES; REPRODUCIBILITY; SIGNAL PROCESSING; STATISTICAL ANALYSIS;

ADULT; BRAIN; CONNECTOME; DATA INTERPRETATION, STATISTICAL; HUMANS; MAGNETIC RESONANCE IMAGING; MIDDLE AGED; MULTIVARIATE ANALYSIS; NEURAL PATHWAYS; REPRODUCIBILITY OF RESULTS; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 84964425512     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2016.04.006     Document Type: Article

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