Detecting functional connectivity change points for single-subject fMRI data

Frontiers in Computational Neuroscience

Volumn , Issue OCT, 2013, Pages

  Cribben, Ivor ^a   Wager, Tor D ^b   Lindquist, Martin A ^c  

^a UNIVERSITY OF ALBERTA   (Canada)

^b UNIVERSITY OF COLORADO   (United States)

^c JOHNS HOPKINS BLOOMBERG SCHOOL OF PUBLIC HEALTH   (United States)

Author keywords

Dynamic connectivity; Functional connectivity; Graph based change point detection; Graphical lasso; Network change points; Stability selection; Stationary bootstrap

Indexed keywords

CHANGE POINT DETECTION; CHANGE-POINTS; FUNCTIONAL CONNECTIVITY; GRAPHICAL LASSOS; STABILITY SELECTIONS; STATIONARY BOOTSTRAP;

ALGORITHMS; MAGNETIC RESONANCE IMAGING; REGRESSION ANALYSIS;

BRAIN;

ACCURACY; ALGORITHM; ANXIETY; ARTICLE; BAYES THEOREM; BRAIN FUNCTION; BRAIN REGION; DYNAMIC CONNECTIVITY REGRESSION; FUNCTIONAL CONNECTIVITY; FUNCTIONAL MAGNETIC RESONANCE IMAGING; MATHEMATICAL ANALYSIS; NERVE CELL NETWORK; NERVE CONDUCTION; SIMULATION; TASK PERFORMANCE;

EID: 84888126273     PISSN: 16625188     EISSN: None     Source Type: Journal    
DOI: 10.3389/fncom.2013.00143     Document Type: Article

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