Sparse temporally dynamic resting-state functional connectivity networks for early MCI identification

Brain Imaging and Behavior

Volumn 10, Issue 2, 2016, Pages 342-356

  Wee, Chong Yaw ^a   Yang, Sen ^c   Yap, Pew Thian ^a   Shen, Dinggang ^a,b  

^a UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

^b Korea University   (South Korea)

^c Arizona State University   (United States)

Author keywords

Mild Cognitive Impairment (MCI); Resting state functional MRI (R fMRI); Sliding window correlation; Sparse temporal networks; Temporal dynamics; Temporal smoothness

Indexed keywords

AGED; ARTICLE; BRAIN REGION; CLINICAL ARTICLE; CLINICAL EVALUATION; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST ACCURACY STUDY; FEMALE; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN; LEARNING ALGORITHM; MALE; MILD COGNITIVE IMPAIRMENT; NUCLEAR MAGNETIC RESONANCE SCANNER; PRIORITY JOURNAL; RESTING STATE NETWORK; ALGORITHM; BRAIN; BRAIN MAPPING; CASE CONTROL STUDY; COGNITIVE DEFECT; CONNECTOME; FACTUAL DATABASE; IMAGE PROCESSING; MEMBRANE POTENTIAL; NERVE CELL NETWORK; NERVE TRACT; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; PATHOPHYSIOLOGY; PHYSIOLOGY; PROCEDURES; SPATIOTEMPORAL ANALYSIS;

AGED; ALGORITHMS; BRAIN; BRAIN MAPPING; CASE-CONTROL STUDIES; COGNITIVE DYSFUNCTION; CONNECTOME; DATABASES, FACTUAL; FEMALE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MALE; MEMBRANE POTENTIALS; NERVE NET; NEURAL PATHWAYS; SPATIO-TEMPORAL ANALYSIS;

EID: 84933566531     PISSN: 19317557     EISSN: 19317565     Source Type: Journal    
DOI: 10.1007/s11682-015-9408-2     Document Type: Article

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