Quantification of network perfusion in ASL cerebral blood flow data with seed based and ICA approaches

Brain Topography

Volumn 26, Issue 4, 2013, Pages 569-580

  Jann, Kay ^a,b   Orosz, Ariane ^a   Dierks, Thomas ^a   Wang, Danny J J ^b   Wiest, Roland ^a   Federspiel, Andrea ^a  

^a UNIVERSITY OF BERN   (Switzerland)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Arterial spin labeling; Cerebral blood flow; Functional connectivity; Independent component analysis; Network quantification; Seed based analysis

Indexed keywords

ADULT; ALGORITHM; ARTERIAL SPIN LABELING; ARTICLE; BLOOD OXYGENATION; BOLD SIGNAL; BRAIN BLOOD FLOW; BRAIN PERFUSION; DEFAULT MODE NETWORK; FEMALE; FUNCTIONAL MAGNETIC RESONANCE IMAGING; FUNCTIONAL NEUROIMAGING; HUMAN; HUMAN EXPERIMENT; INDEPENDENT COMPONENT ANALYSIS; INFORMATION PROCESSING; MALE; NORMAL HUMAN; POSTERIOR CINGULATE; PRIMARY MOTOR CORTEX; PRIORITY JOURNAL; SIGNAL NOISE RATIO; SPIN LABELING;

ADULT; BRAIN MAPPING; CEREBRAL CORTEX; DATA INTERPRETATION, STATISTICAL; FEMALE; HUMANS; MAGNETIC RESONANCE ANGIOGRAPHY; MALE; NERVE NET; REGIONAL BLOOD FLOW; YOUNG ADULT;

EID: 84885031860     PISSN: 08960267     EISSN: 15736792     Source Type: Journal    
DOI: 10.1007/s10548-013-0280-3     Document Type: Article

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