Estimating brain age using high-resolution pattern recognition: Younger brains in long-term meditation practitioners

NeuroImage

Volumn 134, Issue , 2016, Pages 508-513

  Luders, Eileen ^a,b   Cherbuin, Nicolas ^b   Gaser, Christian ^c  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

^c JENA UNIVERSITY HOSPITAL   (Germany)

Author keywords

Aging; Brain; Gray matter; Meditation; Mindfulness; MRI

Indexed keywords

ADULT; AGE; AGE DISTRIBUTION; AGED; AGING; ALGORITHM; ARTICLE; BRAIN AGE; BRAIN AGING; BRAINAGE INDEX; COMPARATIVE STUDY; CONTROLLED STUDY; CROSS-SECTIONAL STUDY; FEMALE; HIGH RESOLUTION PATTERN RECOGNITION; HUMAN; HUMAN EXPERIMENT; IMAGE ANALYSIS; MACHINE LEARNING; MALE; MEDITATION; MIDDLE AGED; NEUROIMAGING; NORMAL HUMAN; NUCLEAR MAGNETIC RESONANCE IMAGING; NUCLEAR MAGNETIC RESONANCE SCANNER; PATTERN RECOGNITION; PRIORITY JOURNAL; SEX DIFFERENCE; VALIDATION PROCESS; VERY ELDERLY; YOUNG ADULT; ANATOMY AND HISTOLOGY; AUTOMATED PATTERN RECOGNITION; BRAIN; INTERPERSONAL COMMUNICATION; MINDFULNESS; PHYSIOLOGY;

ADULT; AGED; AGING; BRAIN; FEMALE; HUMANS; MACHINE LEARNING; MAGNETIC RESONANCE IMAGING; MALE; MIDDLE AGED; MINDFULNESS; NEGOTIATING; PATTERN RECOGNITION, AUTOMATED; YOUNG ADULT;

EID: 84964462312     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2016.04.007     Document Type: Article

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