Identifying major depressive disorder using Hurst exponent of resting-state brain networks

Psychiatry Research - Neuroimaging

Volumn 214, Issue 3, 2013, Pages 306-312

  Wei, Maobin ^a   Qin, Jiaolong ^a   Yan, Rui ^b   Li, Haoran ^a   Yao, Zhijian ^b,c   Lu, Qing ^a  

^a SOUTHEAST UNIVERSITY   (China)

^b NANJING MEDICAL UNIVERSITY   (China)

^c MEDICAL SCHOOL OF NANJING UNIVERSITY   (China)

Author keywords

Classification; Functional magnetic resonance imaging (fMRI); Hurst exponent; Major depressive disorder; Resting state networks

Indexed keywords

ADULT; ARTICLE; CLINICAL ARTICLE; CONTROLLED STUDY; FEMALE; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN; HURST EXPONENT; LONG TERM MEMORY; MAJOR DEPRESSION; MALE; MEASUREMENT; PRIORITY JOURNAL; RESTING STATE NETWORK; SUPPORT VECTOR MACHINE;

CLASSIFICATION; FUNCTIONAL MAGNETIC RESONANCE IMAGING (FMRI); HURST EXPONENT; MAJOR DEPRESSIVE DISORDER; RESTING-STATE NETWORKS;

ADULT; BRAIN MAPPING; CASE-CONTROL STUDIES; CEREBRAL CORTEX; DEPRESSION; DEPRESSIVE DISORDER, MAJOR; FEMALE; HUMANS; MAGNETIC RESONANCE IMAGING; MALE; MEMORY; MIDDLE AGED; REST; SUPPORT VECTOR MACHINES; YOUNG ADULT;

EID: 84888293224     PISSN: 09254927     EISSN: 18727506     Source Type: Journal    
DOI: 10.1016/j.pscychresns.2013.09.008     Document Type: Article

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