Identifying endophenotypes of autism: A multivariate approach

Frontiers in Computational Neuroscience

Volumn 8, Issue JUN, 2014, Pages

  Segovia, Fermín ^a,b   Holt, Rosemary ^b   Spencer, Michael ^b   Górriz, Juan M ^c   Ramírez, Javier ^c   Puntonet, Carlos G ^c   Phillips, Christophe ^a   Chura, Lindsay ^b   Baron Cohen, Simon ^b   Suckling, John ^b  

^a UNIVERSITY OF LIÈGE   (Belgium)

^b UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^c UNIVERSITY OF GRANADA   (Spain)

Author keywords

Autism spectrum condition; Endophenotype; MRI; Searchlight; Support vector machine

Indexed keywords

MAGNETIC RESONANCE IMAGING; SEARCHLIGHTS; SUPPORT VECTOR MACHINES;

AUTISM SPECTRUM CONDITION; ENDOPHENOTYPE; MULTIVARIATE APPROACH; PAIR-WISE COMPARISON; SUPPORT VECTOR MACHINE CLASSIFIERS; UNAFFECTED SIBLINGS;

DISEASES;

ADOLESCENT; ADULT; ANGULAR GYRUS; ARTICLE; ASPERGER SYNDROME; AUTISM; CEREBELLUM; CHILD; CONTROLLED STUDY; ENDOPHENOTYPE; FEMALE; GRAY MATTER; HUMAN; MAJOR CLINICAL STUDY; MALE; MULTIVARIATE ANALYSIS; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; NUCLEAR MAGNETIC RESONANCE SCANNER; OCCIPITAL LOBE; PARIETAL LOBE; SIBLING; SUPPORT VECTOR MACHINE;

EID: 84902177268     PISSN: None     EISSN: 16625188     Source Type: Journal    
DOI: 10.3389/fncom.2014.00060     Document Type: Article

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