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Pattern classification using principal components of cortical thickness and its discriminative pattern in schizophrenia

Cited 76 time in Web of Science Cited 77 time in Scopus
Authors
Yoon, Uicheul; Lee, Jong-Min; Im, Kiho; Shin, Yong-Wook; Cho, Baek Hwan; Kim, In Young; Kwon, Jun Soo; Kim, Sun I
Issue Date
2006-12-26
Publisher
Elsevier
Citation
Neuroimage. 2007 Feb 15;34(4):1405-15. Epub 2006 Dec 26.
Keywords
AdultAgedAged, 80 and overCerebral Cortex/anatomy & histology/*pathologyDiscriminant AnalysisFemaleFunctional LateralityHumansInterviews as TopicMaleMiddle AgedSchizophrenia/classification/*pathology
Abstract
We proposed pattern classification based on principal components of cortical thickness between schizophrenic patients and healthy controls, which was trained using a leave-one-out cross-validation. The cortical thickness was measured by calculating the Euclidean distance between linked vertices on the inner and outer cortical surfaces. Principal component analysis was applied to each lobe for practical computational issues and stability of principal components. And, discriminative patterns derived at every vertex in the original feature space with respect to support vector machine were analyzed with definitive findings of brain abnormalities in schizophrenia for establishing practical confidence. It was simulated with 50 randomly selected validation set for the generalization and the average accuracy of classification was reported. This study showed that some principal components might be more useful than others for classification, but not necessarily matching the ordering of the variance amounts they explained. In particular, 40-70 principal components rearranged by a simple two-sample t-test which ranked the effectiveness of features were used for the best mean accuracy of simulated classification (frontal: (left(%)|right(%))=91.07|88.80, parietal: 91.40|91.53, temporal: 93.60|91.47, occipital: 88.80|91.60). And, discriminative power appeared more spatially diffused bilaterally in the several regions, especially precentral, postcentral, superior frontal and temporal, cingulate and parahippocampal gyri. Since our results of discriminative patterns derived from classifier were consistent with a previous morphological analysis of schizophrenia, it can be said that the cortical thickness is a reliable feature for pattern classification and the potential benefits of such diagnostic tools are enhanced by our finding.
ISSN
1053-8119 (Print)
Language
English
URI
http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17188902

http://hdl.handle.net/10371/22977
DOI
https://doi.org/10.1016/j.neuroimage.2006.11.021
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College of Medicine/School of Medicine (의과대학/대학원)Psychiatry (정신과학전공)Journal Papers (저널논문_정신과학전공)
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