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Papazova, I.* ; Wunderlich, S.* ; Papazov, B.* ; Vogelmann, U.* ; Keeser, D.* ; Karali, T.* ; Falkai, P.* ; Rospleszcz, S. ; Maurus, I.* ; Schmitt, A.* ; Hasan, A.* ; Malchow, B.* ; Stöcklein, S.*

Characterizing cognitive subtypes in schizophrenia using cortical curvature.

J. Psychiatr. Res. 173, 131-138 (2024)
Publ. Version/Full Text DOI PMC
Open Access Gold (Paid Option)
Creative Commons Lizenzvertrag
Cognitive deficits are a core symptom of schizophrenia, but research on their neural underpinnings has been challenged by the heterogeneity in deficits' severity among patients. Here, we address this issue by combining logistic regression and random forest to classify two neuropsychological profiles of patients with high (HighCog) and low (LowCog) cognitive performance in two independent samples. We based our analysis on the cortical features grey matter volume (VOL), cortical thickness (CT), and mean curvature (MC) of N = 57 patients (discovery sample) and validated the classification in an independent sample (N = 52). We investigated which cortical feature would yield the best classification results and expected that the 10 most important features would include frontal and temporal brain regions. The model based on MC had the best performance with area under the curve (AUC) values of 76% and 73%, and identified fronto-temporal and occipital brain regions as the most important features for the classification. Moreover, subsequent comparison analyses could reveal significant differences in MC of single brain regions between the two cognitive profiles. The present study suggests MC as a promising neuroanatomical parameter for characterizing schizophrenia cognitive subtypes.
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Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords Cognitive Subtypes ; Cortical Curvature ; Schizophrenia; Surface-based Analysis; Human Cerebral-cortex; Neurocognitive Deficits; Intrinsic Curvature; Longitudinal Course; Brain Structure; Thickness; Gyrification; Classification; Connectivity
ISSN (print) / ISBN 0022-3956
e-ISSN 1879-1379
Journal Journal of Psychiatric Research
Quellenangaben Volume: 173, Issue: , Pages: 131-138 Article Number: , Supplement: ,
Publisher Elsevier
Publishing Place The Boulevard, Langford Lane, Kidlington, Oxford Ox5 1gb, England
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute of Epidemiology II (EPI2)
Grants Federal Ministry of Education and Research (BMBF)