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Abstract #3611

Disparate Multivariate Relationships between Brain-Behavior Dimensions across Patients with Schizophrenia at Different Illness Stages

Qiannan Zhao1 and Su Lui1
1Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Provinc, West China Hospital of Sichuan University, Chengdu, China


Clarifying brain-behavior associations in schizophrenia helps understand neurobiological mechanisms and explore biomarkers for patient stratification and cognition-targeted interventions. Sparse canonical correlation analysis (sCCA) is a method that maximizes the correlations between linear combinations of each high-dimensional data set, providing more information relative to traditional bivariate correlation analysis. In order to characterize multivariate brain-behavior associations in schizophrenia, we performed sCCA in patients at different illness stages. Disparate canonical correlations were found across FES patients and stable treated patients, involving cortical thickness and surface area contributed in each sample, consistent with their well-established differences in neurodevelopmental trajectories, genetics, and contributions to cognition.

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