A Prior-Knowledge-Guided Feature Selection Method and Its Application to Biomarker Identification of Schizophrenia

Authors

• Ying Xing
• Godfrey D Pearlson
• Peter Kochunov
• Vince D Calhoun
• Yuhui Du

Language

English

Publication Date

1-1-2025

Journal

Network Neuroscience

DOI

10.1162/NETN.a.37

PMID

41280234

PMCID

PMC12635834

PubMedCentral® Posted Date

11-20-2025

PubMedCentral® Full Text Version

Post-print

Abstract

Despite considerable efforts to uncover the neural basis of psychiatric disorders using neuroimaging, few methods utilize intrinsic brain-derived knowledge, leading to limited specificity and discriminability in biomarker identification. To leverage the inherent characteristics within the brain, we propose a prior-knowledge-guided feature selection method to flexibly unveil discriminative and target-oriented biomarkers of psychiatric disorders. Specifically, we construct a constrained sparse regularization allowing for the flexible integration of diverse prior knowledge to identify sparse neuroimaging features linked to specific psychopathology. Additionally, we simultaneously integrate graph-based regularization and redundancy-removal regularization to further ensure the discriminability and independence among the selected features. Different priors hold varying significance in identifying specific biomarkers. Four functional magnetic resonance imaging (fMRI) datasets from 708 healthy controls and 537 schizophrenia patients are used to evaluate our method integrated with various prior knowledge, revealing specific schizophrenia-related brain abnormalities. Compared with nine advanced feature selection methods, our method improves mean classification accuracy by 3.89% to 11.24%, particularly revealing reduced interactions within the visual domain and between subcortical and visual domains in schizophrenia patients. The proposed method offers flexible and precise biomarker identification tailored to specific targets, advancing the understanding and diagnosis of psychiatric conditions.

Keywords

Dimensionality reduction, Classification, Mental disorders, Functional network connectivity, Biomarker

Published Open-Access

yes

Recommended Citation

Xing, Ying; Pearlson, Godfrey D; Kochunov, Peter; et al., "A Prior-Knowledge-Guided Feature Selection Method and Its Application to Biomarker Identification of Schizophrenia" (2025). Faculty, Staff and Student Publications. 4401.
https://digitalcommons.library.tmc.edu/uthmed_docs/4401