Group-specific discriminant analysis enhances detection of sex differences in brain functional network lateralization.

ABSTRACT:

Background

Lateralization is the asymmetry in function and cognition between the brain hemispheres, with notable sex differences. Conventional neuroscience studies on lateralization use univariate statistical comparisons between male and female groups, with limited and ineffective validation for group specificity. This article proposes to model sex differences in brain functional network lateralization as a dual-classification problem: first-order classification of left versus right hemispheres and second-order classification of male versus female models. To capture sex-specific patterns, we developed an interpretable group-specific discriminant analysis (GSDA) for first-order classification, followed by logistic regression for second-order classification.

Findings

Evaluatio

SUBMITTER: Zhou S 

PROVIDER: S-EPMC12398281 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature