Yujiro Yoshihara

The paper develops a method to profile resting-state fMRI connectivity variations to improve the reliability and generalizability of psychiatric disorder biomarkers across multiple centers.

This study compares unsupervised feature selection with supervised methods to identify robust resting-state functional connectivity patterns associated with psychiatric disorders.

This study develops a generalizable neuromarker for ASD across multiple sites and developmental stages, showing significant performance in adults, children, and adolescents.

The paper uses brain connectivity data to show overlapping but asymmetrical relationships between schizophrenia and autism.

The paper develops a harmonization method for resting-state fMRI data across sites by separating site differences into sampling and measurement biases, reducing measurement bias by 29% and improving signal-to-noise ratios by 40%.

The paper builds a working memory prediction model from whole-brain functional connectivity in healthy individuals and applies it to psychiatric disorders, finding correlations between connectivity patterns and working memory performance.