Yuji Takahara

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 paper identifies a thalamo-somatomotor functional connectivity biomarker that stratifies MDD patients into subtypes with distinct antidepressant treatment responses, demonstrating generalizability across independent datasets.

The paper evaluates rs-fMRI analysis pipelines for MDD biomarkers using multi-site datasets, finding optimal combinations of parcellation, connectivity estimation, harmonization, and machine learning methods.

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