Go Okada

Computational Mechanisms of Neuroimaging Biomarkers Uncovered by Multicenter Resting-State fMRI Connectivity Variation Profile

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.

Unsupervised feature computation-based feature selection robustly extracted resting-state functional connectivity patterns related to mental disorders

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

Comprehensive evaluation of pipelines for diagnostic biomarkers of major depressive disorder using multi-site resting-state fMRI 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.

Generalizable neuromarker for autism spectrum disorder across imaging sites and developmental stages: A multi-site study

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

A Large-Scale ENIGMA Multisite Replication Study of Brain Age in Depression

The paper replicates a brain age gap in depression using a large-scale multisite study, finding a similar effect size to a prior study.

Resting-state brain activity can predict target-independent aptitude in fMRI-neurofeedback training

This study identifies resting-state brain connectivity patterns that predict individual aptitude in fMRI-neurofeedback training, independent of targeted brain regions.

Common brain networks between major depressive disorder and symptoms of depression that are validated for independent cohorts

The paper identifies common brain networks between major depressive disorder and depression symptoms that generalize across independent imaging sites.

Harmonization of resting-state functional MRI data across multiple imaging sites via the separation of site differences into sampling bias and measurement bias

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%.

A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity

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.