# Generalizable brain network markers of major depressive disorder across multiple imaging sites

## TL;DR

This study develops a brain network marker for major depressive disorder that works across different imaging sites, improving generalization and clinical applicability.

## Contribution

A novel harmonization method enables generalizable machine learning markers for MDD across multiple imaging sites.

## Key findings

- A harmonization method reduced site differences in fMRI data for MDD classification.
- The classifier achieved ~70% accuracy on an independent dataset from five imaging sites.
- The results ensure scientific reproducibility and potential clinical use of the brain marker.

## Abstract

Many studies have highlighted the difficulty inherent to the clinical application of fundamental neuroscience knowledge based on machine learning techniques. It is difficult to generalize machine learning brain markers to the data acquired from independent imaging sites, mainly due to large site differences in functional magnetic resonance imaging. We address the difficulty of finding a generalizable marker of major depressive disorder (MDD) that would distinguish patients from healthy controls based on resting-state functional connectivity patterns. For the discovery dataset with 713 participants from 4 imaging sites, we removed site differences using our recently developed harmonization method and developed a machine learning MDD classifier. The classifier achieved an approximately 70% generalization accuracy for an independent validation dataset with 521 participants from 5 different imaging sites. The successful generalization to a perfectly independent dataset acquired from multiple imaging sites is novel and ensures scientific reproducibility and clinical applicability.

Biomarkers for psychiatric disorders based on neuroimaging data have yet to be put to practical use. This study overcomes the problems of inter-site differences in fMRI data by using a novel harmonization method, thereby successfully constructing a generalizable brain network marker of major depressive disorder across multiple imaging sites.