Resting-state EEG and machine learning to investigate cortical connectivity as a biomarker in chronic mTBI.

ABSTRACT:

Introduction

Mild traumatic brain injury (mTBI) is a heterogeneous condition with long-term sequelae, yet diagnosis in the chronic stage remains limited by reliance on acute criteria and subjective reports. Objective biomarkers are needed, as current blood-based markers show diagnostic value primarily in the acute and subacute phases. Resting-state EEG (RS-EEG) can capture large-scale network disruptions through functional connectivity (FC) and microstate analysis, but its role in chronic mTBI is unclear.

Methods

We tested whether RS-EEG features distinguish chronic mTBI from controls and predict symptom burden. This observational case-control study included 44 participants (18 chronic mTBI, 26 controls). Source-reconstructed EEG was analyzed for spectral power, microstate m

SUBMITTER: Marshall WJ 

PROVIDER: S-EPMC12883407 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature