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Updated: May 9, 2025

Event Related Potentials ERPs and other EEG Based Methods for Extracting Biomarkers of Brain Dysfunction: Examples from Pediatric Attention Deficit/Hyperactivity Disorder ADHD

Event Related Potentials ERPs and other EEG Based Methods for Extracting Biomarkers of Brain Dysfunction: Examples from Pediatric Attention Deficit/Hyperactivity Disorder ADHD

Published on: March 12, 2020

Functional connectivity anomalies in medication-naive children with ADHD: Diagnostic potential, symptoms

Yingzi Hu¹, Yexian Zeng¹, Tong Fu²

¹The Affiliated Brain Hospital, Guangzhou Medical University, Guangzhou 510370, China; Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou 510370, China; Institute of Psychiatry and Psychology, The Affiliated Brain Hospital, Guangzhou Medical University, Guangzhou 510370, China.

Clinical Neurophysiology : Official Journal of the International Federation of Clinical Neurophysiology

|April 30, 2025

Abstract

Objective:

To identify reliable electroencephalography (EEG) biomarkers for attention deficit/hyperactivity disorder (ADHD) by investigating anomalous functional connectivity patterns and their clinical relevance.

Methods:

Resting-state EEG data were collected from 74 children aged 6-12 (33 unmedicated ADHD; 41 typically developing). Functional connectivity was quantified using the imaginary part of coherency (ICOH). Machine learning (ML)-based support vector machine (SVM) modeling, regression, and mediation analyses linked connectivity features to symptom severity and diagnostic classification.

Results:

Children with ADHD exhibited beta (β) band hypo-connectivity in frontal regions (Fp2-F4, Fp1-Cz, F7-Cz) and theta (θ) band hyper-connectivity in left parietal-central networks (C3-P7, P3-P7, etc.). An SVM classifier achieved an average area under the curve of 0.89 using three connectivity features. Left parietal θ band hyper-connectivity (C3-P7) correlated with both inattention and hyperactivity/impulsivity and mediated their interrelationship.

Conclusions:

ADHD is characterized by disrupted frontoparietal connectivity, with θ band hyper-connectivity in sensory-integration networks potentially compensating for impaired frontal regulation.

Significance:

These findings highlight C3-P7 θ band connectivity as both a diagnostic and mechanistic biomarker, providing novel target for neurofeedback therapies and enhancing the differential diagnosis in neurodevelopmental disorders.

Keywords:

ADHD biomarkers Functional Connectivity Machine Learning Classification Mediation Analysis Resting-state EEG

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