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Attention-Deficit/Hyperactivity Disorder

Attention-Deficit/Hyperactivity Disorder

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by persistent inattention, hyperactivity, and impulsivity. It affects approximately 5-8% of children globally, with around 60-70% of cases persisting into adulthood. ADHD has significant implications for educational attainment, social interactions, and occupational success.
Diagnostic Criteria and Symptoms
To diagnose ADHD, symptoms must manifest before age 12 and be evident across multiple settings....

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Related Experiment Video

Updated: Feb 22, 2026

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

Parsing heterogeneity in attention-deficit hyperactivity disorder using EEG-based subgroups.

Sandra K Loo¹, James J McGough¹, James T McCracken¹

¹Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, UCLA David Geffen School of Medicine, Los Angeles, CA, USA.

Journal of Child Psychology and Psychiatry, and Allied Disciplines

|September 19, 2017

Summary

Researchers identified distinct subgroups in children with and without attention-deficit/hyperactivity disorder (ADHD) based on resting electroencephalography (EEG) patterns. These EEG profiles correlate with specific behavioral and cognitive characteristics, suggesting potential for outcome prediction.

Keywords:

ADHD Electrophysiology latent class analysis resting state

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Area of Science:

Neuroscience
Child Psychology
Psychiatry

Background:

Attention-deficit/hyperactivity disorder (ADHD) is a complex condition with varied presentations.
Understanding brain state differences in ADHD is crucial for targeted interventions.
Current research aims to identify distinct electroencephalography (EEG) profiles in children with and without ADHD.

Purpose of the Study:

To identify distinct subgroups of resting-state EEG profiles in children with and without ADHD.
To clinically characterize these identified subgroups based on behavioral and cognitive data.

Main Methods:

Latent class analysis applied to resting-state EEG data from 781 children (6-18 years old).
Included 620 children with ADHD and 161 controls.
Behavioral and cognitive data collected via interviews, rating scales, and cognitive tests.

Main Results:

A five-class solution best fit the data, with four classes showing elevated spectral power.
No single EEG profile characterized all children with or without ADHD, indicating heterogeneity.
Elevated slow-wave activity linked to externalizing behaviors and cognitive deficits.
Elevated alpha and beta power associated with internalizing behaviors, emotion dysregulation, and preserved cognition.

Conclusions:

Population-level heterogeneity exists in resting-state EEG subgroups within ADHD and control groups.
These EEG subgroups are associated with distinct behavioral and cognitive profiles.
EEG measures may serve as biomarkers for ADHD treatment response or outcomes rather than for diagnosis.