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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: Mar 19, 2026

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

Published on: September 12, 2011

Altered structural connectivity in ADHD: a network based analysis.

Richard Beare¹, Chris Adamson¹, Mark A Bellgrove²

¹Developmental Imaging, Royal Children's Hospital, Murdoch Childrens Research Institute, Melbourne, 3052, Australia.

Brain Imaging and Behavior

|June 13, 2016

Summary

This summary is machine-generated.

Attention deficit/hyperactivity disorder (ADHD) involves disrupted brain networks, showing less long-range connections and more local ones in adolescents. This suggests a delay in brain maturation for ADHD.

Keywords:

ADHD Connectivity Graph theory HARDI MRI NBS

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Last Updated: Mar 19, 2026

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

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Published on: September 12, 2011

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

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Published on: March 12, 2020

Using Brain Activation nir-HEG/Q-EEG and Execution Measures CPTs in a ADHD Assessment Protocol

Using Brain Activation nir-HEG/Q-EEG and Execution Measures CPTs in a ADHD Assessment Protocol

Published on: April 1, 2018

Area of Science:

Neuroscience
Developmental Neuroscience
Brain Imaging

Background:

Attention deficit/hyperactivity disorder (ADHD) is increasingly understood as a network dysfunction rather than localized brain abnormalities.
Investigating structural brain network differences is crucial for understanding ADHD pathophysiology.

Purpose of the Study:

To investigate structural brain network differences in children and adolescents with ADHD compared to healthy controls.
To identify specific network components and connectivity patterns altered in ADHD using graph theory and Network Based Statistic (NBS).

Main Methods:

Employed high-angular resolution diffusion imaging (HARDI) and whole-brain tractography on 21 ADHD and 21 control boys.
Utilized graph theory metrics and NBS to analyze anatomic networks and connectivity patterns.
Compared various tractography methods, diffusion models (tensor, CSD), and edge weighting techniques.

Main Results:

ADHD brains exhibited more modular and interconnected local networks with decreased global, long-range connections.
A sub-network with stronger connectivity in bilateral frontostriatal and left occipital, temporal, parietal regions was identified in ADHD.
White matter microstructure in these regions correlated with ADHD symptom severity.

Conclusions:

Findings demonstrate topological organization disruption in distributed neural networks in ADHD.
Results support the theory of a maturation delay in brain development associated with ADHD.
Probabilistic tractography using CSD and Hagmann weighting provided robust network difference detection.