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Related Experiment Video

Updated: Jan 7, 2026

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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Brain morphological changes across behaviour spectrums in attention-deficit/hyperactivity disorder.

Tianzheng Zhong1, Feng Wang1, Jianfeng Qiu2

  • 1Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an, Shandong, China.

General Psychiatry
|December 29, 2025
PubMed
Summary

Attention-deficit/hyperactivity disorder (ADHD) involves distinct brain grey matter volume (GMV) changes. This study identified two ADHD subtypes with unique GMV patterns linked to specific behavioral symptoms, suggesting tailored treatments.

Keywords:
Attention Deficit Disorder with HyperactivityBehaviourBrainCausalityNeuropsychiatry

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Area of Science:

  • Neuroimaging
  • Developmental Neuroscience
  • Psychiatry

Background:

  • Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder characterized by behavioral symptoms and alterations in grey matter volume (GMV).
  • Previous research has not fully clarified the progressive and causal relationships between GMV changes and behavioral manifestations in ADHD.
  • Understanding these relationships is crucial for developing effective diagnostic and therapeutic strategies.

Purpose of the Study:

  • To investigate the causal relationship between grey matter volume (GMV) alterations and behavioral symptoms in children and adolescents with ADHD.
  • To explore progressive patterns of GMV changes using behavior-causal structural covariance network (BCaSCN) analysis.
  • To identify distinct neuroanatomical subtypes of ADHD based on GMV patterns.

Main Methods:

  • Structural magnetic resonance imaging (sMRI) data from 135 children/adolescents with ADHD and 182 neurotypical controls (NCs).
  • Neuroanatomical subtyping of ADHD using a clustering algorithm based on GMV.
  • Region-of-interest-based BCaSCN analysis on pseudo-time series data derived from ADHD, inattentive, and hyperactive/impulsive index values.

Main Results:

  • Two distinct ADHD subtypes were identified based on neuroanatomical differences compared to NCs.
  • ADHD subtype 1 showed associations with inattentiveness, with key nodes in frontal regions and the cerebellum.
  • ADHD subtype 2 was linked to overall disease severity, with the cerebellum and hippocampus as primary hubs.

Conclusions:

  • ADHD exhibits heterogeneous GMV changes that correlate with specific behavioral domains.
  • The findings underscore the necessity for subtype-specific diagnostic approaches and therapeutic interventions in ADHD.
  • Targeting distinct neuroanatomical patterns may improve treatment efficacy for ADHD.