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Related Concept Videos

Attention-Deficit/Hyperactivity Disorder01:30

Attention-Deficit/Hyperactivity Disorder

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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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Modeling in Therapy01:26

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Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
Participant Modeling
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Brain Imaging01:14

Brain Imaging

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Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...
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Related Experiment Video

Updated: Jul 15, 2025

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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Functional Imaging Derived ADHD Biotypes Based on Deep Clustering May Guide Personalized Medication Therapy.

Aichen Feng1,2, Yuan Feng3, Dongmei Zhi4

  • 1Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China, 100190.

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|October 4, 2023
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Summary

Researchers identified two distinct subtypes of attention deficit hyperactivity disorder (ADHD) using brain imaging. This discovery may enable personalized ADHD treatment strategies, improving medication effectiveness for better symptom recovery.

Keywords:
ABCDAttention deficit hyperactivity disorder (ADHD)biological subtype detectiondeep clusteringgraph convolutional network (GCN)

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Area of Science:

  • Neuroscience
  • Psychiatry
  • Computational Biology

Background:

  • Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder lacking clear subtype-medication correlations.
  • Objective neuroimaging markers are needed for personalized, biotype-guided ADHD treatment.

Approach:

  • Utilized graph convolutional networks and deep clustering on functional network connectivity (FNC) data.
  • Identified two distinct ADHD biotypes in 1069 ADHD patients from the Adolescent Brain and Cognitive Development (ABCD) study.
  • Validated biotype replication in an independent cohort of 130 ADHD adolescents undergoing medication treatment.

Key Points:

  • ADHD biotypes showed differences in cognitive performance and hyperactivity/impulsivity symptoms.
  • Biotype 1 exhibited significantly better recovery with methylphenidate compared to Biotype 2 with atomoxetine.
  • The imaging-driven, biotype-guided approach shows promise for personalized ADHD treatment.

Conclusions:

  • Deep learning algorithms can identify novel ADHD biotypes from neuroimaging data.
  • This approach facilitates individualized treatment selection for improved medication effectiveness.
  • Further exploration of deep learning for ADHD biotype discovery is warranted.