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Controllability in attention deficit hyperactivity disorder brains.

Bo Chen1, Weigang Sun1, Chuankui Yan2

  • 1Department of Mathematics, School of Science, Hangzhou Dianzi University, Hangzhou, 310018 People's Republic of China.

Cognitive Neurodynamics
|August 6, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a controllability index to identify brain network differences in attention deficit hyperactivity disorder (ADHD). The new metric effectively highlights abnormal brain regions in ADHD patients, offering potential for diagnosing other mental health conditions.

Keywords:
Attention deficit hyperactivity disorderBrain networkComplex networksControllability

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Area of Science:

  • Neuroscience
  • Network Science
  • Psychiatry

Background:

  • Mental illnesses involve complex brain network dysfunctions.
  • Understanding these network alterations is key for diagnosis and treatment.
  • Existing metrics may not fully capture brain network abnormalities.

Purpose of the Study:

  • To quantify a novel node controllability index (CA-scores) for brain networks.
  • To develop a framework for studying attention deficit hyperactivity disorder (ADHD) brain dysfunction.
  • To compare the controllability index with other network metrics in identifying ADHD-related abnormalities.

Main Methods:

  • Analysis of fMRI data from 143 healthy controls and 102 ADHD patients.
  • Calculation of a node controllability index (CA-scores) for brain regions.
  • Comparison of CA-scores with connection strength, eigenvector centrality, and topology entropy.

Main Results:

  • Significant differences in CA-scores were found in specific brain regions of ADHD patients, including the Rolandic operculum, insula, and precuneus.
  • The controllability index demonstrated potential effectiveness in identifying abnormal brain regions in ADHD.
  • CA-scores revealed distinct differences in both individual brain regions (nodes) and functional modules (subsystems).

Conclusions:

  • The node controllability index (CA-scores) is a promising metric for understanding brain network dysfunction in ADHD.
  • This controllability metric may be more sensitive than other network measures for detecting abnormalities in ADHD.
  • The framework can be extended to investigate other psychiatric disorders.