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Related Experiment Video

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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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Age dependent electroencephalographic changes in attention-deficit/hyperactivity disorder (ADHD).

S-S Poil1, S Bollmann2, C Ghisleni3

  • 1Center for MR-Research, University Children's Hospital, Zürich, Switzerland; Center for Integrative Human Physiology (ZIHP), University of Zürich, Switzerland.

Clinical Neurophysiology : Official Journal of the International Federation of Clinical Neurophysiology
|March 4, 2014
PubMed
Summary

Objective biomarkers for attention-deficit/hyperactivity disorder (ADHD) show promise, especially in adults. Resting electroencephalogram (EEG) spectral markers can help diagnose ADHD, persisting into adulthood.

Keywords:
Attention-deficit/hyperactivity disorderDevelopmentElectroencephalographyEyes-closed resting-stateLinear regressionSupport vector machine

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Area of Science:

  • Neuroscience
  • Psychiatry

Background:

  • Attention-deficit/hyperactivity disorder (ADHD) diagnosis relies on subjective criteria.
  • Objective biomarkers are needed for improved ADHD diagnostics and treatment monitoring.
  • Resting electroencephalogram (EEG) offers non-invasive spectral markers of brain function.

Purpose of the Study:

  • To analyze ADHD and developmental effects on spectral resting EEG biomarkers.
  • To clarify the diagnostic value of EEG spectral markers using pattern classification.
  • To investigate age- and frequency-dependent alterations in ADHD.

Main Methods:

  • Integrated analysis of resting (eyes-closed) EEG spectral biomarkers in children and adults.
  • Regression analysis and support vector machine (SVM) classification were employed.
  • Analysis focused on power and central frequency across all EEG bands.

Main Results:

  • EEG alterations in ADHD are age- and frequency-dependent.
  • Adult ADHD showed decreased delta/theta power, but increased alpha-1 and beta power, with alpha frequency slowing.
  • SVM classification achieved 67% sensitivity and 83% specificity for adult ADHD, but was less effective for children.

Conclusions:

  • Resting state electrophysiology is altered in ADHD, with impairments persisting into adulthood.
  • Spectral EEG biomarkers demonstrate potential for both diagnostic and prognostic value in ADHD.
  • Further research may refine EEG-based ADHD diagnostics.