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

Poil, S. -S., Bollmann, S., Ghisleni, C., O'Gorman, R. L., Klaver, P., Ball, J., Eich-Hoechli, D., Brandeis, D. and Michels, L. (2014) Age dependent electroencephalographic changes in attention-deficit/hyperactivity disorder (ADHD). Clinical Neurophysiology, 125 8: 1626-1638. doi:10.1016/j.clinph.2013.12.118


Author Poil, S. -S.
Bollmann, S.
Ghisleni, C.
O'Gorman, R. L.
Klaver, P.
Ball, J.
Eich-Hoechli, D.
Brandeis, D.
Michels, L.
Title Age dependent electroencephalographic changes in attention-deficit/hyperactivity disorder (ADHD)
Journal name Clinical Neurophysiology   Check publisher's open access policy
ISSN 1872-8952
1388-2457
Publication date 2014-08
Sub-type Article (original research)
DOI 10.1016/j.clinph.2013.12.118
Open Access Status
Volume 125
Issue 8
Start page 1626
End page 1638
Total pages 13
Place of publication Shannon, Ireland
Publisher Elsevier Ireland
Collection year 2015
Language eng
Subject 2728 Clinical Neurology
2808 Neurology
2737 Physiology (medical)
2809 Sensory Systems
Formatted abstract
Objective:
Objective biomarkers for attention-deficit/hyperactivity disorder (ADHD) could improve diagnostics or treatment monitoring of this psychiatric disorder. The resting electroencephalogram (EEG) provides non-invasive spectral markers of brain function and development. Their accuracy as ADHD markers is increasingly questioned but may improve with pattern classification.

Methods:
This study provides an integrated analysis of ADHD and developmental effects in children and adults using regression analysis and support vector machine classification of spectral resting (eyes-closed) EEG biomarkers in order to clarify their diagnostic value.

Results:
ADHD effects on EEG strongly depend on age and frequency. We observed typical non-linear developmental decreases in delta and theta power for both ADHD and control groups. However, for ADHD adults we found a slowing in alpha frequency combined with a higher power in alpha-1 (8-10. Hz) and beta (13-30. Hz). Support vector machine classification of ADHD adults versus controls yielded a notable cross validated sensitivity of 67% and specificity of 83% using power and central frequency from all frequency bands. ADHD children were not classified convincingly with these markers.

Conclusions:
Resting state electrophysiology is altered in ADHD, and these electrophysiological impairments persist into adulthood.

Significance:
Spectral biomarkers may have both diagnostic and prognostic value.
Keyword Attention-deficit/hyperactivity disorder
Development
Electroencephalography
Eyes-closed resting-state
Linear regression
Support vector machine
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Non HERDC
Centre for Advanced Imaging Publications
 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 12 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 12 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Tue, 28 Oct 2014, 12:45:15 EST by System User on behalf of Centre for Advanced Imaging