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Open Access Highly Accessed Research article

Regional differences in trait-like characteristics of the waking EEG in early adolescence

Dominik C Benz1, Leila Tarokh12*, Peter Achermann134 and Sarah P Loughran15

Author affiliations

1 Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland

2 Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, USA

3 Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland

4 Neuroscience Center, University and ETH Zurich, Zurich, Switzerland

5 School of Psychology, Illawarra Health & Medical Research Institute, University of Wollongong, Wollongong, NSW, Australia

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Citation and License

BMC Neuroscience 2013, 14:117  doi:10.1186/1471-2202-14-117

Published: 9 October 2013

Abstract

Background

The human waking EEG spectrum shows high heritability and stability and, despite maturational cortical changes, high test-retest reliability in children and teens. These phenomena have also been shown to be region specific. We examined the stability of the morphology of the wake EEG spectrum in children aged 11 to 13 years recorded over weekly intervals and assessed whether the waking EEG spectrum in children may also be trait-like. Three minutes of eyes open and three minutes of eyes closed waking EEG was recorded in 22 healthy children once a week for three consecutive weeks. Eyes open and closed EEG power density spectra were calculated for two central (C3LM and C4LM) and two occipital (O1LM and O2LM) derivations. A hierarchical cluster analysis was performed to determine whether the morphology of the waking EEG spectrum between 1 and 20 Hz is trait-like. We also examined the stability of the alpha peak using an ANOVA.

Results

The morphology of the EEG spectrum recorded from central derivations was highly stable and unique to an individual (correctly classified in 85% of participants), while the EEG recorded from occipital derivations, while stable, was much less unique across individuals (correctly classified in 42% of participants). Furthermore, our analysis revealed an increase in alpha peak height concurrent with a decline in the frequency of the alpha peak across weeks for occipital derivations. No changes in either measure were observed in the central derivations.

Conclusions

Our results indicate that across weekly recordings, power spectra at central derivations exhibit more “trait-like” characteristics than occipital derivations. These results may be relevant for future studies searching for links between phenotypes, such as psychiatric diagnoses, and the underlying genes (i.e., endophenotypes) by suggesting that such studies should make use of more anterior rather than posterior EEG derivations.

Keywords:
Spectral analysis; Development; Endophentoype; Clustering; Alpha activity