Heritability of Sleep EEG Topography in Adolescence: Results from a Longitudinal Twin Study
Abstract The topographic distribution of sleep EEG power is a reflection of brain structure and function. The goal of this study was to examine the degree to which genes contribute to sleep EEG topography during adolescence, a period of brain restructuring and maturation. We recorded high-density sl...
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doaj-9a732348380844a3b8b29f2b9bffa1f52020-12-08T03:42:09ZengNature Publishing GroupScientific Reports2045-23222018-05-018111310.1038/s41598-018-25590-7Heritability of Sleep EEG Topography in Adolescence: Results from a Longitudinal Twin StudyAndjela Markovic0Peter Achermann1Thomas Rusterholz2Leila Tarokh3University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of BernInstitute of Pharmacology and Toxicology, University of ZurichUniversity Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of BernUniversity Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of BernAbstract The topographic distribution of sleep EEG power is a reflection of brain structure and function. The goal of this study was to examine the degree to which genes contribute to sleep EEG topography during adolescence, a period of brain restructuring and maturation. We recorded high-density sleep EEG in monozygotic (MZ; n = 28) and dizygotic (DZ; n = 22) adolescent twins (mean age = 13.2 ± 1.1 years) at two time points 6 months apart. The topographic distribution of normalized sleep EEG power was examined for the frequency bands delta (1–4.6 Hz) to gamma 2 (34.2–44 Hz) during NREM and REM sleep. We found highest heritability values in the beta band for NREM and REM sleep (0.44 ≤ h2 ≤ 0.57), while environmental factors shared amongst twin siblings accounted for the variance in the delta to sigma bands (0.59 ≤ c2 ≤ 0.83). Given that both genetic and environmental factors are reflected in sleep EEG topography, our results suggest that topography may provide a rich metric by which to understand brain function. Furthermore, the frequency specific parsing of the influence of genetic from environmental factors on topography suggests functionally distinct networks and reveals the mechanisms that shape these networks.https://doi.org/10.1038/s41598-018-25590-7 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Andjela Markovic Peter Achermann Thomas Rusterholz Leila Tarokh |
spellingShingle |
Andjela Markovic Peter Achermann Thomas Rusterholz Leila Tarokh Heritability of Sleep EEG Topography in Adolescence: Results from a Longitudinal Twin Study Scientific Reports |
author_facet |
Andjela Markovic Peter Achermann Thomas Rusterholz Leila Tarokh |
author_sort |
Andjela Markovic |
title |
Heritability of Sleep EEG Topography in Adolescence: Results from a Longitudinal Twin Study |
title_short |
Heritability of Sleep EEG Topography in Adolescence: Results from a Longitudinal Twin Study |
title_full |
Heritability of Sleep EEG Topography in Adolescence: Results from a Longitudinal Twin Study |
title_fullStr |
Heritability of Sleep EEG Topography in Adolescence: Results from a Longitudinal Twin Study |
title_full_unstemmed |
Heritability of Sleep EEG Topography in Adolescence: Results from a Longitudinal Twin Study |
title_sort |
heritability of sleep eeg topography in adolescence: results from a longitudinal twin study |
publisher |
Nature Publishing Group |
series |
Scientific Reports |
issn |
2045-2322 |
publishDate |
2018-05-01 |
description |
Abstract The topographic distribution of sleep EEG power is a reflection of brain structure and function. The goal of this study was to examine the degree to which genes contribute to sleep EEG topography during adolescence, a period of brain restructuring and maturation. We recorded high-density sleep EEG in monozygotic (MZ; n = 28) and dizygotic (DZ; n = 22) adolescent twins (mean age = 13.2 ± 1.1 years) at two time points 6 months apart. The topographic distribution of normalized sleep EEG power was examined for the frequency bands delta (1–4.6 Hz) to gamma 2 (34.2–44 Hz) during NREM and REM sleep. We found highest heritability values in the beta band for NREM and REM sleep (0.44 ≤ h2 ≤ 0.57), while environmental factors shared amongst twin siblings accounted for the variance in the delta to sigma bands (0.59 ≤ c2 ≤ 0.83). Given that both genetic and environmental factors are reflected in sleep EEG topography, our results suggest that topography may provide a rich metric by which to understand brain function. Furthermore, the frequency specific parsing of the influence of genetic from environmental factors on topography suggests functionally distinct networks and reveals the mechanisms that shape these networks. |
url |
https://doi.org/10.1038/s41598-018-25590-7 |
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