Heritability of background EEG across the power spectrum.

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Title: Heritability of background EEG across the power spectrum.
Authors: Smit, D. J. A. (AUTHOR), Posthuma, D. (AUTHOR), Boomsma, D. I. (AUTHOR), Geus, E. J. C. (AUTHOR)
Source: Psychophysiology. Nov2005, Vol. 42 Issue 6, p691-697. 7p. 4 Charts, 1 Graph.
Subjects: Electroencephalography, Differential psychology, Genetic algorithms, Power spectra, Frequency spectra
Abstract: We estimated the genetic and nongenetic (environmental) contributions to individual differences in the background EEG power spectrum in two age cohorts with mean ages of 26.2 and 49.4 years. Nineteen-lead EEG was recorded with eyes closed from 142 monozygotic and 167 dizygotic twin pairs and their siblings, totaling 760 subjects. We obtained power spectra in 24 bins of 1 Hz ranging from 1.0 to 25.0 Hz. Generally, heritability was highest around the alpha peak frequency and lower in the theta and delta bands. In the beta band heritability gradually decreased with increasing frequency, especially in the temporal regions. Genetic correlations between power in the classical broad bands indicated that half to three-quarters of the genetic variance can be attributed to a common source. We conclude that across the scalp and most of the frequency spectrum, individual differences in adult EEG are largely determined by genetic factors. [ABSTRACT FROM AUTHOR]
Copyright of Psychophysiology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Heritability of background EEG across the power spectrum.
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  Data: <searchLink fieldCode="JN" term="%22Psychophysiology%22">Psychophysiology</searchLink>. Nov2005, Vol. 42 Issue 6, p691-697. 7p. 4 Charts, 1 Graph.
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  Data: <searchLink fieldCode="DE" term="%22Electroencephalography%22">Electroencephalography</searchLink><br /><searchLink fieldCode="DE" term="%22Differential+psychology%22">Differential psychology</searchLink><br /><searchLink fieldCode="DE" term="%22Genetic+algorithms%22">Genetic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Power+spectra%22">Power spectra</searchLink><br /><searchLink fieldCode="DE" term="%22Frequency+spectra%22">Frequency spectra</searchLink>
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  Label: Abstract
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  Data: We estimated the genetic and nongenetic (environmental) contributions to individual differences in the background EEG power spectrum in two age cohorts with mean ages of 26.2 and 49.4 years. Nineteen-lead EEG was recorded with eyes closed from 142 monozygotic and 167 dizygotic twin pairs and their siblings, totaling 760 subjects. We obtained power spectra in 24 bins of 1 Hz ranging from 1.0 to 25.0 Hz. Generally, heritability was highest around the alpha peak frequency and lower in the theta and delta bands. In the beta band heritability gradually decreased with increasing frequency, especially in the temporal regions. Genetic correlations between power in the classical broad bands indicated that half to three-quarters of the genetic variance can be attributed to a common source. We conclude that across the scalp and most of the frequency spectrum, individual differences in adult EEG are largely determined by genetic factors. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Psychophysiology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1111/j.1469-8986.2005.00352.x
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        Text: English
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      – SubjectFull: Genetic algorithms
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              Text: Nov2005
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