Reciprocal Relationships Between the Oscillatory Systems of the Brain

Resting EEG recordings were made from cohorts of 146 children aged 7–17 years and 132 adults aged 18–32 years and the levels of personality features and psychopathology were assessed using the Eysenck, Spilberger, Gray-Wilson, and Goodman questionnaires. Factor analysis was used to discriminate cova...

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Bibliographic Details
Published in:Neuroscience and behavioral physiology 2010, Vol.40 (1), p.29-35
Main Authors: Knyazev, G. G., Slobodskoi-Plyusnin, Ya. Yu, Savost’yanov, A. N., Levin, E. A., Bocharov, A. V.
Format: Article
Language:English
Subjects:
Adolescent
Adult
Aging
Alpha Rhythm
Analysis of Variance
Anxiety
Behavior
Behavioral Sciences
Biomedical and Life Sciences
Biomedicine
Brain - physiology
Child
Cognition & reasoning
Cohort Studies
Delta Rhythm
Electroencephalography
Factor Analysis, Statistical
Female
Humans
Male
Neurobiology
Neurosciences
Periodicity
Personality
Personality - physiology
Personality Tests
Physiology
Questionnaires
Rest - physiology
Rhythm
Surveys and Questionnaires
Theta Rhythm
Young Adult
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Summary:Resting EEG recordings were made from cohorts of 146 children aged 7–17 years and 132 adults aged 18–32 years and the levels of personality features and psychopathology were assessed using the Eysenck, Spilberger, Gray-Wilson, and Goodman questionnaires. Factor analysis was used to discriminate covariance of measures of the spectral power of EEG rhythms into positive and negative components. The latter were interpreted as a measure of inhibitory interactions between oscillatory systems. In children, positive covariance of rhythms was stronger than in adults, while reciprocal relationships between oscillatory systems were weaker. In adults, trait anxiety correlated positively with the strength of the reciprocal relationship between the alpha and delta oscillatory systems. In children, an analogous relationship was seen between anxiety and the strength of the reciprocal relationship between the theta and delta systems. The data are discussed in the light of the evolutionary interpretation of EEG rhythms.
ISSN:0097-0549
1573-899X
DOI:10.1007/s11055-009-9227-2