Genetic influences on dynamic complexity of brain oscillations

Abstract

Human electroencephalogram (EEG) consists of complex aperiodic oscillations that are assumed to indicate underlying neural dynamics such as the number and degree of independence of oscillating neuronal networks. EEG complexity can be estimated using measures derived from nonlinear dynamic systems theory. Variations in such measures have been shown to be associated with normal individual differences in cognition and some neuropsychiatric disorders. Despite the increasing use of EEG complexity measures for the study of normal and abnormal brain functioning, little is known about genetic and environmental influences on these measures. Using the pointwise dimension (PD2) algorithm, this study assessed heritability of EEG complexity at rest in a sample of 214 young female twins consisting of 51 monozygotic (MZ) and 56 dizygotic (DZ) pairs. In MZ twins, intrapair correlations were high and statistically significant; in DZ twins, correlations were substantially smaller. Genetic analyses using linear structural equation modeling revealed high and significant heritability of EEG complexity: 62-68% in the eyes-closed condition, and 46-60% in the eyes-open condition. Results suggest that individual differences in the complexity of resting electrocortical dynamics are largely determined by genetic factors. Neurophysiological mechanisms mediating genetic variation in EEG complexity may include the degree of structural connectivity and functional differentiation among cortical neuronal assemblies. © 2005 Elsevier Ireland Ltd. All rights reserved.Keywords: Electroencephalogram; Complexity; Nonlinear dynamics; Twins; Heritability Neural activity underlying cognition and behavior is characterized by a high degree of functional differentiation and, at the same time, functional integration achieved through rapid binding of spatially distributed and functionally specialized neuronal groups [32]. To some extent, these fundamental properties of large-scale brain dynamics are reflected in the electroencephalogram (EEG) recorded from the scalp. The EEG results from the summation of postsynaptic activity of a large number of spatially distributed but functionally connected and interacting cortical neurons and neuronal assemblies. Accordingly, the EEG time series has a complex structure reflecting the complexity of the underlying neural generators [16,26]. A greater number of independent processes contributing to the EEG results in a greater complexity of EEG time series [18]. EEG complexity may reflect the number of states of a system resulting from the interaction * Corresponding author. Tel.: +1 314 286 2201; fax: +1 314 286 0092.E-mail address: andrey@matlock.wustl.edu (A.P. Anokhin).among its elements, with higher complexity reflecting a larger number of separable oscillatory networks [32].In recent years, cortical oscillations have been increasingly viewed from the perspective of nonlinear dynamic systems theory, which investigates complex, aperiodic systems capable of self-organization [9,26]. The behavior of complex syste...

Genetic foundations of human intelligence

“…Many of these genetic influences have also been linked to g and/or intelligence (Hulshoff Pol et al 2006;Peper et al 2007;Posthuma et al 2002). Similar data have been reported for aspects of brain function that may be related to intelligence, such as the dynamic complexity of measuring brain oscillations assessing executive function output (Anokhin et al 2006), suggesting that these physiological brain measures may be endophenotypes (Gottesman and Gould 2003), or physiological markers of intelligence. Similar data have also been reported for performance on tasks considered by many to reflect more elementary information processing capacity, than performance on intelligence tests (Roberts and Stankov 1999), such as inspection time (Edmonds et al 2008) and executive control (Friedman et al 2008).…”

Genetic Contributions to Long-Range Temporal Correlations in Ongoing Oscillations

“…The heritability of the DFA exponents (33-60%) was comparable with that of biomarkers of human brain function such as the P300 component (van Beijsterveldt and van Baal, 2002) or complexity measures derived from nonlinear dynamic systems theory (Anokhin et al, 2006). Interestingly, heritability of epilepsy is also high (ϳ80%) (Kjeldsen et al, 2003).…”

The Electrical Brain Activity in Men with Different Alpha-Rhythm Characteristics during Manual Movements Executed by the Subdominant Hand

“…Kristeva et al [13] give evidence that the combination of the synchronization of the neuronal ensembles (the α-EEG amplitude increase) and the economical use of the muscular system (the integrated power reduction of the electromyogram [EMG] of facial muscles) shows an increased capacity of the self-control of movements. Such statements are based on the fact that EEG α-modal frequency is believed [14][15][16][17][18] as strictly determined genetic basis, as it reflects the important structural innate characteristics of the thalamic and cortical neurons, in particular, the features of the ionic processes in these cells [19][20][21].…”