Temporal order of nonlinear dynamics in human brain.
In previous spectral analysis investigations, we demonstrated that the spontaneous activity of the alpha EEG is not stationary but rather shows cyclic alterations with a circa 1-min periodicity. Following the conclusion that a power increase in the alpha band implies a neuronal synchronization, and vice versa, an associated decrease of the EEG complexity was postulated. Accordingly, a rhythmic variation, i.e., a temporal order of the nonlinear dynamics with similar period length, was expected. Bipolar 4-min EEG recordings were obtained from 20 awake subjects (mean age: 23.5+/-2.5 years) with eyes closed for the EEG leads C3, C4, Oz, and Fz according to the 10-20 system. For the automatic evaluation of spontaneous alterations of complexity, a sliding computation of the so-called correlation dimension, using an analysis window length of 20 s continuously shifted by 1 s, was performed. The time series of complexity exhibited an oscillatory behavior with a mean period length of 58.7 s; the Friedman test statistic revealed no significant topological differences. For the rejection of the null hypothesis that the observed periodicity is a random one, two-group t-tests and ANOVA with repeated measures were performed, comparing the corresponding amplitudes and period lengths with those derived from 20 pseudo-random signals (taken from a multivariate Gaussian normal distribution). The mean relative change of EEG complexity was highly significantly increased (P<0.0001) compared to that of random data. Likewise, the difference of mean period lengths was also significant (P<0.01). The results indicate that the coupling strength of the neural network of the brain changes periodically, with a cyclic alteration from a central to a parallel processing mode of information, reflecting state transitions from synchronized, low-complex EEG activity to desynchronized high-complex activity, and vice versa. Various neuronal control mechanisms that may be acting as pacemakers responsible for the temporal order of such transients are discussed. A disturbance of the temporal order may be of pathophysiological significance.
Tirsch
W S
WS
GSF-Institut für Medizinische Informatik und Institut für Biomathematik, D-85764, Neuherberg, Germany. tirsch@gsf.de
Stude
Ph
P
Scherb
H
H
Keidel
M
M
D000200:Action Potentials / Q000502:physiology*; D000328:Adult; D001683:Biological Clocks / Q000502:physiology*; D001921:Brain / Q000502:physiology*; D003344:Cortical Synchronization; D004569:Electroencephalography / Q000706:statistics & numerical data; D006801:Humans; D009415:Nerve Net / Q000502:physiology*; D009434:Neural Pathways / Q000502:physiology*; D017711:Nonlinear Dynamics; D016011:Normal Distribution; D010507:Periodicity; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors