Topographic analysis of dimension estimates of EEG and filtered rhythms in epileptic patients with complex partial seizures |
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Authors: | Hongkui Jing Morikuni Takigawa |
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Institution: | (1) Department of Neuropsychiatry, Faculty of Medicine, Kagoshima University, 8-35-1 Sakuragaoka, Kagoshima City 890-8520, Japan, JP |
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Abstract: | Nonlinear dynamic properties were analyzed on the EEG and filtered rhythms recorded from healthy subjects and epileptic patients
with complex partial seizures. Estimates of correlation dimensions of control EEG, interictal EEG and ictal EEG were calculated.
The values were demonstrated on topograms. The delta (0.5–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), beta (13–30 Hz) and gamma
(30–40 Hz) components were obtained and considered as signals from the cortex. Corresponding surrogate data was produced.
Firstly, the influence of sampling parameters on the calculation was tested. The dimension estimates of the signals from the
frontal, temporal, parietal and occipital regions were computed and compared with the results of surrogate data. In the control
subjects, the estimates between the EEG and surrogate data did not differ (P > 0.05). The interictal EEG from the frontal region and occipital region, as well as its theta component from the frontal
region, and temporal region, showed obviously low dimensions (P < 0.01). The ictal EEG exhibited significantly low-dimension estimates across the scalp. All filtered rhythms from the temporal
region yielded lower results than those of the surrogate data (P < 0.01). The dimension estimates of the EEG and filtered components markedly changed when the neurological state varied.
For each neurological state, the dimension estimates were not uniform among the EEG and frequency components. The signal with
a different frequency range and in a different neurological state showed a different dimension estimate. Furthermore, the
theta and alpha components demonstrated the same estimates not only within each neurological state, but also among the different
states. These results indicate that the theta and alpha components may be caused by similar dynamic processes. We conclude
that the brain function underlying the ictal EEG has a simple mechanism. Several heterogeneous dynamic systems play important
roles in the generation of EEG.
Received: 10 December 1999 / Accepted in revised form: 8 May 2000 |
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