Changes in electroencephalogram in rat epilepsy model via nonlinear dynamical approach
- VernacularTitle:应用非线性动力学指标分析大鼠癫痫模型脑电信息变化
- Author:
Minguang XU
;
Peng XIA
;
Yong JIANG
;
Kaiping LONG
;
Jiqing YANG
- Publication Type:Journal Article
- From:
Chinese Journal of Tissue Engineering Research
2005;9(21):216-218
- CountryChina
- Language:Chinese
-
Abstract:
BACKGROUND: The dynamic characteristics of electroencephalogram (EEG) include a decrease in the chaotic dimension, the correlation dimen sion, the Lyapunov exponent, the chaotic complexity, the freedom of EEG and an enhanced synchronization and periodicity of the EEG from several minutes to tens of minutes before epileptic seizures. All these characteristics prefigure the forthcoming seizures. Some studies have proven that the non linear dynamical system can be used as a feasible approach to explore the potential variables for describing the chaos portrait of EEG. OBJECTIVE: To analyze the electric characteristics of EEG signal in the epileptic seizures in rat model by investigating the nonlinear dynamical variables, such as the approximate entropy (ApEn) and correlation dimen sion. DESIGN: Observational and experimental study based on animals. SETTING: Department of Medical Engineering, Department of Gastroen terology, Second Artilleryman General Hospital of Chinese PLA; Department of Physics, Faulty of Biomedical Engineering, Fourth Military Medical Uni versity of Chinese PLA. MATERIALS: From September 2001 to January 2002, this study was conducted at the Complexity Laboratory of the Biomedical Department of the Fourth Military Medical University of Chinese PLA. Six male SD rats,weighing 150- 200 g, were selected.INTERVENTIONS: After intraperitoneal injection of chloral hydrate (0. 5 mL), the male SD rats were deeply anesthetized. When their EEG signal became stable, bemegride injection was diluted at 1:1 with saline and was given on a volume of 0.5 mL to the rats intraperitoneally. After a while,the epileptic seizures started marked by a spasm with a deep roar. The entire epileptic seizures were recorded. According to the shape of EEG waves and the corresponding symptoms of the rats during their seizures, data of the four phases, referring to normal condition, preictal phase, ictal phase and postictal phases of epileptic seizures, were selected for nonlinear analysis. The variations of the ApEn and the correlation dimension were calculated.MAIN OUTCOME MEASURES: In the four phases of the seizures, before seizures, preictal phase, ictal phase and postictal phases, the changes in the ApEn and correlation dimension were observed.RESULTS: All the 6 rats entered the statistical procedure. During epilepsy, the ApEn and correlation dimension of the EEG signal in ictal phases (0. 447 ±0. 126, 2. 166 ±0. 377) decreased significantly while those in preictal phases(0. 807 ±0. 182, 4. 773 ±0. 319) and postictal phases (1. 241 ±0. 125, 6. 042 ±0. 373) (t = -3. 984to 17. 902, P ＜0. 01). The ApEn and the correlation dimension of the EEG signal in preictal and ictal phases had significant difference with those observed under normal conditions (1.313 ± 0. 090, 6. 405 ± 0. 694) (t = -5. 228 to 12. 740, P ＜ 0. 01 ).CONCLUSION: The changes in ApEn and correlation dimension showed by nonlinear dynamical approach in this study reflect the characteristics of EEG signals in preictal time, ictal time and postictal timeof the epileptic seizures and the differences among them. Additionally, they also reveal the laws in the changes of the complex ictal EEG signal.
