An investigation of EEG dynamics in an animal model of temporal lobe epilepsy using the maximum Lyapunov exponent

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• 作者：S ; eep P. Nair ; Deng-Shan Shiau ; Jose C. Principe ; Leonidas D. Iasemidis ; Panos M. Pardalos ; Wendy M. Norman ; Paul R. Carney ; Kevin M. Kelly ; J. Chris Sackellares
• 关键词：Seizures ; Temporal lobe epilepsy ; EEG dynamics
• 刊名：Experimental Neurology
• 出版年：2009
• 出版时间：March 2009
• 年：2009
• 卷：216
• 期：1
• 页码：115-121
• 全文大小：659 K

文摘

Analysis of intracranial electroencephalographic (iEEG) recordings in patients with temporal lobe epilepsy (TLE) has revealed characteristic dynamical features that distinguish the interictal, ictal, and postictal states and inter-state transitions. Experimental investigations into the mechanisms underlying these observations require the use of an animal model. A rat TLE model was used to test for differences in iEEG dynamics between well-defined states and to test specific hypotheses: 1) the short-term maximum Lyapunov exponent (STL_max), a measure of signal order, is lowest and closest in value among cortical sites during the ictal state, and highest and most divergent during the postictal state; 2) STL_max values estimated from the stimulated hippocampus are the lowest among all cortical sites; and 3) the transition from the interictal to ictal state is associated with a convergence in STL_max values among cortical sites. iEEGs were recorded from bilateral frontal cortices and hippocampi. STL_max and T-index (a measure of convergence/divergence of STL_max between recorded brain areas) were compared among the four different periods. Statistical tests (ANOVA and multiple comparisons) revealed that ictal STL_max was lower (p < 0.05) than other periods, STL_max values corresponding to the stimulated hippocampus were lower than those estimated from other cortical regions, and T-index values were highest during the postictal period and lowest during the ictal period. Also, the T-index values corresponding to the preictal period were lower than those during the interictal period (p < 0.05). These results indicate that a rat TLE model demonstrates several important dynamical signal characteristics similar to those found in human TLE and support future use of the model to study epileptic state transitions.