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An investigation of EEG dynamics in an animal model of temporal lobe epilepsy using the maximum Lyapunov exponent
- Source :
-
Experimental Neurology . Mar2009, Vol. 216 Issue 1, p115-121. 7p. - Publication Year :
- 2009
-
Abstract
- Abstract: 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 (STLmax), 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) STLmax 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 STLmax values among cortical sites. iEEGs were recorded from bilateral frontal cortices and hippocampi. STLmax and T-index (a measure of convergence/divergence of STLmax between recorded brain areas) were compared among the four different periods. Statistical tests (ANOVA and multiple comparisons) revealed that ictal STLmax was lower (p <0.05) than other periods, STLmax 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. [Copyright &y& Elsevier]
Details
- Language :
- English
- ISSN :
- 00144886
- Volume :
- 216
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Experimental Neurology
- Publication Type :
- Academic Journal
- Accession number :
- 36548925
- Full Text :
- https://doi.org/10.1016/j.expneurol.2008.11.009