Non-parametric early seizure detection in an animal model of temporal lobe epilepsy.

The performance of five non-parametric, univariate seizure detection schemes (embedding delay, Hurst scale, wavelet scale, nonlinear autocorrelation and variance energy) were evaluated as a function of the sampling rate of EEG recordings, the electrode types used for EEG acquisition, and the spatial location of the EEG electrodes in order to determine the applicability of the measures in real-time closed-loop seizure intervention. The criteria chosen for evaluating the performance were high statistical robustness (as determined through the sensitivity and the specificity of a given measure in detecting a seizure) and the lag in seizure detection with respect to the seizure onset time (as determined by visual inspection of the EEG signal by a trained epileptologist). An optimality index was designed to evaluate the overall performance of each measure. For the EEG data recorded with microwire electrode array at a sampling rate of 12 kHz, the wavelet scale measure exhibited better overall performance in terms of its ability to detect a seizure with high optimality index value and high statistics in terms of sensitivity and specificity.

Coherence analysis over the latent period of epileptogenesis reveal that high-frequency communication is increased across hemispheres in an animal model of limbic epilepsy.

A total of 32 microwire electrodes were implanted bilaterally into the hippocampus of Sprague-Dawley rats, which were then stimulated in the manner prescribed for the chronic limbic epilepsy model. After the initial seizure brought on by the stimulation, the animals were recorded at a high sampling rate (approximately 12 kHz) for the entire duration of the latent period. Coherence was calculated across channels in both stimulated (and later seizing) animals and non-stimulated (and thus non-seizing control) animals. Average coherence over time was greatest in intrahemispherical electrode pairs in both stimulated and non-stimulated animals. However, the 200-800 Hz band displays increased coherence interhemispherically and up to 200 Hz band displays decreased coherence interhemispherically: this occurs only in stimulated animals.

Detection of high frequency oscillations with Teager energy in an animal model of limbic epilepsy.

High frequency oscillations (HFO) in limbic epilepsy represent a marked difference between abnormal and normal brain activity. Faced with the difficult of visually detecting HFOs in large amounts of intracranial EEG data, it is necessary to develop an automated process. This paper presents Teager Energy as a method of finding HFOs. Teager energy is an ideal measure because unlike conventional energy it takes into account the frequency component of the signal as well as signal amplitude. This greatly aids in the dissection of HFOs out of the noise and other signals contained in the EEG. Therein, Teager energy analysis is able to detect high-frequency, low-amplitude components that conventional energy measurements would miss.