Abstract
Previous studies reported that we developed a new system comprising continuous wavelet transform (CWT) and artificial neural network (ANN) , and it was effective for the detection of automatic absence-like seizure in long-term electroencephalography (EEG) monitoring. The porpose of this study is to exmine the circadian profile of epileptic seizure using epileptic rats. We measured EEG with the animal model for epilepsy, the Wakaya epileptic rat (WER) . WER is a new mutant exhibiting both spontaneous absence-like behavior and tonic-clonic convulsions. EEG data redorded for three consecutive days were analysed using the system based on CWT and ANN. The frequency of absence-like seizure was greater during the dark period than light period. It was suggested that daily oscillations in the frequency of epileptic seizure might be depended on light and dark cycles. [J Physiol Sci. 2008;58 Suppl:S147]
