Prediction of Spike‐Wave Bursts in Absence Epilepsy by EEG Power‐Spectrum Signals

Summary: The EEGs of subjects with absence seizures were examined to determine if changes occurred prior to spike‐wave bursts that could be used to predict bursts. A number of 20‐s epochs of EEG prior to spike‐wave bursts (preburst epochs) and during periods remote from bursts (control epochs) were examined in 5 subjects. Power‐spectrum analysis was carried out on each epoch and frequency bands from 0 to 50 c/s were combined into 2‐c/s bandwidths. Logarithmically transformed power values in each frequency band were entered into a discriminant analysis algorithm for each subject separately. Results were expressed in terms of a test for significant differences between preburst and control epochs (F statistic) and a “success ratio” of discriminant analysis classification, defined as the proportion of correct classifications in both groups, as obtained using a cross‐validation procedure. A significant preburst EEG pattern was found in 4 of the 5 subjects, and success ratios ranged from 0.64 to 0.83. Each subject's preburst EEG seemed to be characterized by a unique pattern of changes, and thus no common prodromal signal was found. The EEG changes did not appear to be caused by overt behaviors, such as eye closure or drowsiness. The findings suggest that the preburst EEG pattern represents a functional alteration in brain activity which could arise from the burst‐producing mechanism directly.