PREDICTABILITY OF EEG INTERICTAL SPIKES

To determine whether EEG spikes are predictable, time series of EEG sp ike intervals were generated from subdural and depth electrode recordi ngs from four patients, The intervals between EEG spikes were hand edi ted to ensure high accuracy and eliminate false positive and negative spikes. Spike rates (per minute) were generated from longer time serie s, but for these data hand editing was usually not feasible, Linear an d nonlinear models were fit to both types of data. One patient had no linear or nonlinear predictability, two had predictability that could be well accounted for with a linear stochastic model, and one had a de gree of nonlinear predictability for both interval and rate data that no linear model could adequately account for.