Data-mining of time-domain features from neural extracellular field data

Abstract

Spike-wave and polyspike-wave activity in electroencephalogram are waveforms typical of certain epileptic states. Automated detection of such patterns would be desirable for automated seizure detection in both experimental and clinical venues. We have developed a time-domain algorithm denominated SPUD to facilitate data-mining of large electroencephalogram/electrocorticogram datasets to identify the occurrence of spike-wave or other activity patterns. This algorithm feeds into our enhanced Neural Query System [2, 12] database application to facilitate data-mining. We have used our algorithm to identify and classify activity from both simulated and experimental seizures. © 2008 Springer-Verlag Berlin Heidelberg.