Measurement and Quantification of Spatio- Temporal Dynamics of Human Epileptic Seizures

Since its discovery by Hans Berger in 1929, the electroencephalogram (EEG) has been the most utilized signal to clinically assess brain function. The enormous complexity of the EEG signal, both in time and space, should not surprise us since the EEG is a direct correlate of brain function. If the system to be probed is complex and our signal is a reliable descriptor of its function, then we can also expect complexity in the signal. Unfortunately, traditional signal processing (SP) theory is based on very simple assumptions about the system that produced the signal (e.g. linearity assumption). Hence the application of SP methodologies to automatically quantify the EEG has met the challenge with varying degrees of success. We can say that today the trained electroencephalographer or neurologist are still the golden standards in characterizing phasic events in the EEG such as spikes, the quantification of background activity (as in sleep staging) and identification and localization of epileptic seizures.