Biclustering EEG data from epileptic patients treated with vagus nerve stimulation

We present a pilot study of an application of consistent biclustering to analyze scalp EEG data obtained from epileptic patients undergoing treatment with a vagus nerve stimulator (VNS). The ultimate goal of this study is to develop a physiologic marker for optimal VNS parameters (e.g. output current, signal frequency, etc.) using measures of scalp EEG signals. A time series of STLmax values was computed for each scalp EEG channel recorded from two epileptic patients and used as a feature of the two datasets. The averaged samples from stimulation periods were then separated from averaged samples from non-stimulation periods by feature selection performed within the consistent biclustering routine.The obtained biclustering results allow us to assume that signals from certain parts of the brain consistently change their characteristics when VNS is switched on and could provide a basis for desirable VNS stimulation parameters. A physiologic marker of optimal VNS effect could greatly reduce the cost, time, and risk of calibrating VNS stimulation parameters in newly implanted patients compared to the current method of clinical response.