EFFECTS OF LORAZEPAM ON THE AUTOMATIC ONLINE EVALUATION OF SLEEP EEC DATA IN HEALTHY-VOLUNTEERS

In earlier publications we described an automatic algorithm to detect rapid eye movement (REM) sleep from a single-channel EEG recording wit hout using EMG or EOG information. This system consisted of an artific ial neural network operating on the basis of preprocessed EEG data and was composed to provide a maximum of robustness for online applicatio ns. In the present study the influence of acute administration of lora zepam on the performance of the REM detection procedure was evaluated. Following an adaptation to laboratory conditions, sleep EEG data were obtained from healthy subjects in three nights each. On the evening o f the second night the volunteers received a single dosage of 2.5 mg L orazepam; the other two nights were drug-free. The sleep profile and t he quantitative EEG data reflected the known changes following acute a dministration of benzodiazepines: during the treatment night the amoun t of non-REM sleep and the relative power of the EEG signal in the bet a and gamma frequency bands was increased relative to the first night, while the amount of REM sleep was reduced. The night of drug disconti nuation still showed some characteristics of the treatment night. The discordance rate of the REM detection algorithm relative to the manual evaluation ranged from 9% to 14.2% for the different nights. Surprisi ngly, the percentage of correctly classified time periods was even hig her for the lorazepam night as compared to the other nights.