Paroxetine is a selective and potent serotonin reuptake inhibitor and its efficacy for the treatment of depression has been proven. Under acute and subchronical treatment regimens, disturbances of the regular sleep pattern are a reported side effect of the drug. The present study was therefore performed to investigate the impact of subchronic treatment with the selective serotonin reuptake inhibitor paroxetine on the microstructure of the sleep EEG. The study especially addressed the question of subchronic effects of paroxetine medication (30 mg/day) in eight healthy male volunteers in a double blind, placebo-controlled crossover design. Conventional sleep EEG parameters and a spectral power analysis for different sleep stages after 4 weeks of treatment were computed. Additionally, the correlation of certain EEG rhythms across the night was calculated in order to detect subtle dynamical EEG alterations, not necessarily obvious when regarding conventional EEG analysis. Although we could not detect any alterations of the spectral power values in certain frequency bands either during NREM nor during REM sleep following subchronic paroxetine medication, the dynamical EEG attributes across the night revealed a significant enhancement of the correlation between certain EEG rhythms mainly during NREM sleep.
In earlier publications we described an automatic algorithm to detect rapid eye movement (REM) sleep from a single-channel EEG recording without using EMG or EOG information. This system consisted of an artificial neural network operating on the basis of preprocessed EEG data and was composed to provide a maximum of robustness for online applications. In the present study the influence of acute administration of lorazepam 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 of the second night the volunteers received a single dosage of 2.5 mg Lorazepam; the other two nights were drug-free. The sleep profile and the quantitative EEG data reflected the known changes following acute administration of benzodiazepines: during the treatment night the amount of non-REM sleep and the relative power of the EEG signal in the beta and gamma frequency bands was increased relative to the first night, while the amount of REM sleep was reduced. The night of drug discontinuation 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. Surprisingly, the percentage of correctly classified time periods was even higher for the lorazepam night as compared to the other nights.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.