Abstract
In healthy subjects, sleep has a typical structure of three to five cyclic transitions between different sleep states. In major depression, this regular pattern is often destroyed but can be reestablished during successful treatment. The differences between healthy and abnormal sleep are generally assessed in a time-consuming process, which consists of determining the nightly variations of the sleep states (the hypnogram) based on visual inspection of the electroencephalogram (EEG), electrooculogram, and electromyogram. In this study, three different methods of sleep EEG analysis (spectrum, outlier, and recurrence analysis) have been examined with regard to their ability to extract information about treatment effects in patients with major depression. Our data suggest that improved sleep patterns during treatment with antidepressant medication can be identified with an appropriate analysis of the EEG. By comparing different methods, we have found that many treatment effects identified by spectrum analysis can be reproduced by the much simpler technique of outlier analysis. Finally, the cyclic structure of sleep and its modification by antidepressant treatment is best illustrated by a non-linear approach, the so-called recurrence method.
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This work was supported by the European Union through the Network of Excellence BioSim, contract no. LSHB-CT-2004-005137.
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Figueroa Helland, V.C., Postnova, S., Schwarz, U. et al. Comparison of Different Methods for the Evaluation of Treatment Effects from the Sleep EEG of Patients with Major Depression. J Biol Phys 34, 393–404 (2008). https://doi.org/10.1007/s10867-008-9096-x
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DOI: https://doi.org/10.1007/s10867-008-9096-x