VISUAL SLEEP STAGING IS STILL THE MOST WIDELY USED PROCEDURE TO ANALYZE SLEEP. IT ALLOWS ONE TO SUBDIVIDE SLEEP RECORDINGS INTO discrete states

VISUAL SLEEP STAGING IS STILL THE MOST WIDELY USED PROCEDURE TO ANALYZE SLEEP. IT ALLOWS ONE TO SUBDIVIDE SLEEP RECORDINGS INTO discrete states or stages, defined by coherent and recurrent patterns of one1 or more2 electrophysiologic signals. Based on this method, human sleep has been defined as an alternating sequence of 4 stages of non-rapid eye movement sleep (NREM stages 1 to 4), and rapid eye movement (REM) sleep.3 Although there is unanimous acceptance of the existence of 2 different states of sleep, REM and NREM sleep, different conceptions of the structure of NREM sleep have been proposed. Based on quantitative electroencephalographic analysis during sleep, NREM sleep can be represented as a continuum instead of a staged process.4,5 A continuous representation of NREM sleep allows one to model the sleep process by quantitative variables, such as the mean electroencephalographic (EEG) frequency or the power of different EEG frequency bands.6,7,8 In contrast with this, the strongest point for sleep staging is that it allows the integration of a variety of electrophysiologic information from different recording channels into a reasonably small number of well-defined stages. Sleep staging is confronted with 2 major difficulties: first, how to exactly delineate neighboring stages, and second, how to handle intrastate variability? Both points have an influence on the reliability of sleep studies.9 Although rules for the definition of sleep states and stages have been developed,2 the question of intrastate heterogeneity has been widely ignored. Exceptions consist of a few scattered proposals to subdivide the sleep-onset process into fine-graded steps,10 to study differences between stage 2 sleep early and late in night-time sleep,11 or to subdivide NREM and REM sleep into tonic and phasic segments.12 Another approach to subdivide the NREM sleep process into meaningful subunits has been proposed by Terzano and coworkers.13,14 These authors developed the concept of a cyclic alternating pattern (CAP), corresponding to different functional states of arousal-control mechanisms during NREM sleep.15 In a recent study, Brandenberger et al16 called into question the homogeneity of stage 2 sleep. These authors presented data that suggest that 2 types of stage 2 sleep can be differentiated, a quiet one, preceding slow-wave sleep, and an active one, preceding REM sleep. Sleep staging is a rule-based procedure, which uses expert knowledge to define which combination of electrophysiologic patterns defines a sleep stage.2 As an alternative, a statistical analysis could explore which pattern configurations, extracted from EEG, electromyogram (EMG), electrooculogram, or any other physiologic signal, are either typical, ie, occur more frequently, or atypical, i.e., occur less frequently, relative to one’s expectation. The configural frequency analysis (CFA)17 is a nonparametric taxonomic statistical analysis that allows one to identify overrepresentations (types) or underrepresentations (antitypes) in the frequency distribution of multiple variable classifications. This procedure examines the statistical significance of patterns of cell frequencies in cross-tabulated data and defines types or antitypes, depending on whether observed cell frequencies are greater or smaller than expected by the marginal distribution. The objective of the present study was to investigate the structure of sleep by means of the CFA. We applied the CFA to 3 continuously measured variables during sleep: (a) an EEG parameter (EEG-P), representing the distribution of EEG wave lengths, A Taxonomic Analysis of Sleep Stages