Stages and architecture of normal sleep
- Douglas Kirsch, MD, FAASM
Douglas Kirsch, MD, FAASM
- Clinical Associate Professor
- UNC School of Medicine
Sleep is a rapidly reversible state of reduced responsiveness, motor activity, and metabolism . It is a phenomenon observed in all animals in some form; this universality suggests that the act of sleeping likely has some evolutionary relevance. Humans spend approximately one-third of their life, or about eight hours per night, sleeping. The purpose of sleeping is poorly understood, however, and multiple theories exist. These theories include restoration, energy conservation, and memory consolidation.
The polysomnogram is the primary tool for assessing sleep in the laboratory for both clinical and research purposes. During a polysomnogram, electroencephalography (EEG) and other sensors are used to categorize sleep in discrete stages. Initial sleep staging was described in the 1930s, and formal rules for staging sleep were first propagated in 1968 . Since 2007, most sleep laboratories use terminology and scoring rules from the American Academy of Sleep Medicine (AASM) manual for the Scoring of Sleep and Associated Events, which is routinely updated . Sleep laboratories accredited by the AASM are required to use the AASM scoring manual, and these guidelines are being increasingly adopted worldwide .
This topic will review the current guidelines for adult sleep staging, the architecture of sleep, common causes of sleep stage abnormalities, and theories around the purposes for sleep. The classification of sleep disorders is reviewed separately. (See "Classification of sleep disorders".)
Sleep can be broadly segmented into rapid eye movement (REM) sleep and non-REM (NREM) sleep. Scoring of sleep stages occurs in 30-second epochs based on current American Academy of Sleep Medicine (AASM) scoring rules . The current rules mandate the use of electroencephalography (EEG), electromyography (EMG) for muscle tone, and electro-oculography (EOG) for eye movements, to determine the stage of sleep. This may change in the future to better align with sleep as a continuous process, by focusing attention on shorter epochs of sleep or through spectral analysis of sleep EEG.
A typical 30-second sleep study data epoch is provided in the figure (figure 1). The EEG data is derived from electrodes placed on the head in frontal, central, and occipital locations and referenced to bone according to the international 10-20 system (figure 2). As part of this system, odd numbers refer to the left side of the head and even numbers are right sided; typically, EEGs require bilateral monitoring, as left and right cerebral hemispheres may not provide identical data. While full EEG monitoring requires placement of all 10-20 electrodes, sleep staging requires only the partial grouping mentioned above (F3 and F4, C3 and C4, O1 and O2). Brainwaves are assessed by amplitude and frequency; different frequencies are associated with different stages of sleep (table 1).To continue reading this article, you must log in with your personal, hospital, or group practice subscription. For more information on subscription options, click below on the option that best describes you:
- Siegel JM. Sleep viewed as a state of adaptive inactivity. Nat Rev Neurosci 2009; 10:747.
- Rechtshaffen A, Kales A (Eds). A manual of standardized terminology and scoring system for sleep stages of human subjects. 204, United States Government Printing Office; National Institutes of Health, Washington, DC 1968.
- Berry RB, Brooks R, Gamaldo CE, et al. The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Specifications, version 2.4, American Academy of Sleep Medicine, Darien IL 2017.
- Magalang UJ, Chen NH, Cistulli PA, et al. Agreement in the scoring of respiratory events and sleep among international sleep centers. Sleep 2013; 36:591.
- Ohayon MM, Carskadon MA, Guilleminault C, Vitiello MV. Meta-analysis of quantitative sleep parameters from childhood to old age in healthy individuals: developing normative sleep values across the human lifespan. Sleep 2004; 27:1255.
- Agnew HW Jr, Webb WB, Williams RL. The first night effect: an EEG study of sleep. Psychophysiology 1966; 2:263.
- Proctor A, Bianchi MT. Clinical pharmacology in sleep medicine. ISRN Pharmacol 2012; 2012:914168.
- ASERINSKY E, KLEITMAN N. Regularly occurring periods of eye motility, and concomitant phenomena, during sleep. Science 1953; 118:273.
- Tononi G, Cirelli C. Perchance to prune. During sleep, the brain weakens the connections among nerve cells, apparently conserving energy and, paradoxically, aiding memory. Sci Am 2013; 309:34.
- American Academy of Sleep Medicine. International classification of sleep disorders: Diagnostic and coding manual, 2nd ed, Westchester, IL 2005.
- Weitzenblum E, Chaouat A. Sleep and chronic obstructive pulmonary disease. Sleep Med Rev 2004; 8:281.
- Howell MJ. Parasomnias: an updated review. Neurotherapeutics 2012; 9:753.
- España RA, Scammell TE. Sleep neurobiology from a clinical perspective. Sleep 2011; 34:845.
- Anderson KN, Bradley AJ. Sleep disturbance in mental health problems and neurodegenerative disease. Nat Sci Sleep 2013; 5:61.
- Porkka-Heiskanen T, Zitting KM, Wigren HK. Sleep, its regulation and possible mechanisms of sleep disturbances. Acta Physiol (Oxf) 2013; 208:311.
- Xie L, Kang H, Xu Q, et al. Sleep drives metabolite clearance from the adult brain. Science 2013; 342:373.
- Yang G, Lai CS, Cichon J, et al. Sleep promotes branch-specific formation of dendritic spines after learning. Science 2014; 344:1173.
- Diering GH, Nirujogi RS, Roth RH, et al. Homer1a drives homeostatic scaling-down of excitatory synapses during sleep. Science 2017; 355:511.
- de Vivo L, Bellesi M, Marshall W, et al. Ultrastructural evidence for synaptic scaling across the wake/sleep cycle. Science 2017; 355:507.
- Siegel JM. Clues to the functions of mammalian sleep. Nature 2005; 437:1264.
- Tononi G, Cirelli C. Sleep and the price of plasticity: from synaptic and cellular homeostasis to memory consolidation and integration. Neuron 2014; 81:12.