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      The nature of arousal in sleep.

      Journal of Sleep Research
      Arousal, physiology, Autonomic Nervous System, Brain, Cortical Synchronization, Electroencephalography, Humans, Sleep, Sleep Stages

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          Abstract

          The role of arousals in sleep is gaining interest among both basic researchers and clinicians. In the last 20 years increasing evidence shows that arousals are deeply involved in the pathophysiology of sleep disorders. The nature of arousals in sleep is still a matter of debate. According to the conceptual framework of the American Sleep Disorders Association criteria, arousals are a marker of sleep disruption representing a detrimental and harmful feature for sleep. In contrast, our view indicates arousals as elements weaved into the texture of sleep taking part in the regulation of the sleep process. In addition, the concept of micro-arousal (MA) has been extended, incorporating, besides the classical low-voltage fast-rhythm electroencephalographic (EEG) arousals, high-amplitude EEG bursts, be they like delta-like or K-complexes, which reflects a special kind of arousal process, mobilizing parallely antiarousal swings. In physiologic conditions, the slow and fast MA are not randomly scattered but appear structurally distributed within sleep representing state-specific arousal responses. MA preceded by slow waves occurs more frequently across the descending part of sleep cycles and in the first cycles, while the traditional fast type of arousals across the ascending slope of cycles prevails during the last third of sleep. The uniform arousal characteristics of these two types of MAs is supported by the finding that different MAs are associated with an increasing magnitude of vegetative activation ranging hierarchically from the weaker slow EEG types (coupled with mild autonomic activation) to the stronger rapid EEG types (coupled with a vigorous autonomic activation). Finally, it has been ascertained that MA are not isolated events but are basically endowed with a periodic nature expressed in non-rapid eye movement (NREM) sleep by the cyclic alternating pattern (CAP). Understanding the role of arousals and CAP and the relationship between physiologic and pathologic MA can shed light on the adaptive properties of the sleeping brain and provide insight into the pathomechanisms of sleep disturbances. Functional significance of arousal in sleep, and particularly in NREM sleep, is to ensure the reversibility of sleep, without which it would be identical to coma. Arousals may connect the sleeper with the surrounding world maintaining the selection of relevant incoming information and adapting the organism to the dangers and demands of the outer world. In this dynamic perspective, ongoing phasic events carry on the one hand arousal influences and on the other elements of information processing. The other function of arousals is tailoring the more or less stereotyped endogenously determined sleep process driven by chemical influences according to internal and external demands. In this perspective, arousals shape the individual course of night sleep as a variation of the sleep program.

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          Functional neuroanatomy of human rapid-eye-movement sleep and dreaming.

          Rapid-eye-movement (REM) sleep is associated with intense neuronal activity, ocular saccades, muscular atonia and dreaming. The function of REM sleep remains elusive and its neural correlates have not been characterized precisely in man. Here we use positron emission tomography and statistical parametric mapping to study the brain state associated with REM sleep in humans. We report a group study of seven subjects who maintained steady REM sleep during brain scanning and recalled dreams upon awakening. The results show that regional cerebral blood flow is positively correlated with REM sleep in pontine tegmentum, left thalamus, both amygdaloid complexes, anterior cingulate cortex and right parietal operculum. Negative correlations between regional cerebral blood flow and REM sleep are observed bilaterally, in a vast area of dorsolateral prefrontal cortex, in parietal cortex (supramarginal gyrus) as well as in posterior cingulate cortex and precuneus. Given the role of the amygdaloid complexes in the acquisition of emotionally influenced memories, the pattern of activation in the amygdala and the cortical areas provides a biological basis for the processing of some types of memory during REM sleep.
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            The functional states of the thalamus and the associated neuronal interplay.

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              Low-frequency (< 1 Hz) oscillations in the human sleep electroencephalogram.

              Low-frequency (< 1 Hz) oscillations in intracellular recordings from cortical neurons were first reported in the anaesthetized cat and then also during natural sleep. The slow sequences of hyperpolarization and depolarization were reflected by slow oscillations in the electroencephalogram. The aim of the present study was to examine whether comparable low-frequency components are present in the human sleep electroencephalogram. All-night sleep recordings from eight healthy young men were subjected to spectral analysis in which the low-frequency attenuation of the amplifier was compensated. During sleep stages with a predominance of slow waves and in the first two episodes of non-rapid-eye-movement sleep, the mean power spectrum showed a peak at 0.7-0.8 Hz (range 0.55-0.95 Hz). The typical decline in delta activity from the first to the second non-rapid-eye-movement sleep episode was not present at frequencies below 2 Hz. To detect very low frequency components in the pattern of slow waves and sleep spindles, a new time series was computed from the mean voltage of successive 0.5 s epochs of the low-pass (< 4.5 Hz) or band-pass (12-15 Hz) filtered electroencephalogram. Spectral analysis revealed a periodicity of 20-30 s in the prevalence of slow waves and a periodicity of 4 s in the occurrence of activity in the spindle frequency range. The results demonstrate that distinct components below 1 Hz are also present in the human sleep electroencephalogram spectrum. The differences in the dynamics between the component with a mean peak value at 0.7-0.8 Hz and delta waves above 2 Hz is in accordance with results from animal experiments.
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