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Beta EEG reflects sensory processing in active wakefulness and homeostatic sleep drive in quiet wakefulness

机译:Beta EEG反映了主动觉醒的感觉处理和安静觉醒的稳态睡眠驱动

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摘要

Markers of sleep drive (<10Hz; slow wave activity and theta) have been identified in the course of slow wave sleep (SWS) and wakefulness. So far, higher frequencies in the waking electroencephalogram have not been examined thoroughly as a function of sleep drive. Here, we measured EEG dynamics in epochs of active wake (AW; wake characterized by high muscle tone) or quiet wake (QW; wake characterized by low muscle tone). We hypothesized that the higher beta oscillations (15-35Hz, measured by local field potential and electroencephalography) represent fundamentally different processes in AW and QW.In AW, sensory-stimulation elevated beta activity in parallel with gamma (80-90Hz) activity, indicative of cognitive processing. In QW, beta activity paralleled slow wave activity (1-4Hz) and theta (5-8Hz) in tracking sleep need. Cerebral lactate concentration, a measure of cerebral glucose utilization, increased during AW whereas it declined during QW. Mathematical modeling of state-dependent dynamics of cortical lactate concentration was more precisely predictive when QW and AW were included as two distinct substates rather than a uniform state of wakefulness. The extent to which lactate concentration declined in QW and increased in AW was proportionate to the amount of beta activity.These data distinguish QW from AW. QW, particularly when characterized by beta activity, is permissive to metabolic and electrophysiological changes that occur in SWS. These data urge further studies on state dependent beta oscillations across species.
机译:在慢波睡眠(SWS)和清醒过程中已识别出睡眠驱动器标志(<10Hz;慢波活动和theta)。到目前为止,尚未完全检查醒来的脑电图中的较高频率是否与睡眠驱动有关。在这里,我们测量了主动觉醒(AW;以高肌张力为特征的觉醒)或安静觉醒(QW;以低肌张力为特征的觉醒)时期的脑电图动力学。我们假设较高的β振荡(通过局部场电势和脑电图测量的15-35Hz)代表了AW和QW的根本不同过程。在AW中,感觉刺激增加了β的活动,同时具有伽马(80-90Hz)的活动,这表明认知加工。在QW中,β活动与慢波活动(1-4Hz)和theta(5-8Hz)平行,可追踪睡眠需求。脑乳酸水平是衡量脑部葡萄糖利用率的指标,在​​AW期间升高,而在QW期间降低。当QW和AW被包括为两个不同的子状态而不是统一的清醒状态时,皮质乳酸浓度的状态相关动力学的数学模型可以更精确地预测。乳酸浓度在QW中下降并在AW中增加的程度与β活性成正比。这些数据将QW与AW区别开来。 QW,特别是当以β活性为特征时,允许SWS中发生的代谢和电生理变化。这些数据促使人们进一步研究物种间依赖状态的β振荡。

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