Cortical mechanisms and functional role of slow sleep oscillations

描述（由申请人提供）：本研究的目的是了解丘脑皮质系统慢波睡眠振荡的内在和电路机制。睡眠对健康和幸福至关重要。睡眠障碍越来越多地由生活方式和环境因素引起，可能与各种精神障碍有关。最近的研究表明，慢波睡眠（SWS）可能对记忆的形成和巩固至关重要。揭示介导这种节律的未知机制将有助于我们理解正常功能和病理中大脑节律的起源。在慢波睡眠（SWS）期间，整个皮层网络在沉默和活跃状态之间交替，每次持续0.2-1秒。慢波振荡的超极化（沉默）阶段与失易化有关，即所有皮层和丘脑神经元暂时缺乏突触活动。在SWS期间去极化（活跃）的皮质状态与大脑的清醒状态有许多相似之处。我们认为，SWS睡眠振荡是非常大的神经元群的特性，是由沉默状态下的微小兴奋性突触后电位的叠加引起的，这种状态使皮质锥体细胞膜去极化，足以产生尖峰，从而启动活跃的网络状态。在活跃状态中积累的内在和突触特性的变化触发了向沉默状态的过渡。活跃和沉默状态之间的反复转换触发了长期的突触可塑性，增强了先前清醒状态导致的突触异质性。这也许可以解释SWS振荡在巩固清醒时获得的记忆痕迹中的作用。在我们的研究中，我们将使用不同复杂程度的电生理和神经解剖学技术以及计算机模拟。实验将在自然睡眠和麻醉的动物体内进行，并在体外对大脑切片进行。详细的霍奇金-赫胥黎型计算机模型将基于解剖学和生理学数据开发，并将用于研究涉及SWS活动产生的特定细胞和网络机制。一个计算效率高且解剖学上真实的网络模型，包含数十万个神经元与真实的突触相互连接，将被开发用于模拟SWS期间丘脑皮质系统的大规模动态。实验数据将在拉瓦尔大学收集，使用多地点脑电图和多单元记录（多达64个通道），细胞内记录（多达4个同时记录的神经元）以及它们的组合。实验数据的计算分析、模型开发和模拟将在索尔克研究所进行。本研究为进一步研究SWS在突触可塑性和记忆巩固中的作用奠定了基础。根据世界卫生组织（www.WHO.int），流行病学数据表明，大约30%至35%的普通民众抱怨与睡眠有关的问题。睡眠障碍——尤其是睡眠呼吸暂停、睡眠剥夺和困倦——影响着7000万美国人，每年造成160亿美元的医疗费用和500亿美元的生产力损失。更好地了解睡眠期间大脑活动的机制和功能是未来临床研究和干预的重要基础。

DESCRIPTION (provided by applicant): The goal of this research is to understand intrinsic and circuit mechanisms underlying slow wave sleep oscillations in the thalamocortical system. Sleep is essential for health and well-being. Sleep disturbances, increasingly caused by lifestyle and environmental factors, can be linked to a variety of mental disorders. Recent studies have reported that slow wave sleep (SWS) may be essential for memory formation and consolidation. Revealing yet unknown mechanisms mediating this rhythm will aid our understanding of the origins of brain rhythms in both normal function and pathology. During slow wave sleep (SWS) the entire cortical network alternates between silent and active states, each lasting 0.2-1 sec. The hyperpolarizing (silent) phase of the slow oscillation is associated with disfacilitation, a temporal absence of synaptic activity in all cortical and thalamic neurons. Depolarized (active) cortical states during SWS have many similarities with the wake state of the brain. We propose that SWS sleep oscillations are property of a very large neuronal population and are caused by the summation of miniature excitatory postsynaptic potentials during the silent state that depolarizes the cortical pyramidal cell membrane sufficiently for spike generation thus initiating the active network state. Changes of intrinsic and synaptic properties accumulated during the active state trigger a transition to the silent state. Repetitive transitions between active and silent states trigger long-term synaptic plasticity enhancing the synaptic heterogeneity that results from previous states of wakefulness. This may explain the role of SWS oscillations in consolidation of memory traces acquired during wakefulness. In our study we will use electrophysiological and neuroanatomical techniques and computer simulations with different levels of complexity. Experiments will be conducted on naturally sleeping and anesthetized animals in vivo and on brain slices in vitro. Detailed Hodgkin-Huxley type computer models will be developed based on anatomical and physiological data and will be used to study specific cellular and network mechanisms involved in the generation of SWS activity. A computationally efficient and anatomically realistic network models containing hundreds of thousands of neurons interconnected with realistic synapses will be developed to model large- scale dynamics of the thalamocortical system during SWS. Experimental data will be collected at Laval University using multisite EEG and multiunit recordings (up to 64 channels), intracellular recordings (up to 4 simultaneously recorded neurons), and their combination. Computational analysis of the experimental data, model development and simulations will be conducted at the Salk Institute. This study will provide a ground for future studies of the role of SWS in synaptic plasticity and memory consolidation. According to the World Health Organization (www.WHO.int), epidemiological data suggests that about 30 to 35% of the general population complains about sleep-related problems. Sleep disorders - notably sleep apnea, sleep deprivation and sleepiness - affect 70 million Americans, resulting in $16 billion in annual healthcare expenses and $50 billion in lost productivity. A better mechanistic and functional understanding of brain activity during sleep represents an important basis for future clinical research and intervention.