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中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。揭示这种节律的未知机制将有助于我们理解正常功能和病理学中脑节律的起源。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。慢振荡的超极化（沉默）阶段与去便利化有关，即所有皮层和丘脑神经元中暂时缺乏突触活动。SWS期间的去极化（活跃）皮层状态与大脑的清醒状态有许多相似之处。我们建议，SWS睡眠振荡是一个非常大的神经元群体的属性，是由在沉默状态下，去极化皮层锥体细胞膜足以产生尖峰，从而启动活跃的网络状态的微型兴奋性突触后电位的总和。在活动状态期间积累的内在和突触性质的变化触发向沉默状态的转变。活跃和沉默状态之间的重复转换触发长期突触可塑性，增强了由先前清醒状态引起的突触异质性。这可以解释SWS振荡在巩固清醒期间获得的记忆痕迹中的作用。在我们的研究中，我们将使用电生理学和神经解剖学技术和不同复杂程度的计算机模拟。实验将在自然睡眠和麻醉的动物体内和体外脑切片上进行。详细的Hodgkin-Huxley型计算机模型将根据解剖学和生理学数据开发，并将用于研究SWS活动产生所涉及的特定细胞和网络机制。将开发一个计算效率高、解剖学上真实的网络模型，该模型包含数十万个与真实突触互连的神经元，以模拟SWS期间丘脑皮质系统的大规模动力学。将在拉瓦尔大学使用多位点EEG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）及其组合收集实验数据。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慢波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）的数据，流行病学数据表明，大约30%至35%的普通人群抱怨与睡眠有关的问题。睡眠障碍-特别是睡眠呼吸暂停，睡眠剥夺和嗜睡-影响7000万美国人，导致每年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.