Bell Laboratories, Alcatel-Lucent , Murray Hill, NJ , USA.
BioCircuits Institute, University of California San Diego , La Jolla, CA , USA.
Front Neurol. 2015 Feb 26;6:32. doi: 10.3389/fneur.2015.00032. eCollection 2015.
Identifying the neuronal circuits and dynamics of sleep-to-wake transition is essential to understanding brain regulation of behavioral states, including sleep-wake cycles, arousal, and hyperarousal. Recent work by different laboratories has used optogenetics to determine the role of individual neuromodulators in state transitions. The optogenetically driven data do not yet provide a multi-dimensional schematic of the mechanisms underlying changes in vigilance states. This work presents a modeling framework to interpret, assist, and drive research on the sleep-regulatory network. We identify feedback, redundancy, and gating hierarchy as three fundamental aspects of this model. The presented model is expected to expand as additional data on the contribution of each transmitter to a vigilance state becomes available. Incorporation of conductance-based models of neuronal ensembles into this model and existing models of cortical excitability will provide more comprehensive insight into sleep dynamics as well as sleep and arousal-related disorders.
确定睡眠到觉醒转换的神经元回路和动力学对于理解大脑对行为状态的调节至关重要,包括睡眠-觉醒周期、觉醒和过度觉醒。不同实验室的最近工作已经使用光遗传学来确定单个神经调质在状态转换中的作用。光遗传学驱动的数据尚未提供警觉状态变化背后机制的多维示意图。这项工作提出了一个建模框架,用于解释、辅助和推动睡眠调节网络的研究。我们将反馈、冗余和门控层次结构确定为该模型的三个基本方面。随着关于每种递质对警觉状态贡献的更多数据的出现,预计该模型将会扩展。将神经元集合的基于电导率的模型纳入该模型和现有的皮质兴奋性模型将为睡眠动力学以及与睡眠和觉醒相关的障碍提供更全面的见解。