The suprachiasmatic nucleus (SCN), also known as the circadian master clock, consists of a large population of oscillator neurons. Together, these neurons produce a coherent signal that drives the body's circadian rhythms. What properties of the cell-to-cell communication allow the synchronization of these neurons, despite a wide range of environmental challenges such as fluctuations in photoperiods? To answer that question, we present a mean-field description of globally coupled neurons modeled as Goodwin oscillators with standard Gaussian noise. Provided that the initial conditions of all neurons are independent and identically distributed, any finite number of neurons becomes independent and has the same probability distribution in the mean-field limit, a phenomenon called propagation of chaos. This probability distribution is a solution to a Vlasov-Fokker-Planck type equation, which can be obtained from the stochastic particle model. We study, using the macroscopic description, how the interaction between external noise and intercellular coupling affects the dynamics of the collective rhythm, and we provide a numerical description of the bifurcations resulting from the noise-induced transitions. Our numerical simulations show a noise-induced rhythm generation at low noise intensities, while the SCN clock is arrhythmic in the high noise setting. Notably, coupling induces resonance-like behavior at low noise intensities, and varying coupling strength can cause period locking and variance dissipation even in the presence of noise.
翻译:超异谱核心(SCN)也称为环形总钟,由大量的振动器神经神经元组成。这些神经元一起产生一个一致的信号,驱动身体的振动神经元节奏。细胞对细胞通信的特性允许这些神经元同步,尽管存在一系列广泛的环境挑战,如光期波动;为了回答这个问题,我们提出了一个以古德温振动器和标准高斯噪音为模型的全球相伴神经元的中位描述。只要所有神经元的初始条件是独立和相同的分布,任何有限的神经元数量都变得独立,在平均限值中具有相同的概率分布,一种叫做混乱的传播现象。这种概率分布是Vlasov-Fokker-Purck 型方程式的解决方案,可以从随机粒子模型中获取。我们用宏观分解描述,外部噪音和细胞间组合之间的相互作用如何影响集体节奏的动态,我们提供了在平均限值限制范围内的神经元存在数量,并且具有相同的概率分布,在平均限值范围内的概率分布着相同的概率分布,而我们所生成的快速度则显示的是,在高变压期中, 。