皮层上状态波动的随机放大
Stochastic Amplification of Fluctuations in Cortical Up-states
摘要：
皮层神经元是神经元;因此，它们的局部场电位可以在静止状态和活动状态之间波动，产生0.5-2 Hz的缓慢振荡，该振荡被广泛地称为上状态和下状态之间的转换。尽管有大量的研究向上向下转换，破译其性质，机制和功能今天仍然是具有挑战性的任务。在本文中，我们专注于最近的实验证据，表明一类自发振荡可以出现在向上状态。特别地，在它们的相关功率谱中出现了20 Hz附近的非平凡峰值，这产生了更高频率（在30-90 Hz频带中）的活动功率的增强。此外，Ups中的这种节律似乎是一种突发或集体现象，因为单个神经元并没有锁定它，因为它们大多保持不同步。值得注意的是，类似的振荡（以及光谱中伴随的峰值）不会出现在Down状态中。在这里，我们揭示了这些发现，通过使用不同的计算模型的动态皮质网络中存在的不同水平的生理复杂性。我们的结论，支持的理论和模拟，是集体现象的“随机放大的波动”-以前描述的其他背景下，如生态学和流行病学-解释在一个优雅和简约的方式，超越模型依赖的细节，这种额外的节奏出现只在向上状态，但不是在唐斯。
英文摘要：
Cortical neurons are bistable; as a consequence their local field potentials can fluctuate between quiescent and active states, generating slow 0.5-2 Hz oscillations which are widely known as transitions between Up and Down States. Despite a large number of studies on Up-Down transitions, deciphering its nature, mechanisms and function are still today challenging tasks. In this paper we focus on recent experimental evidence, showing that a class of spontaneous oscillations can emerge within the Up states. In particular, a non-trivial peak around 20 Hz appears in their associated power-spectra, what produces an enhancement of the activity power for higher frequencies (in the 30-90 Hz band). Moreover, this rhythm within Ups seems to be an emergent or collective phenomenon given that individual neurons do not lock to it as they remain mostly unsynchronized. Remarkably, similar oscillations (and the concomitant peak in the spectrum) do not appear in the Down states. Here we shed light on these findings by using different computational models for the dynamics of cortical networks in presence of different levels of physiological complexity. Our conclusion, supported by both theory and simulations, is that the collective phenomenon of "stochastic amplification of fluctuations" -previously described in other contexts such as Ecology and Epidemiology-- explains in an elegant and parsimonious manner, beyond model-dependent details, this extra-rhythm emerging only in the Up states but not in the Downs.
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