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上下皮质动态反映双稳态网络中的状态转变。

UP-DOWN cortical dynamics reflect state transitions in a bistable network.

机构信息

Institut d'Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain.

Centre de Recerca Matemàtica, Bellaterra, Spain.

出版信息

Elife. 2017 Aug 4;6:e22425. doi: 10.7554/eLife.22425.

Abstract

In the idling brain, neuronal circuits transition between periods of sustained firing (UP state) and quiescence (DOWN state), a pattern the mechanisms of which remain unclear. Here we analyzed spontaneous cortical population activity from anesthetized rats and found that UP and DOWN durations were highly variable and that population rates showed no significant decay during UP periods. We built a network rate model with excitatory (E) and inhibitory (I) populations exhibiting a novel bistable regime between a quiescent and an inhibition-stabilized state of arbitrarily low rate. Fluctuations triggered state transitions, while adaptation in E cells paradoxically caused a marginal decay of E-rate but a marked decay of I-rate in UP periods, a prediction that we validated experimentally. A spiking network implementation further predicted that DOWN-to-UP transitions must be caused by synchronous high-amplitude events. Our findings provide evidence of bistable cortical networks that exhibit non-rhythmic state transitions when the brain rests.

摘要

在空闲的大脑中,神经元回路在持续发射(UP 状态)和静止(DOWN 状态)之间转换,其机制尚不清楚。在这里,我们分析了麻醉大鼠的自发皮层群体活动,发现 UP 和 DOWN 的持续时间变化很大,并且群体速率在 UP 期间没有明显下降。我们建立了一个具有兴奋性(E)和抑制性(I)群体的网络速率模型,它们在一个静止和一个抑制稳定状态之间表现出一种新颖的双稳态状态,其速率任意低。波动引发状态转换,而 E 细胞的适应作用反而是 UP 期间 E 率的轻微下降,但 I 率的显著下降,这一预测我们通过实验进行了验证。一个尖峰网络的实现进一步预测 DOWN 到 UP 的转变必须是由同步的高振幅事件引起的。我们的发现为大脑休息时表现出非节律性状态转换的双稳态皮质网络提供了证据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17d2/5582872/512854f9b34e/elife-22425-fig1.jpg

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