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相互关联的双时反馈回路可以增强对随机性和记忆持久性的鲁棒性。

Interlinked dual-time feedback loops can enhance robustness to stochasticity and persistence of memory.

作者信息

Smolen Paul, Baxter Douglas A, Byrne John H

机构信息

Department of Neurobiology and Anatomy, W.M. Keck Center for the Neurobiology of Learning and Memory, The University of Texas Medical School at Houston, P.O. Box 20708, Houston, Texas 77225, USA.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2009 Mar;79(3 Pt 1):031902. doi: 10.1103/PhysRevE.79.031902. Epub 2009 Mar 4.

Abstract

Multiple interlinked positive feedback loops shape the stimulus responses of various biochemical systems, such as the cell cycle or intracellular Ca2+ release. Recent studies with simplified models have identified two advantages of coupling fast and slow feedback loops. This dual-time structure enables a fast response while enhancing resistances of responses and bistability to stimulus noise. We now find that (1) the dual-time structure similarly confers resistance to internal noise due to molecule number fluctuations, and (2) model variants with altered coupling, which better represent some specific biochemical systems, share all the above advantages. We also develop a similar bistable model with coupling of a fast autoactivation loop to a slow loop. This model's topology was suggested by positive feedback proposed to play a role in long-term synaptic potentiation (LTP). The advantages of fast response and noise resistance are also present in this autoactivation model. Empirically, LTP develops resistance to reversal over approximately 1h . The model suggests this resistance may result from increased amounts of synaptic kinases involved in positive feedback.

摘要

多个相互关联的正反馈回路塑造了各种生化系统的刺激反应,如细胞周期或细胞内Ca2+释放。最近使用简化模型的研究已经确定了耦合快速和慢速反馈回路的两个优点。这种双时结构能够实现快速响应,同时增强响应的抗性和对刺激噪声的双稳态。我们现在发现:(1)双时结构同样赋予了对由于分子数波动引起的内部噪声的抗性;(2)具有改变耦合的模型变体,能更好地代表某些特定生化系统,具备上述所有优点。我们还开发了一个类似的双稳态模型,该模型将快速自激活回路与慢速回路耦合。这个模型的拓扑结构是由被认为在长时程突触增强(LTP)中起作用的正反馈所提出的。快速响应和抗噪声的优点在这个自激活模型中也存在。从经验上看,LTP在大约1小时内产生对逆转的抗性。该模型表明这种抗性可能源于参与正反馈的突触激酶数量增加。

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