稳态.神经网络与神经行为学-神经科学百科全书 节选

《神经科学百科全书11:稳态、神经网络与神经行为学(导读版)》原书篇幅巨大，为所有神经科学百科全书之首。由来自世界各地的2400多位专家撰稿人合力打造，覆盖了神经科学全部主要领域。每个词条在收入书中之前均经过顾问委员会的同行评议，词条中均含有词汇表、引言、参考文献和丰富的交叉参考内容。主编为著名神经科学家、美国神经科学学会前主席LarryR.Squire。内容平易，本科生即可读懂。深度和广度独一无二，足可满足专家学者的需要。导读版精选原书中的部分主题，按内容重新编排，更适合国内读者购买和阅读。

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插图：However, over much longer periods （several days）, experimental work has demonstrated that growth cones can respond to gradients of 0.2% or less across their spatial extent. Furthermore, at sufficiently high and low concentrations, almost all or almost no receptors are bound: this leads to further reductions in sensitivity. Experimental and theoretical work has confirmed that the highest sensitivity is achieved when approximately half of the receptors are bound, which occurs when the concentration is equal to the dissociation constant for binding. Aside from these general constraints on gradient detection, models have also been developed which directly simulate the behavior of growth cones and axons in the presence of guidance cue gradients. Several models have focused on biochemical networks which are putatively responsible for growth cone motility and guidance. Such models are difficult to construct, partly due to the complexity of growth cone biochemistry and partly due to the lack of experimental data on important quantities such as reaction rate constants, concentrations, and interactions between molecular species. One model has focused on the Rho-GTPase signaling network, which is known to play an important role in actin-driven cell motility. Due to incomplete experimental data, the investigators took a qualitative approach, simulating the behavior of several plausible interaction networks and kinetic constants and using the results of these simulations to form hypotheses about the underlying mechanisms of growth cone motility. They found that the Rho-GTPase network undergoes a sharp transition in its dynamics when a threshold concentration of a particular signaling molecule is reached. The authors linked these two dynamic behaviors to different modes of growth cone motility, developing a model which could reproduce sme experimentally observed phenomena.

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