The Role of Presynaptic Dynamics in Processing of Natural Spike Trains in Hippocampal Synapses
The Role of Presynaptic Dynamics in Processing of Natural Spike Trains in Hippocampal Synapses
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DOI：
10.1523/jneurosci.4050-10.2010
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发表时间：
2010-11-24
影响因子：
5.3
通讯作者：
Klyachko, Vitaly A.
中科院分区：
文献类型：
--
作者：
Kandaswamy, Umasankar;Deng, Pan-Yue;Klyachko, Vitaly A.
短时程可塑性（STP）是神经元信息加工的重要机制。在兴奋性海马突触，STP作为一个高通滤波器的传输信息携带的位置场放电优化。该STP滤波器使突触能够执行高度非线性的开关式操作，从而允许具有类似场特性的信号通过和放大。由于STP过程之间的相互作用的复杂性，这种过滤范式的突触机制仍然知之甚少。在这里，我们描述了一个简单的机制模型STP，在很大程度上来自突触功能的基本原则，再现这种高度非线性的突触行为。该模型，制定的释放概率，认为钙依赖形式的突触前增强和它们对囊泡池动态的影响，这是使用一个两池模型的囊泡招聘之间的相互作用。通过考虑释放概率和各种形式的STP之间的相互依赖性，该模型试图提供一个现实的主要突触前过程之间的耦合。模型参数首先确定在恒定频率刺激期间使用突触动力学。然后，该模型准确地再现了所有的主要特征的突触过滤范式在自然的刺激模式，没有自由参数。然后使用消除方法来识别每个STP组件对突触动力学的贡献。基于此分析，该模型预测突触过滤特性的强钙依赖性，这在大鼠海马脑片中得到了实验验证。因此，这个简单的模型可以提供一个有用的框架，以进一步研究STP在神经计算中的作用。
Short-term plasticity (STP) represents a key neuronal mechanism of information processing. In excitatory hippocampal synapses, STP serves as a high-pass filter optimized for the transmission of information-carrying place-field discharges. This STP filter enables synapses to perform a highly nonlinear, switch-like operation permitting the passage and amplification of signals with place-field-like characteristics. Because of the complexity of interactions among STP processes, the synaptic mechanisms underlying this filtering paradigm remain poorly understood. Here, we describe a simple mechanistic model of STP, derived in large part from basic principles of synaptic function, that reproduces this highly nonlinear synaptic behavior. The model, formulated in terms of release probability, considers the interactions between calcium-dependent forms of presynaptic enhancement and their impact on vesicle pool dynamics, which is described using a two-pool model of vesicle recruitment. By considering the interdependency between release probability and various forms of STP, the model attempts to provide a realistic coupling among major presynaptic processes. The model parameters are first determined using synaptic dynamics during constant-frequency stimulation. The model then accurately reproduces all major characteristics of the synaptic filtering paradigm during natural stimulus patterns without free parameters. An elimination approach is then used to identify the contribution of each STP component to synaptic dynamics. Based on this analysis, the model predicts strong calcium dependence of synaptic filtering properties, which is verified experimentally in rat hippocampal slices. This simple model may thus offer a useful framework to further investigate the role of STP in neural computations.