COMPUTATION AND SYNAPTIC MODIFICATION IN THE DENTATE

这项研究的长期目标是了解 海马体。海马体被认为在 学习和记忆功能，涉及多个主要领域 神经紊乱。如果我们要了解海马体的功能，我们 必须了解计算和突触修改是如何在 海马体的细胞。 计算机建模是研究海马区的一种新的有力工具 功能。单个神经元的计算机模型可以用来测试 难以在实验中解决的假设，可以提供具体的 对观察到的现象的机制的预测。在这项研究中 海马齿状颗粒细胞的非常详细的模型将是 发展起来的。这些模型将包括完整的形态以及 突触和非突触电导的数学描述以及 控制细胞内钙浓度的过程。模特们将成为 尽可能地逼真，以与可观的身体保持一致 可用的实验数据。 这些高度详细的模型将用于：1)评估 齿状突起作用的形态和电紧张性结构 颗粒细胞。2)确定以下计算可能性的范围 这些细胞给出了它们互补的离子通道类型、分布和 密度。在某些情况下，计算可能性如何变化 参数值的变化可能会揭示某些现象 病理情况。3)解释钙浓度是如何变化的 该细胞可能与长时程增强的诱导有关。 (LTP)或长期抑郁(LTD)。如果我们了解LTP和LTD 发生，我们将在理解学习是如何进行的方面取得了长足进步 和记忆的发生。4)推导包括突触修改的方法 在与LTP和LTP的实验观察一致的模型中 LTD. 这项研究将提供对计算和 齿状颗粒细胞的突触修饰。这将告诉我们如何 非常详细的模型可能会简化为对齿状结构的简单描述 颗粒细胞保留了这些细胞的基本计算特征 细胞。然后，这些简单的描述可以用于复杂网络 研究海马区功能的模型。

The long-term goal of this research is to understand the function of the hippocampus. The hippocampus is thought to play an important role in learning and memory functions and is involved in a number of major neurological disorders. If we are to understand hippocampal function, we must understand how computation and synaptic modification take place in the cells of the hippocampus. Computer modeling is a new and powerful tool for studying hippocampal function. Computer models of individual neurons can he used to test hypotheses difficult to address experimentally and can provide specific predictions about the mechanisms of observed phenomena. In this research highly detailed models of hippocampal dentate granule cells will be developed. These models will include complete morphology along with mathematical descriptions of synaptic and non-synaptic conductances and of processes that control calcium concentration in the cell. Models will be made as realistic as possible to be consistent with the considerable body of experimental data available. These highly detailed models will be used to: 1) Assess the importance of the morphological and electrotonic structure for the function of dentate granule cells. 2) Determine the range of computational possibilities of these cells given their complement of ion channel types, distributions and densities. How the computational possibilities change when certain parameter values change might reveal phenomena seen with certain pathological conditions. 3) Explain how calcium concentration changes in the cell might be correlated with the induction of long-term potentiation (LTP) or long-term depression (LTD). If we understand how LTP and LTD occur, we will have made great strides towards understanding how learning and memory take place. 4) Deduce a means to include synaptic modification in models that is consistent with experimental observations of LTP and LTD. This research will provide a quantitative understanding of computation and synaptic modification in dentate granule cells. This will tell us how highly detailed models might be reduced to simple descriptions of dentate granule cells that retain the essential computational features of these cells. These simple descriptions can then be used in complex network models to investigate hippocampal function.