COMPUTER METHODS FOR PHYSIOLOGICAL PROBLEMS

用于网络模拟的神经元模型通常是这样的 过于简单化的研究试图理解 活动完全是神经元相互连接的结果 一直是一个值得怀疑的价值。我们计划用来模拟小型神经网络 真实的神经元模型，看看我们是否可以确定 神经元形态和通道分布的详细信息 产出模式趋同。 长期以来，我们一直使用计算机模拟来了解 单个神经细胞及其形态和离子的相对贡献 频道。我们已经开发了一个程序，CABLE，(可在PC和Unix上使用 工作站)来模拟具有复杂分支的神经元 形态多样，河道类型多样，河道分布不均匀。 用它来解释实验结果的一个很好的例子 部分性电活动引起的动作电位传播的失效和恢复 多发性硬化症的脱髓鞘和新的结节形成。我们计划 改进我们现有的计算机软件，以使神经畅销 数值计算方面的非专业人员更容易完成模拟任务 方法：研究方法。神经元模拟软件将扩展为包括 几个新功能，其中最重要的是(A)，取代了 基于神经网络规范的空间离散化方法 根据神经元的组成部分(如胞体，轴突， 和树突状树)，(B)，增加突触连接 单个神经元，以及(C)使用高级模型描述 允许用户定义其他生理机制和 将它们插入神经元上的任何一组位置。

The models of neurons used in network simulations have usually been so oversimplified that studies which have attempted to understand patterns of activity solely as a consequence of the interconnections of the neurons have been a dubious value. We plan to simulate small nerve networks with realistic neuron models in order to see if we can determine the level of detail of neuron morphology and channel distribution at which network output patterns converge. We have long used computer simulations to understand the functioning of single nerve cells and the relative contributions of morphology and ionic channels. We have developed a program,CABLE,(available on PC's and Unix workstations) to simulate neurons with complex branching morphology,multiple channel types,and inhomogeneous channel distribution. A good example of its use in the interpretation of experimental results on failure and recovery of action potential propagation due to partial demyelination and new node formation in multiple sclerosis. We plan to refine our present computer software in order to make the nerve sell simulation task much more accessible to non-specialists in numerical methods. The neuron simulation software will be extended to incorporate several new features,the most important ones being (a),replacement of the current method of spatial discretization by specification of nerve morphology in terms of the component parts of the neuron (e.g. soma, axon, and dendritic tree), (b), addition of synaptic connections between individual neurons, and (c), use of a high level model description language to allow the user to define other physiological mechanisms and insert them at any set of locations on the neuron.