• 主题
高级搜索  >
历史搜索 清空历史
首页> 美国卫生研究院文献>other >The Volterra Functional Series is a Viable Alternative to Kinetic Models for Synaptic Modeling -Calibration and Benchmarking
【2h】

The Volterra Functional Series is a Viable Alternative to Kinetic Models for Synaptic Modeling -Calibration and Benchmarking

机译：Volterra功能系列是动力学模型的可行替代方案可用于突触建模-校准和基准测试

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务，本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文，但由于OA文献来源多样且变更频繁，仍可能出现获取不到、文献不完整或与标题不符等情况，如果获取不到我们将提供退款服务。请知悉。
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Synaptic transmission is governed by a series of complex and highly nonlinear mechanisms and pathways in which the dynamics have a profound influence on the overall signal sent to the postsynaptic cell. In simulation, these mechanisms are often represented through kinetic models governed by state variables and rate law equations. Calculations of such ordinary differential equations (ODEs) in kinetic models can be computationally intensive, and although algorithms have been optimally developed to handle ODEs efficiently, simulation of numerous, large and complex kinetic models requires a prohibitively large amount of computational power. Here we present an alternative representation of ionotropic glutamatergic receptors AMPAr and NMDAr kinetic models consisting of input-output surrogates of the receptor models which can capture the nonlinear dynamics seen in the kinetic models. We benchmark this Input-Output (IO) synapse model and compare it with kinetic receptor models to evaluate the simulation time required when using either synapse model, as well as the number of time steps each model needs for simulation. While remaining faithful to the original dynamics of the model, our results indicate that the IO synapse model requires less simulation time than the kinetic models under conditions which elicit normal physiological responses, thereby improving computational efficiency while preserving the complex non-linear dynamics of the receptors. These IO surrogates therefore constitute an appealing alternative to kinetic models in large scale networks simulations.
机译：突触传递受一系列复杂且高度非线性的机制和途径控制，其中动力学对传递至突触后细胞的整体信号产生深远影响。在仿真中，这些机制通常通过由状态变量和速率定律方程控制的动力学模型来表示。动力学模型中此类常微分方程（ODE）的计算可能会占用大量计算资源，并且尽管已针对有效地处理ODE进行了优化开发的算法，但对众多大型复杂动力学模型的仿真却需要大量的计算能力。在这里，我们介绍了离子型谷氨酸能受体AMPAr和NMDAr动力学模型的另一种表示形式，该模型由受体模型的输入-输出替代组成，可以捕获动力学模型中看到的非线性动力学。我们对该输入输出（IO）突触模型进行基准测试，并将其与动力学受体模型进行比较，以评估使用任一突触模型时所需的仿真时间，以及每个模型进行仿真所需的时间步数。在忠实于模型的原始动力学的同时，我们的结果表明，在引起正常生理反应的条件下，IO突触模型比动力学模型需要更少的仿真时间，从而提高了计算效率，同时保留了受体的复杂非线性动力学。因此，这些IO替代物构成了大规模网络仿真中动力学模型的诱人替代品。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号