neuroConstruct: a tool for modeling networks of neurons in 3D space.

neuroConstruct: a tool for modeling networks of neurons in 3D space.
复制标题

神经结构:在3D空间中建模神经元网络的工具。

DOI:
10.1016/j.neuron.2007.03.025
复制
发表时间:
2007-04-19
期刊:
影响因子:
16.2
通讯作者:
Silver RA
Silver RA
中科院分区:
医学1区
文献类型:
--
作者:
Gleeson P;Steuber V;Silver RA

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基于电导的神经网络模型可以帮助我们理解突触和细胞机制是如何影响大脑功能的。然而,这些复杂的模型很难开发,而且大多数神经科学家都无法接触到。此外,即使是最逼真的生物网络模型也忽略了大脑的许多3D解剖特征。在这里,我们描述了一个新的软件应用程序,NeuroConstruct,它促进了3D空间中多室神经元网络的创建、可视化和分析。图形用户界面允许无需编程即可生成和修改模型。NeurConstruct内的模型基于与模拟器无关的新的NeuroML标准,允许为神经元或Genesis模拟器自动生成代码。通过复制已发布的模型来测试NeuroConstruct,并通过在两个模拟器上比较相同的模型来验证其模拟器独立性。通过将已发表的一维小脑颗粒细胞层模型扩展到3D,我们展示了如何创建更具解剖学真实性的网络模型,以及它们的特性与实验测量结果的比较。
Conductance-based neuronal network models can help us understand how synaptic and cellular mechanisms underlie brain function. However, these complex models are difficult to develop and are inaccessible to most neuroscientists. Moreover, even the most biologically realistic network models disregard many 3D anatomical features of the brain. Here, we describe a new software application, neuroConstruct, that facilitates the creation, visualization, and analysis of networks of multicompartmental neurons in 3D space. A graphical user interface allows model generation and modification without programming. Models within neuroConstruct are based on new simulator-independent NeuroML standards, allowing automatic generation of code for NEURON or GENESIS simulators. neuroConstruct was tested by reproducing published models and its simulator independence verified by comparing the same model on two simulators. We show how more anatomically realistic network models can be created and their properties compared with experimental measurements by extending a published 1D cerebellar granule cell layer model to 3D.
DOI: 10.1111/j.1469-7793.1998.845bj.x
发表时间: 1998-08-01
影响因子: 5.5
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