Extension of NEURON simulator for simulation of reaction-diffusion in neurons

模拟生物工程技术在医学神经科学中的发展受到限制， 计算神经科学的重点是人类的更高的能力，如玩的能力， 象棋或围棋。这导致了这样一种观点，即最好通过求助于大脑来了解大脑。 计算机科学的概念：人工神经网络，信息论，贝叶斯推理， 模式识别等。这些工具是否足以理解人类 新皮质功能，它们显然不足以理解神经系统 在神经和精神病理学中观察到的功能障碍。脑部疾病，就像其他疾病一样 器官系统，是生物组织的疾病，最终必须考虑能量学， 氧合，血液和脑压，以及化学反应和毒素的扩散， 大药厂这种全器官模拟将需要与其他模拟器的连接。通过这样 链接，以及通过内部扩展，我们一直在扩展广泛使用的神经元 模拟器处理神经组织中的反应扩散，以便更好地了解大脑 信号传导、神经变性毒性级联和药物作用。在当前的融资期内，我们 将通过4个目标进一步增强NEURON的NRxD模块：1.改进突触建模技术 通过将突触前体积、间隙和突触后体积一起考虑来处理离子型 突触、代谢型突触、缝隙连接和复杂组合突触;沿着 再摄取、扩散、电扩散、神经递质、第二信使和逆行 神经递质的协调作用。2.允许更快速和更广泛地探索 参数空间，通过提高仿真速度，并允许充分的状态变量保存， 改进的模拟初始化和从高性能计算故障中恢复。3. 开发基于Python和基于套接字的应用程序编程接口（API）， 与其他模拟器的连接，包括用于电扩散和用于各种类型的随机 仿真4.继续软件包的传播和教育，以获得更多的计算和 实验NRxD用户。我们将继续提供每年两次的教程，并赞助 在计算神经科学和其他会议上的额外研讨会。我们将在线整合 提供程序员参考和生物学参考的教程和文档 在线手册。我们将开发一套与这些相关的视频教程， 连接在一起，形成一个在线课程。总的来说，我们希望我们的新模拟 神经技术将越来越多地用于研究用途和未来用途， 个性化医疗的临床应用。

Development of simulation bioengineering techniques in medical neuroscience has been limited due to computational neuroscience's focus on the higher capacities of humans, such as the ability to play chess or go. That has led to the notion that the brain can best be understood by recourse to the concepts of computer science: artificial neural networks, information theory, Bayesian inference, pattern recognition, etc. Whether or not these tools are sufficient for understanding human neocortical function, they are clearly not sufficient for understanding the nervous system dysfunction seen in neurological and psychiatric pathology. Brain disease, like diseases of other organ systems, is disease of biological tissue, and must eventually consider energetics and oxygenation, blood and brain pressures, as well as chemical reactions and diffusion of toxins and pharmaceuticals. Such full-organ simulation will require linkages to other simulators. Through such linkages, as well as through internal extensions, we have been extending the widely-used NEURON simulator to handle reaction-diffusion in neural tissue in order to better understand brain signaling, neurodegenerative toxic cascades, and drug effects. For the current funding period we will further augment NEURON's NRxD module through 4 Aims: 1. Improve synaptic modeling techniques by considering presynaptic volume, cleft and postsynaptic volume together to handle ionotropic synapses, metabotropic synapses, gap junctions and complex combination synapses; along with reuptake, diffusion, electrodiffusion, neurotransmitters, second messengers and retrograde neurotransmitters in a coordinated way. 2. Allow more rapid and more extensive exploration of parameter space by improving simulation speed and by allowing full state variable saving for improved simulation initialization and recovery from high-performance computing failures. 3. Develop both Python-based and socket-based application programming interfaces (APIs) for easier linkage with other simulators, including for electrodiffusion and for various types of stochastic simulation. 4. Continue package dissemination and education in order to get more computational and experimental NRxD users. We will continue to offer twice-yearly tutorials, and to sponsor additional workshops at Computational Neuroscience and at other meetings. We will integrate online tutorials with the documentation to provide both Programmer's Reference and Biological Reference online manuals. We will develop a set of video tutorials associated with these that will eventually be linked together to make an online course. Overall, we expect that our novel simulation neurotechnology will be of increasing use and utilization both for research use, and for future clinical adoption in personalized medicine.