蓝脑项目（和 NEURON 软件）如何运作？
此问题与 873448 相关。
来自维基百科：
蓝脑计划试图通过对哺乳动物大脑进行逆向工程直至分子水平来创造合成大脑。 [...] 使用运行 Michael Hines 的 NEURON 软件的 Blue Gene 超级计算机，模拟不仅仅包含人工神经网络，还涉及神经元的生物学真实模型。
“如果我们正确构建它，它应该会说话、具有智能并且行为方式与人类非常相似。”
我的问题是该软件内部如何工作。如果它“涉及神经元的生物现实模型”，那么它与神经网络有什么不同，为什么神经网络不能很好地模拟生物大脑，而这个项目可以？那么，NEURON软件是如何进行模拟的呢？
最后，如果这个问题不属于这里，我深表歉意（也许 BioStar StackExchance 是一个更好的提问地点）。
This question is related to 873448.
From Wikipedia:
The Blue Brain Project is an attempt to create a synthetic brain by reverse-engineering the mammalian brain down to the molecular level. [...] Using a Blue Gene supercomputer running Michael Hines's NEURON software, the simulation does not consist simply of an artificial neural network, but involves a biologically realistic model of neurons.
"If we build it correctly it should speak and have an intelligence and behave very much as a human does."
My question is how the software works internally. If it "involves a biologically realistic model of neurons", how is that different from a neural network, and why can't neural networks simulate a biological brain well while this project would be able to? And, how is NEURON software used in the simulation?
Lastly, I apologize if this question doesn't belong here (maybe the BioStar StackExchance would be a better place to ask).
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NEURON 软件通过不同离子通道对细胞内外的离子通量进行建模，从而对神经元细胞进行建模。这些运动在神经元膜的内部和外部之间产生电位差，并且这种电位的调节允许不同的神经元相互通信。存在多种神经元生物物理模型，例如 integrate-and-火灾模型或Hodgkin-Huxley模型
人工神经网络除了共享相同的名称之外，网络与生物神经网络几乎没有任何关系。它们是一种以加权方式相互连接的数学结构，允许接受一个或多个输入并产生一个或多个输出。
编辑：我必须补充一点，尽管蓝色计划是朝着建模整个大脑迈出的令人难以置信且非常令人钦佩的一步，但我们离这个目标还很远很远。所有这些都是模型，因此它们近似于生物细胞的行为，但它们绝不是完整的。此外，这些模型分析的神经元的“选择”存在很大偏差。大多数模型代表大脑的某些区域（例如皮层或海马体），其中 1）我们拥有相当多的知识，2）由协同工作的神经元细胞的组织结构构成。大脑的其他部分可能并不那么容易建模（请注意，我以开玩笑的方式使用“琐碎”，我并不是说建模皮质很容易！），但是我想这个细节有点超出了SO的范围。您也可以在 Psychology SE 上提问。
最后，为了纠正引用的说法，该项目确实对大鼠的体感皮层进行了建模，这只是整个大鼠大脑的很小一部分。
NEURON software models neuronal cells by modeling fluxes of ions inside and outside the cell through different ion channels. These movement generate a difference of electrical potential between the interior and the exterior of the neuronal membrane, and modulations of this potential allows different neurons to communicate between each other. Several biophysical models for neurons exist, such as the integrate-and-fire model or the Hodgkin-Huxley model
Artificial neural networks have pretty much nothing to do with biological neural networks, apart from sharing the same name. They're mathematical constructs that are connected with each other in a weighted manner, allowing to take one or more inputs and produce one or more outputs.
EDIT: I have to add, as much as the Blue Project is an incredible and very admirable step towards modeling an entire brain, we are far far far far away from that goal. All these are models, so they approximate the behaviour of biological cells, but they are in no way complete. Furthermore, there is a high bias in the "choice" of which neurons these models analyze. Most of the models represent certain areas of the brain (such as the cortex or the hippocampus) of which 1) we have quite a bit of knowledge and 2) are constituted by very organized structures of neuronal cells working together. Other parts of the brain may not be as trivial to model (note that I use "trivial" in a jokingly way, I'm not in any way saying that modeling the cortex is easy!), but I guess the details of this would be a bit outside the scope of SO. You can ask on the Psychology SE as well.
Finally, to correct the quoted statement, the project did model a column of the somatosensory cortex of the rat, which is only a very tiny part of an entire rat brain.