How does the Blue Brain Project (and NEURON software) work?

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 apolo开发者_运维问答gize if this question doesn't belong here (maybe the BioStar StackExchance would be a better place to ask).

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. Maybe when the cognitive science proposal will be operative you could pose the question there!

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.