[MURG] - emulation difficulties

[digfarenough]

The goal is a hardware/software combination that functionally reproduces a human's mind. Since it's generally accepted that the mind is caused by the brain, we want to functionally reproduce the brain. The brain is built from a network of information processors, neurons, whose processing abilities are closely tied to its biology (things like distance of synapses from the axonal hillock, and production of proteins involved in LTP, to name two). I think, then, that it's safe to say we'll need to functionally reproduce the neurons themselves in a network, to emulate a mind.
 
Two ways of doing this come to mind. One is to make neuronal models of each cell type and use the Hodgkin-Huxley equations to calculate the neuronal dynamics. The problem here, is that the HH equations are differential equations, so that no matter how tiny a timestep you choose, eventually the errors will greatly grow and the network will fall apart. I don't know of any way of getting around this growing error in the system. This makes me believe that this method of emulation will only provide a short life-span for an uploadee.
 
Another way of doing this (which may reduce to the above case, maybe a TOE will help out here) is to simulate at a very low level (atomic, perhaps subatomic) all the goings-ons in each neuron. If you individually know the state of each voltage-dependant channel and the location of every ion, you don't need to use diff eqs to calculate them and can bypass the error. The problem here is twofold: 1. the laws of physics may not be deterministic at this level, quantum effects may come in, and 2. how can you possibly figure out all the information you'd need to simulate a neuron at this level?
 
Does anyone know of other ways emulation has been proposed? Ways that may actually work?
 -Eric


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