Relationship Between Uncertainty and Emergence (neuroscience)?

Not to my knowledge, but I'm not a computer scientist. The massively parallel architecture of the brain is not well modeled by the Turing-Von Newman computer model. However, at least according to the the current paradigm, brain function is describable in terms of classical physics, but the level of complexity means that classical linear mathematics doesn't work very well. Also the connections between specific psychological factors and specific physiologic factors remains largely unknown. However, studies with functional MRIs (fMRIs) have made considerable progress in correlating mental states with brain locations.

- What do you mean by classical linear mathematics?

- What about the research on neural networks? My friend showed me an article where a clam's nervous system was completely described anatomically then modeled with a computer program. Interestingly, as I recall, the program sometimes reached what he called equilibrium states. But... if one thins of a nerve as a simple switch, then the brain no matter how complex is in theory modelable with a computer program, that is if no other effects make it into a quantum machine or some other machine that has not bee discovered yet.

The whole brain is not the sum of it's parts (emergence). Classical linear mathematics = sum of its parts.

http://en.wikipedia.org/wiki/Nonlinear_system



That claim just isn't true. We are a very far away from modelling the brain because of the many boundary conditions needed that are unknown (see link above).

Instead of referring me to a link why not explain to me why it isn't true.

I know what a non-linear system is but just can't imagine how this has to do with summing parts. Oh well. I will do some reading rather than clogging this thread with naive questions.
Thanks.