Anders writes, quoting Robin:
> > 3) Resolution required -- The spatial/chemical resolution of a scanning
> > technology that would be required to sufficiently reliably distinguish
> > between the types of neurons, and to distinguish which neurons connect
> > to which others via which kinds of synapses. (Assume one is repeated
> > slicing and scanning a cryogenically frozen brain.)
> We need to identify synapses, which means on the order of ~1 mu. At
> this resolution the morphological differences can probably be totally
> characterized, but we need the ability to get the receptor types on
> surfaces and possibly some chemical stuff from the inside too. I don't
> think we need much smaller resolution, since then we get down into the
> region where noise and diffusion play a significant role.
If by mu you mean microns, I think you will have to go much smaller than
that in order to accurately model neural behavior. Synapse gaps are
something like 10-20 nm, vessicles are 50-200 nm, and I think receptors
are on the order of 10-50 nm or so. You need a pretty full picture of
the spatial density of the vessicles and receptors in order to model
how the synapse will behave under depolarization.
The rest of the neural surface is important, too, in terms of how the
polarization impulses will spread around the cell. Then in order to
model longer term behavior you probably need to model the microtubule
distribution within the cells, and the rate of synthesis of replacement
neurotransmitter, which will depend on overall metabolism. An old cell
may not be able to fire at the maximum rate indefinitely (I don't know
for sure, but this seems plausible).
It's possible that you can substitute "generic" information for some
or all of these factors and still get a good model. Even if it is
wrong for individual cells maybe the brain would behave roughly the
same if all cells were like the average cell in terms of metabolism,
transport rates, density of various receptors and transmitters, etc.
But I suspect we would not get so lucky.
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