question: job of a neuron
I did not mean to imply that we must factor in all these variables before we
can study neural transmission. That clearly is not possible by humans, now
or in the future. My suspicion is we will require some form of AI for that
task. I don't expect anything in my lifetime! My point was to try and
demonstrate that any model of neuronal function must be able to account for
all these differing signal types and metabolic contexts.
Thanks for the evolution lesson. Reading today a basic neuro primer (layman,
reads journal articles while reading primers) the author stated that in
humans interneurons occur in very high numbers relative to other animals. I
believe Matt that you have done research into GABA(still are?) and wonder if
you can provide any insight into the idea of this high density of
interneurons. If true, why, what is so special about human brains that we
would require so many interneurons?
No, I cannot make any sense of inhibition being first. What a mystery ... .
Matt Jones <jonesmat at physiology.wisc.edu> wrote in message
news:b86268d4.0109071100.274b3ebb at posting.google.com...
> Indeed. The "earliest" ligand-gated ion channel may be an ancestor of
> the modern glycine receptor, an inhibitory synaptic chloride channel.
> The nicotinic acetylcholine, 5HT-3 and GABA receptors appear to be its
> distant progeny. So if anything, inhibitory processes may have been
> around -longer- than excitatory processes (let me know if anyone makes
> sense of -that-).
> I also agree with John H.'s statements. But we brain scientists are
> only human. It's asking a lot to try and take -everything- that
> happens in the brain into account all at once. Mostly we proceed by
> breaking off a little chunk and trying to understand that. Then later,
> we might worry about how it fits back into the whole.
> On the other hand, the obvious solution is to think of all brain
> function as one big huge wavelet...if we could just compute its
> coefficients accurately, then we'd know the secrets of the universe.
> P.S.: Yes, I believe in wavelets. They're filtering kernels developed
> by Ingrid Daubechies, Stephane Mallat and others, and are pretty damn
> useful mathematical tools. I've even used them in some signal
> processing chores. But I can't for the life of me figure out what Ron
> has in mind when he uses that term.