J. Andrew Rogers wrote:
On Jun 1, 2008, at 5:02 PM, Richard Loosemore wrote:
But.... this statement is such a blatant contradiction of all the
known facts about neurons, that I am surprised that abyone would try
to defend it. Real neurons are complicated, and their actual
functional role in the brain is still quite unknown.
So you are asserting (1) that you know very little about neurons *and*
(2) that they are fantastically complex devices at a computational model
level. Remarkable that you are simultaneously deeply knowledgeable and
ignorant at the same time. I see a lot of handwaving and cries of
"Complex! Complex!" but I don't see a lot of evidence of that fact in
the abstract computational sense. Even if one were to assert Penrosian
magic, the result is pretty obviously simple in the theoretical sense,
and we are back to algorithmic equivalence.
Can I point out that this is what "science" is all about:
(1) You discover something (neurons);
(2) You try to understand the role these neurons play in their very
complicated context (the brain);
(3) You come up with some theories (Hebb; McCulloch and Pitts, etc) but
although these theories allow you to build very simple 'artificial'
neural nets, these artificial nets are obviously not doing the same
thing that real neural systems are;
(4) You do some more work and discover that under some circumstances
even the exact placement of afferent synapses in the dendritic tree
could be playing a functional role in the performance of the neuron,
(5) ..... so you conclude that, at this stage of the game, you do not
know everything there is to know about neurons, and that as far as we
can tell the functional role played by these neurons is quite a
complicated function [BTW, I said nothing about 'complex' .... I just
used the ordinary term 'complicated'].
Meanwhile, somebody like yourself comes along and says "Idiots! Neurons
are simple! I can model them in about a hundred lines of Python!".
The problem is that the issues that other people are discussing -- the
larger context to all of this -- is going right over your head. First,
you seem to be unaware that these neuroscientists are explaining only a
small fraction of the real neural functionality. Second, you seem to be
unaware that modeling something using a "black-box" formalism is not
helpful in the larger context of understanding functionality (you could
model a car as a set of mathematically connected parameters, but that
would be virtually useless for helping you to understand what a car
actually does).
Lastly, you are simply taking no account of the hype factor that governs
reports in this area: when someone in the neuroscience area says "We
think we have a unified theory!" it means very little. Believe me, very
few people on the cognitive science side of the fence is jumping up and
down with excitement right now. They are rolling theor eyes. And with
good reason.
I recently had a conversation with a prominent cognitive scientist, and
I mentioned that Trevor Harley and I had just written a paper
demolishing some neuroscience claims. Before I could tell him more
about the paper he gave me this big, laconic grin and said "Yeah, but
come on...! Bit like shooting fish in a barrel, no?". *That* is how
exciting these neuroscience claims are to people in the cognitive
science community. It is not that the results are great, but some smart
computer scientists already got there ten or twenty years ago (as you
claim), it is that the results are pretty trivial or meaningless.
Richard Loosemore
-------------------------------------------
agi
Archives: http://www.listbox.com/member/archive/303/=now
RSS Feed: http://www.listbox.com/member/archive/rss/303/
Modify Your Subscription:
http://www.listbox.com/member/?member_id=8660244&id_secret=103754539-40ed26
Powered by Listbox: http://www.listbox.com
