"William Morse"  wrote in message
news:c6crfg$1a1b$1{at}darwin.ediacara.org...
> Tim Tyler  wrote in
> news:c5ut04$2rpg$1{at}darwin.ediacara.org:
>
> > irr  wrote or quoted:
>
> >> While we might all agree that the primate brain is an incredibly
> >> complex organ, it's not at all agreed upon what it is we mean by
> >> this.  For example, a Kolmogorov measure fails miserably in
> >> classifying the brain as complex, after all you're really only
> >> talking about two dozen or so different recognized cell types stamped
> >> out in enormous repetition with iterated connections between them --
> >> in other words, a digital representation of the brain is incredibly
> >> compressible.
>
> > IMO - this makes no sense at all :-|
>
> > An acceptable digital version of the brain would handle the same I/O -
> > and produce similar inputs from similar outputs.  This sounds like a
> > job for a huge computer with an *extremely* lengthy description to me
> > - and of course a correspondingly enormous Kolmogorov complexity.
>
> I agree with Tim that a digital computer that mimics the brain would be
> huge by today's standards. I however also agree that this capability is
> achieved using a relatively small amount of genetic code. Part of the
> secret is that brain development relies on input from the environment - in
> other words much of the data needed to code for a brain resides outside of
> the genes. Trying to capture this complexity entirely in a computer
program
> would in fact require specifying a lot of data that the actual developing
> brain doesn't include as different cell types but gathers as input to the
> neural net.
>
> Yours,
>
> Bill Morse
>

No argument from me on Tim's I/O or your 'brain mimicking' computer.  But as
you correctly point out -- and as I had originally argued -- the
neuroanatomical regularity apparent in neural tissue, as specified in the
genetic code, ranks low in Kolmogorov complexity.  The difference that you
and Tim correctly arrive at, which is essentially that the brain is complex
not by 'total # of differentiated cell types' but rather on the network of
connections between these, is exactly my original point -- that the choice
of complexity metric as well as what you choose to measure are both of
crucial importance.  To my knowledge thus far in biology, no generalized
complexity metric -- or biological characteristic with which it is used to
measure -- has been successful in reconstructing our presupposed
anthropocentric scala naturae (i.e. that would characterize living organisms
in a hierarchy of complexity on the order of
"humans>hominids>protists>bacteria").
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