human vs machine
Ferber at zoology.uni-frankfurt.de
Fri Aug 11 03:23:42 EST 1995
jkinner at omni.voicenet.com () wrote:
two postings deleted
>This is an interesting question. I think that, in theory, few people
>disagree that it would be possible to model the neurochemical system
>(in the worst case) that a brain uses to go about its business. This is
>NOT to say that we have the capabilities for this scale of modelling
>available at this time. Instead, I would suggest that some day such
>a model might be plausible.
If you really want to build up a model of the human (or any other) brain,
you must provide information about the physiology. As a result of the
complex anatomy of neurones the processing of incoming information
(postsynaptic potentials) is related to the location of the synapse on the
neuron, and the "timing" of the various incoming signals. In insects for
example different parts of the same neurone can process information
independently from each another. Thus each neurone is a really complex
thing and the principles of information processing within this neuron are
not fully understood.
After the definition of each neurone you might be able to assemble them to
your model if you can figure out how the individual neurones are
connected. In my eyes the connections are the problem. As I pointed out in
my previous posting there are 1.000.000.000.000 (10 exp 12) neurones in
the human brain. Each of them receives input from about 1000 other
neurones and synapses on another 1000 neurones. I see no experimental way
to decribe these connections and you need this information for the model.
Really good neurobiologists may be able to record three or four neurones
simultaneously with intracellular electrodes. (Intracellular recording is
necessary for the evaluation of the strength of the connection). How long
would it take to figure out all the connections experimentally? Let's say
you need one minute for each connection what is a unrealistic short period
you have to work nearly 2.000.000.0000 or 20000 millions of years. A
really long time I think.
Recruiting more neuroscientists will shorten this time considerably, but
which organization will fund a million of scientists for 20000 years :-).
>On the other hand, most people seem to forget that digital computers
>are a vastly different medium than wetware. Digital computers just
>aren't good at analyzing and simulating the analog signals involved
>in psychophysiology. Plenty of people may argue that "neurons only
>give off spikes, which can be represented digitally." That's all
>well and good, but what about the other factors? What about cell
>physiology and neuromodulators and hormones that affect the spike
>rate? How are we to measure these parameters in a digital world?
>I would answer that we shouldn't. If machines will think, it will be
>it their own unique way.
I agree, but first we must know what exactly thinking is.
>There is no way to sequence the DNA of a
>computer, so why should we assume that they will think the same way
>that we do? Hell, they can even do MATH better than we can. :)
Better? I think faster is the better description. I'm not familiar with
the literature but are there mathematical laws which were discovered by
>And remember, a good algorithm is worth an infinite amount of space.
How complex is the thinking algorhythm? Less complex than our brain?
>Can anybody remember all the whole numbers? Doubtful. But I'm sure
>most of you know the tried-and-true algorithm x_n+1 = x_n + 1.
>Some problems may not be reducible in this nice way, but who knows
>(jkinner at omni.voicenet.com)
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