[comp.ai.neural-nets] Brain analogies

rao@enuxha.eas.asu.edu (Arun Rao) (03/03/89)

In article <32129@gt-cmmsr.GATECH.EDU>, kirlik@hms3 (Alex Kirlik) writes:
> Some researchers explain the successes of neural-net models 
			       ^^^^^^^^^
> (in mimicking human behavior) in terms of their similarity
> with the structure and mode of processing in the brain.

	Success is relative - no researcher, to my knowledge anyway,
has ever succeeded in mimicking any brain function completely. At this
stage in neural-network research, people are happy just to achieve 
something that conventional (read AI, pattern recognition) techniques
cannot. Sometimes even this advantage is questionable if you look at
some theories closely.
> 
> Now, if one wants to use such an explanation, I contend that
> the burden of proof is on that person to explain why their
> model with a small number of neural units behaves in the same
> way as the brain which uses a larger number of neurons to 

[ stuff deleted ]

> as used by the brain). Rather, my question is: How can we use the
> brain analogy to explain the successes of our models when we
> cannot specify the referential relation that holds between our
> theoretical constructs (units) and the world (the brain)?
> 
	Most current approaches attempt to use hints from neurobiology/
psychology in order to propose theories. The contention is that if
a small number of neurons can perform a very elementary function, then
perhaps a large number will be capable of more complex functions. There
have been at least some approaches which *require* the existence of large
numbers of units before emergent properties can be observed. Some graph
theoretic approaches belong to this category.

	In summary, I don't think anyone contends that their model is
in any respect a complete representation of even a part of the human 
brain even though some theories may assume a many-to-one correspondence.
All are admittedly gross simplifications, but one has to start
somewhere !

- Arun Rao
>    
> Alex Kirlik
> 
-- 
Arun Rao
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