Neural computing ideas and biological terms

[Rogene Eichler]

> Technically, I agree that a rather large schism exists between the
> unknowns of neurophysiology and the creative endeavors of neural
> computing.  However, I disagree with the contention that "leaning
> on the brain for moral support" is necessarily bad.  I have been applying
> neural computational models to analyze clinical data, and have found it
> at times difficult to communicate the significance of these models to my
> frequently non-mathematically oriented colleagues.  Often, I have resorted
> to explanations that are couched in biological terms rather than mathematical
> ones, with the opinion that it is better to communicate something rather
> than nothing at all.  
> 
> Craig Niederberger

I would have to agree with Craig that it is necessary to frame one's model
in biological terms when speaking to biologists. (Most cringe at the sight
of a mathematical equation.) It is difficult to keep an audience's attention
if you are speaking in a foreign tongue. It is your gain and their loss, to
speak both languages. 

However, I grow tired of defending the validity of models to biologists
who do not seem satisfied with any model that does not capture every last
nuiance of complexity or that does not explain every last experimental
finding. Modeling the brain will provide valuable insights into how we
process information and how we can exploit those rules for artificial 
systems. But they do not need to duplicate every last brain dynamic to
be useful or valid. And when modelers continue to make the claim 'just
like the brain' for the sake of convincing you of the validity of the 
model, they are reinforcing the claim that the brain is the ONLY measure.

It seems time for network modelers to develop a new set of measures, or 
perhaps some confidence in the significance of stand-alone models. That
is my interpretation of what "leaning on the brain for moral support"
is really about.


							- Rogene