Neural computing ideas and biological terms

[john kolen]

Rogene Eichler writes
  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. 

This is especially true if it is NOT the case that the details of brain
function are the roots of brain behavior.  These minute details may be
washed out by dynamical principles which have their own behavioral
"chemistry".  For a mathematical example, look at the universality of
symbol dynamics in unimodal iterated mapping (that's just a single bump,
like the logistic function).  As long as the mappings meet some fairly
general qualifications, the iterated systems based on those mappings share
the qualitative behavior, namely the bifurcation structure, regardless of
the quantitative differences between the individual mappings.

John Kolen