networks and biology

[Rogene Eichler]

>    I agree to Dr.Kolen.  I would like the connectionists to pay attention to
> the possibility that neural network models can explain not only the
> qualitative aspects of our brain but also the "quantitative" one of it.
>
>    In fact, I and my collaborators have found that the learning pace of the
> back propagation modeland the human brain are subject to a same power law
> with  nearly equal values of the exponent.   This is reported in
> "Power law in the human memory and in the neural network model,
>  H.Cateau, T.Nakajima, H.Nunokawa and N.Fuchikami", which is
> placed in the neuroprose as a file cateau.power.tar.Z.

The results of your work sound very exciting, indeed. But it is important
not to get trapped in HUGE statements like ' neural network models can explain
not only the qualitative aspects of our brain but also the "quantitative" one
of it.'

You are basing your statement on the ability of a subset of network models
to explain a very small subset of the behaviors that are observable and
testable by somewhat similar criteria. Furthermore, it could be argued that
the criteria you are using for your comparison is qualitative in nature
because of the testing methods employed to measure human performance in
some cognitive tasks.

Your work has shown that complex network systems can demonstrate similar
emergent properties. That statement, supported by the performance measures
you cited, is very powerful. But you have substituted one black box for
another- nothing can be said quantitatively about how or where brain function
occurs.

							- Rogene