What have neural networks achieved?

[Huaiyu Zhu]

As to the objective of a better understand of the brain, I'd like to draw
your attention to a result about

		The Computational Origin of Addiction.

A learning algorithm derived from purely computational considerations was
shown to require a particular mechanism reminiscent to that provided by
the neurotransmitter dopamine, including the possibility of addiction. 
I'd be especially interested in hearing responses from people familiar
with neurophysiology and the role of dopamine.  It might even be possible
to test this theory with current experimental technology.


ftp://ftp.santafe.edu/pub/zhuh/link-iconip97.ps 

	    A possible link between artificial and biological
		     neural network learning rules
			     Huaiyu Zhu

  A learning rule for stochastic neural networks is described, which
  corresponds to biological neural systems in all major aspects.
  Instead of backpropagating a vector through the synapses, only a few
  scalars are broadcast across the whole network, corresponding to the
  role played by the neurotransmitter dopamine.  In addition, the
  annealing process avoids local optima in the learning process and
  corresponds to the difference in learning between adults and
  children.  Some more detailed predictions are made for future
  comparison with neurophysiological data.

(In Proc. Intl. Conf. Neural Information Processing (ICONIP'97), 
Vol.1, pp.263-266. Dunedin, New Zealand, 28-30 Nov, 1997)

Huaiyu
-- 
Huaiyu Zhu                      Tel: 1 505 984 8800 ext 305       
Santa Fe Institute              Fax: 1 505 982 0565
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