chaos and neural information processing

[merrill%bucasb.bu.edu@bu-it.BU.EDU]

   From: john moody <moody-john at YALE.ARPA>
   Date: Wed, 1 Jun 88 13:49:35 EDT

   It is hard for me to imagine how chaotic behavior could be compu-
   tationally useful.

Freeman and Skarda, in a recent article in Behavioral and Brain
Science [1], argue that chaos is a essential element in their model of
olfactory function in the rat.

   For example, it has already been suggested that certain patholog-
   ical phenomina such as epileptic seizures, migraine headaches, and
   visual hallucinations are the result of instabilities in oth-
   erwise stable networks. These instabilities are probably caused by
   changes in the balances of neurotransmitters and neuromodulators.
   Jack Cowan (University of Chicago Mathematics Department) and
   collaborators have developed some very impressive mathematical
   theories to explain such phenomina.

Other researchers have argued that the exact opposite is the case:
that, for instance, the breakdown of chaos is characteristic of Sudden
Heart Failure;  the heart seems to collapse from a normally chaotic
beat into a phase-locked regime.  Similarly, researchers have argued
that the appearance of a domain of apparent periodicity mildly
*predicts* the onset of epileptic seizure.  (If anyone wants a
reference, I'll look it up in my files; I've just moved, and they're a
little chaotic right now.)

As a purely philosophical point, I can imagine a reason for chaos to be
an essential aspect of brain function.  By its very nature, a chaotic
system is capable of changing states at any time with only a slight
kick.  That could allow a neural network to make a decision at any
time without needing an external reset signal, such as most abstract
neural networks require.

[1] Freeman, W. and S. Scarda, "How brains make chaos in order to make
sense of the world", Brain and Behavioral Science, November, '87.