Path: utzoo!attcan!utgpu!jarvis.csri.toronto.edu!mailrus!wuarchive!usc!ucsd!sdcc6!ns299ad
From: ns299ad@sdcc6.ucsd.edu (Pablo R Alvarez)
Newsgroups: comp.ai.neural-nets
Subject: Re: Contrast sensitivity of spatiotemporal models models
Keywords: division, biological
Message-ID: <5696@sdcc6.ucsd.edu>
Date: 10 Dec 89 08:14:46 GMT
References: <8977@discus.technion.ac.il>
Reply-To: palvarez@ucsd.edu
Followup-To: comp.ai.neural-nets
Organization: University of California, San Diego
Lines: 24

In article <8977@discus.technion.ac.il> dario%techunix.bitnet@jade.berkeley.edu (Dario Ringach) writes:
>Assuming that
>division is NOT a biological plausible operation, how can this problem
>be solved by means of a simple, biological plausible, neural network?
>Gradient methods suffer form the same problem in that division is needed
>to get rid of contrast dependency...  Thanks in advance for any help!

	In fact, depending upon the type of division you are talking
about, division IS a biologically plausible operation. Consider the
following: an inhibitory neuron receives inputs from n input cells
and fires in proportion to the strength of that input. This
inhibitory cell I contacts a neuron A. The output of A will be great
when the input to I is small, and vice-versa: this system performs a
division operation.
	Note: in fact, you'd need a lot of inhibitory interneurons
to really do this job right, and it isn't, of course, an exact
division. However, it could very well do the job. There are similar
circuits in the brain, and it has been hypothesized that this might
be their function (McNaughton and Morris, Trends in Neuroscience,
1987 or 88, I can't remember right now).



Pablo Alvarez  (palvarez@ucsd.edu)