Path: utzoo!attcan!utgpu!jarvis.csri.toronto.edu!cs.utexas.edu!samsung!zaphod.mps.ohio-state.edu!sunybcs!boulder!bill
From: bill@boulder.Colorado.EDU
Newsgroups: comp.ai.neural-nets
Subject: Re: Contrast sensitivity of spatiotemporal models models
Keywords: spatiotemporal filtering, motion detection
Message-ID: <14700@boulder.Colorado.EDU>
Date: 8 Dec 89 16:20:22 GMT
References: <8977@discus.technion.ac.il>
Sender: news@boulder.Colorado.EDU
Reply-To: bill@synapse.Colorado.EDU ()
Organization: University of Colorado, Boulder
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>  Almost all suggested motion detectors based on spatiotemporal energy
>  measurements are sensitive to the contrast of the stimulus, so that
>  they do not encode velocity information *directly*.  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!
>
>  Dario Ringach, Technion, Israel Institute of Technology,
>  Dept. of Electrical Engineering, Box 52, 32000 Haifa, Israel
>

  But division IS a biologically plausible operation -- in fact it's
actually more plausible than simple subtraction.  The most common form
of inhibition in the brain (GABA acting to open chloride channels)
performs an operation more like a division than a subtraction (though
it's really a sort of combination of the two).  Neurophysiologists often
refer to this as "shunting inhibition".

				  Bill Skaggs