From newshub.ccs.yorku.ca!torn!utcsri!rutgers!jvnc.net!darwin.sura.net!dtix!mimsy!ingber Thu Jul  9 16:20:07 EDT 1992
Article 6388 of comp.ai.philosophy:
Path: newshub.ccs.yorku.ca!torn!utcsri!rutgers!jvnc.net!darwin.sura.net!dtix!mimsy!ingber
>From: ingber@umiacs.umd.edu (Lester Ingber)
Newsgroups: comp.ai.philosophy
Subject: Re: Generalized Distributed Memory
Message-ID: <57982@mimsy.umd.edu>
Date: 29 Jun 92 16:17:26 GMT
Sender: news@mimsy.umd.edu
Organization: UMIACS, University of Maryland, College Park, MD 20742
Lines: 100

Back in 1983/4 Hank Stapp called me to discuss the holograph theory of
brain function.  After two 3/4-hour phone calls, he agreed that the
linearity problem made that approach seriously deficient, and he
favored my nonlinear statistical approach.  He published this shortly
thereafter in a series of papers dedicated to Eugene Wigner, I believe
in Foundations of Physics.

Quite a few papers later, I believe that the nonlinear statistical
approach had indeed shown that it can quantitatively as well as
qualitatively well describe large-scale neocortical interactions.
A recent paper is:
%A L. Ingber
%T Statistical mechanics of neocortical interactions:
A scaling paradigm applied to electroencephalography
%J Phys. Rev. A
%S 6
%V 44
%P 4017-4060
%D 1991
An electronic copy can be accesed via anonymous ftp following
directions given below.

}From: long@next1.acme.ucf.edu (Richard Long)
}Newsgroups: comp.ai.philosophy
}Subject: Re: Generalized Distributed Memory
}Date: 29 Jun 92 14:11:54 GMT
}Organization: University of Central Florida
}
}In article <650@trwacs.fp.trw.com> erwin@trwacs.fp.trw.com (Harry Erwin)  
}writes:
}> Initial draft, distributed for comment.
}(plausible holographic memory model for the cerebellum deleted)
}
}Your interpretation of cerebellar structure as an interference hologram is  
}interesting to me, if only because the proposed mechanism can be used for  
}other purposes.  However, holographic models in general suffer from a  
}severe conceptual limitation; namely, THEY ARE LINEAR MODELS.  In other  
}words, the information "stored" in the hologram is unaltered (or perhaps  
}degraded).  The original signal can indeed be reconstructed, more or less,  
}but for what purpose?  This kind of memory is more like that of a  
}computer's, in that information is stored and retrieved AS IS.  How is the  
}cerebellum to know WHICH signal to reconstruct, or use such a signal once  
}it is reconstructed?  
}
}If we view the brain generally, and the cerebellum in particular, as a  
}nonlinear dynamical system, we have the properties of distributed storage  
}and robustness that you desire, with information processing to boot.  I  
}don't think that we want our model's of memory to be bit-for-bit replay's  
}of the incoming sensory information; rather, we want them to be abstracted  
}and compacted representations with which we can reconstruct the signal  
}rather than re-present it.  This is rather like saying that, if we are  
}given the first thousand digits of Pi, what we want in our memory model is  
}not a system for regurgitating those same thousand digits, but a SIMPLE  
}(or simpler) algorithm for producing them all (or in the case of memory,  
}the interesting ones ;^) ), plus a few more.  The algorithm captures the  
}"essence" of Pi in a way that the thousand digits does not.
}
}However, I do think that the inhibitory reconstructive processes which you  
}use in your holographic model can also be useful in a nonlinear dynamical  
}systems version.  BTW, I am currently reading Pribram's book.  His (and  
}colleagues) derivation of a "neural wave equation" is particularly  
}interesting.


              Getting (P)Reprints via Anonymous Ftp

     Please  note  that  some of my (p)reprints can be downloaded
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know and I will be glad to prepare a uuencoded copy to  email  to
you.   Sorry,  but I cannot take on the task of mailing out hard-
copies.

     Just follow these procedures on your local machine:
local% ftp ftp.umiacs.umd.edu
[local% ftp 128.8.120.23]
Name (ftp.umiacs.umd.edu:yourloginname): anonymous
Password (ftp.umiacs.umd.edu:anonymous): [type in yourloginname]
ftp> cd pub/ingber
ftp> binary
ftp> get README.file
ftp> get file.ps.Z
ftp> quit
local% uncompress file.ps.Z
local% lpr [-P..] file.ps [to your PostScript laserprinter]

     With a uuencoded copy, first save to  mailfile.   Strip  out
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Applying
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will leave file.ps.Z.  Then, proceed as above.

  * * * * * * * * * * * * * * * * * * * * * * * * * *
  *                                                 *
  *               Prof. Lester Ingber               *
  *           ____________________________          *
  *                                                 *
  *  P.O. Box 857            [10ATT]0-700-L-INGBER  *
  *  McLean, VA 22101        ingber@umiacs.umd.edu  *
  * * * * * * * * * * * * * * * * * * * * * * * * * *


