info. on visual cortex models, simulations .. (summary)

Pervez Mohta pmohta at clyde.ics.uci.edu
Tue Jan 18 19:03:04 EST 1994


 Hi,

 I have had a few responses (6) to my query about visual
 cortex models. Thanks to all of you who responded. Here
 is the original query, followed by a summary of responses.

 Please note:
 Some of the responses were for summaries and those have not
 been included below.
 I have retained the 'date' and 'from' fields from the message
 headers, so someone can follow up with the poster.

 If I still get significant number of responses, I will
 consider a second summary after a while.

 -- pervez mohta
    pmohta at ics.uci.edu


------------------------ Original Query ----------------------------------

 Can anyone give me references (papers, books,etc..) on the
 following:
 
 1. explanation of the visual cortex circuitry, especially
    at the neuronal and circuit level (not chemical level).

 2. work involving development of artificial neural networks,
    or other approaches, for simulating the visual cortex
    functions, preferably for tasks involving classification
    based on visual data,etc..

 -- pervez mohta
    pmohta at ics.uci.edu

---------------------------- Response # 1 ---------------------------------

From: Geoffrey Goodhill <gjg at cns.edinburgh.ac.uk>
Date: Wed, 12 Jan 94 15:59:58 GMT

> Can anyone give me references (papers, books,etc..) on the
> following:
> 
> 1. explanation of the visual cortex circuitry, especially
>    at the neuronal and circuit level (not chemical level).

My PhD thesis was about modelling of ocular dominance column
formation: it can be obtained via anonymous ftp (see below). I have
also published the following papers related to this:

Goodhill, G.J. \& Willshaw, D.J. (1990).
Application of the elastic net algorithm to the formation of ocular
dominance stripes.
{\em Network\/}, {\bf 1}, 41-59.

Dayan, P.S. \& Goodhill, G.J. (1992)
Perturbing Hebbian rules. {\em Advances in
Neural Information Processing Systems}, {\bf 4}, 19-26, eds.
J.E. Moody, S.J. Hanson and R.P. Lippman, Morgan Kaufmann, San Mateo, CA.

Goodhill, G.J. (1993).
Topography and ocular dominance: a model exploring positive correlations.
{\em Biological Cybernetics\/}, {\bf 69}, 109-118.

Goodhill, G.J. \& Willshaw, D.J. (1994).
Elastic net model of ocular
dominance: Overall stripe pattern and monocular deprivation.
{\em Neural Computation\/}, in press.

Simmen, M., Goodhill, G.J. \& Willshaw, D.J. (1994).
Multidimensional scaling as a technique for understanding the
connectivity of the brain. {\em Nature\/}, to appear.

Regards,

Geoff Goodhill




The following technical report version of my thesis is now available
in neuroprose:

             Correlations, Competition, and Optimality: 
      Modelling the Development of Topography and Ocular Dominance

                           CSRP 226

                       Geoffrey Goodhill
            School of Cognitive and Computing Science
                      University Of Sussex

                           ABSTRACT

There is strong biological evidence that the same mechanisms underly
the formation of both topography and ocular dominance in the visual
system. However, previous computational models of visual development
do not satisfactorily address both of these phenomena
simultaneously. In this thesis we discuss in detail several
models of visual development, focussing particularly on the form
of correlations within and between eyes. 

Firstly, we analyse the "correlational" model for ocular dominance
development recently proposed in [Miller, Keller & Stryker 1989] .
This model was originally presented for the case of identical
correlations within each eye and zero correlations between the eyes.
We relax these assumptions by introducing perturbative correlations
within and between eyes, and show that (a) the system is unstable to
non-identical perturbations in each eye, and (b) the addition of small
positive correlations between the eyes, or small negative correlations
within an eye, can cause binocular solutions to be favoured over
monocular solutions.

Secondly, we extend the elastic net model of [Goodhill 1988, Goodhill
and Willshaw 1990] for the development of topography and ocular
dominance, in particular considering its behaviour in the
two-dimensional case. We give both qualitative and quantitative
comparisons with the performance of an algorithm based on the
self-organizing feature map of Kohonen, and show that in general the
elastic net performs better. In addition we show that (a) both
algorithms can reproduce the effects of monocular deprivation, and (b)
that a global orientation for ocular dominance stripes in the elastic
net case can be produced by anisotropic boundary conditions in the
cortex.

Thirdly, we introduce a new model that accounts for the development of
topography and ocular dominance when distributed patterns of activity
are presented simultaneously in both eyes, with significant
correlations both within and between eyes. We show that stripe width
in this model can be influenced by two factors: the extent of lateral
interactions in the postsynaptic sheet, and the degree to which the
two eyes are correlated. An important aspect of this model is the form
of the normalization rule to limit synaptic strengths: we analyse this
for a simple case.

The principal conclusions of this work are as follows:

1. It is possible to formulate computational models that account for
   (a) both topography and stripe formation, and (b) ocular dominance
   segregation in the presence of *positive* correlations between
   the two eyes.

2. Correlations can be used as a ``currency'' with which to compare
   locality within an eye with correspondence between eyes. This
   leads to the novel prediction that stripe width can be influenced
   by the degree of correlation between the two eyes. 


Instructions for obtaining by anonymous ftp:

% ftp cheops.cis.ohio-state.edu
Name: anonymous
Password:neuron
ftp> binary
ftp> cd pub/neuroprose
ftp> get goodhill.thesis.tar
ftp> quit
% tar -xvf goodhill.thesis.tar  (This creates a directory called thesis)
% cd thesis
% more README

WARNING: goodhill.thesis.tar is 2.4 Megabytes, and the thesis takes up
13 Megabytes if all files are uncompressed (there are only 120 pages
- the size is due to the large number of pictures). Each file within
the tar file is individually compressed, so it is not necessary to
have 13 Meg of spare space in order to print out the thesis.

The hardcopy version is also available by requesting CSRP 226 from:

Berry Harper
School of Cognitive and Computing Sciences
University of Sussex
Falmer
Brighton BN1 9QN
GREAT BRITAIN

Please enclose a cheque for either 5 pounds sterling or 10 US dollars,
made out to "University of Sussex".


Geoffrey Goodhill
University of Edinburgh
Centre for Cognitive Science
2 Buccleuch Place
Edinburgh EH8 9LW
email: gjg at cns.ed.ac.uk


---------------------------- Response # 2 ---------------------------------

Date: Wed, 12 Jan 94 08:59:24 PST
From: Joseph Devlin <jdevlin at pollux.usc.edu>

You write:

>Can anyone give me references (papers, books,etc..) on the
>following:

>2. work involving development of artificial neural networks,
>   or other approaches, for simulating the visual cortex
>   functions, preferably for tasks involving classification
>   based on visual data,etc..

Pervez,
  You might want to see Irv Biederman and John Hummel's work on
modeling object recognition via ANNs.  It's pretty state of the
art.
  Christoph von der Malsburg's work in modeling the formation of
retinotopic maps is, in my opinion, the definitive success of ANN
modeling and is clearly related to vision, as well.  His more
recent work is in human face recognition which might be more what
you're looking for.
  Hope these help.

						- Joe

*************************************************************************
Joseph Devlin, PhD Student             	  * 
Neural, Information, & Behavioral Science * email: jdevlin at pollux.usc.edu
Hedco Neuroscience Bldg.		  * 
University of Southern California  	  * "The axon doesn't think.
Los Angeles, CA 90089              	  *  It just ax."  George Bishop
*************************************************************************

   Author: vonder-Malsburg-C.  Buhmann-J.
    Title: Sensory segmentation with coupled neural oscillators.
   Source: BIOLOGICAL CYBERNETICS, vol. 67, iss. 3 (1992): 233-42.

   Author: C. von der Malsburg
    Title: Development of Ocularity Domains and Growth Behaviour
	   of Axon Terminals
   Source: Biological Cybernetics 32, 49-62 (1979)

   Author: Wang-DeLiang.;  Buhmann-Joachim.;
           von-der-Malsburg-Christoph.
    Title: Pattern segmentation in associative memory.
   Source: Neural Computation, 1990 Spr Vol 2(1) 94-106.

   Author: Hummel-J-E.  Biederman-I.
    Title: Dynamic binding in a neural network for shape recognition.
   Source: PSYCHOLOGICAL REVIEW, vol. 99, iss. 3 (1992 Jul): 480-517.

   Author: Lades, Martin;  Vorbruggen, Jan C.;  Buhmann, Joachim;  Lange,
           Jorg;  Malsburg, Christoph v.d.;  Wurtz, Rolf P.;  Konen, Wolfgang
    Title: Distortion invariant object recognition in the dynamic link
           architecture.  (Technical)
   Source: IEEE Transactions on Computers, v42, n3 (March 1993):
           p300(12). 1993


---------------------------- Response # 3 ---------------------------------

Date: Wed, 12 Jan 1994 09:33:58 -0800 (PST)
From: gpotts <gpotts at oregon.uoregon.edu>

1:

Zeki, Semi. A vision of the brain. Oxford, Blackwell Scientific, 1993.

2:
Carpenter, G.A. & Grossberg, S. (eds.). Neural networks for vision and
image processing. Cambridge, MIT Press, 1992.


---------------------------- Response # 4 ---------------------------------

Date: Wed, 12 Jan 94 12:46 PST
From: Jim Stanley <jimst at ornews.intel.com>

Yes, please post a summary.  From the '70s, I recall:
	Marr's work on neocortex and visual system
	Van der Malsberg's visual system work
	Kilmer's hippocampus work
	Grossberg's cortex work
	Freeman's olfactory bulb work

Most of these were in Biological Cybernetics.  Starting threads with
these should allow you to track the work through the '70s and '80s.

Hope this helps.

	Jim Stanley


---------------------------- Response # 5 ---------------------------------

Date: Mon, 17 Jan 94 11:22 GMT
From: Julian Budd <julianb at cogs.susx.ac.uk>

You might start with 

Peters, A. & Jones, E.G. (1984,eds). Cerebral Cortex: Volume 3
Visual Cortex. Plenum Press.

which is not as out-of-date as the year might suggest. 

Also, if you might try a literature search on Kevan A C Martin
from Oxford, whose group has been involved in much of the recent
advances. 

Hope this helps.


---------------------------- Response # 6 ---------------------------------

From: galperin at world.std.com (Geoffrey D Alperin)
Date: Mon, 17 Jan 1994 04:14:57 GMT

pmohta at clyde.ics.uci.edu (Pervez Mohta) writes:

>Can anyone give me references (papers, books,etc..) on the
>following:

>1. explanation of the visual cortex circuitry, especially
>   at the neuronal and circuit level (not chemical level).

>2. work involving development of artificial neural networks,
>   or other approaches, for simulating the visual cortex
>  ...

I can help on point 1.  The Neurobiology class I'm currently taking uses two 
books, each of which has explanations of the visual cortex circuitry:
(In addition to retina.)  
1) From Neuron to Brain, John G Nicholls, A Robert Martin, Bruce G. Wallace,
Third Edition, 1992, Sinauer Associates.
2) Neurons and Networks, John E. Dowling, 1992, The Belknap Press of 
Harvard university Press. 
Both are pretty standard Neurobiology texts.   

-Geoff Alperin

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