[comp.lsi] Biological Chip Coatings

eneumann@bbn.com (Eric Neumann) (04/05/91)

In article <1991Apr2.164740.28858@fcom.cc.utah.edu> 
strohsch@mines.utah.edu (David A Strohschein) writes:
>   I am trying to find information about growing nerve cells on integrated
> circuit surfaces.  The object is to grow the nerves on the ICs while 
> retaining the normal or near normal electrical and physiological 
functions of
> the nerve tissue.  I have done some research in the library under the 
topics of
> tissue culture and biopolymers however, this seems to be a new or 
specialized
> problem and most books do not address this subject.  If there is enough 
response I will post 
> the information. Thanks in advance.

Dr. McKay at MIT in collaboration with Mitch Eggers at Lincoln Lab  have 
developed a system for growing neurons on silicon wafers containing a matrix of gold microelectrodes using poly-lysine (?) as the cellular substratum.  They're able to simultaneously record from many neurons as well as stimulate 
specific ones in order to measure the total response.

Dr. Eric Neumann
System and Technologies Division
BBN Laboratories
Cambridge, MA

rowland@ponder.csci.unt.edu (Keith Rowland) (05/18/91)

In article <1991Apr2.164740.28858@fcom.cc.utah.edu> strohsch@mines.utah.edu (David A Strohschein) writes:
>
>  I am trying to find information about growing nerve cells on integrated
>circuit surfaces.  The object is to grow the nerves on the ICs while 
>retaining the normal or near normal electrical and physiological functions of
>the nerve tissue.

   While not actually growing neurons on ICs we do grow them on glass plates
on which a grid of 64 electrodes has been photo-etched in an area of approx.
1mm^2. We have been very successful in preserving the electrical functions. 
As for the physiological, the cells form networks of synaptic connections
that respond pharmacologically in a predictable manner but we doubt that it has 
the same physiology as the tissue. I'm involved in the data aquisition and
therefore am no expert in the biology of these systems.
   Anyone interested can contact me via e-mail or by news if they think it's
of interest to all. 
__
Keith E. Rowland                rowland@cnns.unt.edu
System Manager                  Center for Network Neuroscience
University of North Texas       PO Box 5218 Denton, Texas 76203
817/565-3896,3472               "Gee, I dunno Andy. Better ask Aunt B."
-- 
Keith E. Rowland                rowland@{sonne.}cnns.unt.edu
System Manager                  Center for Network Neuroscience
University of North Texas       PO Box 5218 Denton, Texas 76203
817/565-3896,3472               "Gee, I dunno Andy. Better ask Aunt B."

arms@cs.UAlberta.CA (Bill Armstrong) (05/18/91)

rowland@ponder.csci.unt.edu (Keith Rowland) writes:

>In article <1991Apr2.164740.28858@fcom.cc.utah.edu> strohsch@mines.utah.edu (David A Strohschein) writes:
>>
>>  I am trying to find information about growing nerve cells on integrated
>>circuit surfaces.  The object is to grow the nerves on the ICs while 
>>retaining the normal or near normal electrical and physiological functions of
>>the nerve tissue.

>   While not actually growing neurons on ICs we do grow them on glass plates
>on which a grid of 64 electrodes has been photo-etched in an area of approx.
>1mm^2.
>__
>Keith E. Rowland                rowland@cnns.unt.edu

In our work on adaptive logic networks (ALN) we have come a long way
in getting them to find simple rules in boolean data.  If you could
get sequences of bits representing axonal pulses in your collection of
neurons, you could try to predict what causes what by taking a many
samples of all signals BUT x over the past t seconds, and training an
ALN to predict the current x.  I suppose you have tried this with
backpropagation networks, but we have found that ALNs are very good at
finding simple rules for generalization.  For example ALNs have
learned (a very good approximation for) the rule for a multiplexer
with 521-input signals, based on 8000 samples, an infinitesimal part
of the whole space.  So it might be worth while to try this out on a
collection of neurons.

Your discipline, about which I know virtually nothing, probably has
very sophisticated ways of studying interaction of neurons, so maybe
the suggestion is not useful.  In any case, I'd appreciate your
comments on the idea.

Bill Armstrong

P.S.  The ALNs are on menaik.cs.ualberta.ca [129.128.4.241] in
--
***************************************************
Prof. William W. Armstrong, Computing Science Dept.
University of Alberta; Edmonton, Alberta, Canada T6G 2H1
arms@cs.ualberta.ca Tel(403)492 2374 FAX 492 1071