TR available

[Bartlett Mel]

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The following TR is now available.  A postscript version can be gotten
by the usual anonymous ftp (see below).  If you can't use the
postscript version, you can get a hardcopy by sending a postcard to:

	C. Hochenedel
	Division of Biology	
	Caltech, 216-76
	Pasadena, CA 91125


	      ________________________________________



			THE SIGMA-PI COLUMN: 
	A MODEL OF ASSOCIATIVE LEARNING IN CEREBRAL NEOCORTEX


			  Bartlett W. Mel
	   Computation and Neural Systems Program, 216-76
		 California Institute of Technology
		    Pasadena, California 91125
		       mel at aurel.cns.caltech.edu



	   		     ABSTRACT

In this paper we present a model of associative learning in cerebral
neocortex.  The extrinsically-projecting pyramidal cells of layers 2,
3, and 5 of association cortex are modeled as {\sl sigma-pi} units,
where a {\sl sigma-pi} unit computes its activation level as a sum of
contributions from a set of multiplicative (or locally-thresholded)
clusters of synapses distributed throughout its dendritic tree.  The
model demonstrates how a broad class of biologically-relevant
nonlinear associative learning problems can be solved in this system
by modifying only a single layer of excitatory synapses under the
control of a Hebb-type learning rule.  The model also accounts for a
variety of features of cortical anatomy, physiology, and biophysics
whose relations to learning have remained poorly understood.  These
include, (1) three learning-related roles for the {\sc nmda} channel,
one of them new, (2) the gross asymmetry in number and patterns of
termination of excitatory vs. inhibitory synapses onto cortical
pyramidal cells, as well as the apparent lack of plasticity at
inhibitory synapses, (3) the replication of like-activated neurons
beneath a single point in cerebral cortex, and in particular the
clumping of apical dendrites of pyramidal cells on their rise to the
cortical surface, (4) the complex 3-dimensional arborizations of axons
and dendrites in layer 1, which give rise to a rich ``combinatorial''
association interface crucial to the current model, and (5) putative
rules for activity-dependent axon growth and synaptogenesis during
associative learning.

__________________________

The postscript file for this manuscript was very large,
so it was broken into three smaller files. Here is what you 
need to do to get them:

unix> ftp cheops.cis.ohio-state.edu  (or, ftp 128.146.8.62)
Name: anonymous
Password: neuron
ftp> cd pub/neuroprose
ftp> binary
ftp> get
(remote-file) mel.sigmapi1.ps.Z
(local-file) foo1.ps.Z
ftp> get
(remote-file) mel.sigmapi2.ps.Z
(local-file) foo2.ps.Z
ftp> get
(remote-file) mel.sigmapi3.ps.Z
(local-file) foo3.ps.Z
ftp> quit

unix> uncompress foo1.ps.Z foo2.ps.Z foo3.ps.Z
unix> lpr -Pxx foo1.ps foo2.ps foo3.ps

(xx is the name of your local postscript printer.)


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