Preprint

[Bartlett Mel]

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Announcing two preprints now available in the
neuroprose archive:

1. Synaptic Integration in an Excitable Dendritic Tree
		by Bartlett W. Mel		

2. Memory Capacity of an Excitable Dendritic Tree
		by Bartlett W. Mel		


Abstracts and ftp instructions follow.  Hardcopies are not available,
unless you're desperate.

-Bartlett
 
 Division of Biology		
 Caltech 216-76
 Pasadena, CA 91125
 mel at caltech.edu	
 (818)356-3643, fax: (818)796-8876


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	SYNAPTIC INTEGRATION IN AN EXCITABLE DENDRITIC TREE

			 Bartlett W. Mel
		 Computation and Neural Systems
	       California Institute of Technology

Compartmental modeling experiments were carried out in an anatomically
characterized neocortical pyramidal cell to study the integrative
behavior of a complex dendritic tree containing active membrane
mechanisms.  Building on a hypothesis presented in (Mel 1992a), this
work provides further support for a novel principle of dendritic
information processing, that could underlie a capacity for nonlinear
pattern discrimination and/or sensory-processing within the dendritic
trees of individual nerve cells.  

It was previously demonstrated that when excitatory synaptic input to
a pyramidal cell is dominated by voltage-dependent NMDA-type channels,
the cell responds more strongly when synaptic drive is concentrated
within several dendritic regions than when it is delivered diffusely
across the dendritic arbor (Mel 1992a).  This effect, called dendritic
``cluster sensitivity'', persisted under wide ranging parameter
variations, and directly implicated the spatial ordering of afferent
synaptic connections onto the dendritic tree as an important
determinant of neuronal response selectivity.

In this work, the sensitivity of neocortical dendrites to spatially
clustered synaptic drive has been further studied with fast sodium and
slow calcium spiking mechanisms present in the dendritic membrane.
Several spatial distributions of the dendritic spiking mechanisms were
tested, with and without NMDA synapses.  Results of numerous
simulations reveal that dendritic cluster sensitivity is a highly
robust phenomenon in dendrites containing a sufficiency of excitatory
membrane mechanisms, and is only weakly dependent on their detailed
spatial distribution, peak conductances, or kinetics.  Factors that
either work against or make irrelevant the dendritic cluster
sensitivity effect include 1) very high-resistance spine necks, 2)
very large synaptic conductances, 3) very high baseline levels of
synaptic activity, or 4) large fluctuations in level of synaptic
activity on short time scales.

The functional significance of dendritic cluster-sensitivity has been
previously discussed in the context of associative learning and memory
(Mel 1992ab).  Here it is demonstrated that the dendritic tree of a
cluster-sensitive neuron implements an approximative spatial
correlation, or sum of products, operation, such as that which may
underlie nonlinear disparity tuning in binocular visual neurons.

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	   MEMORY CAPACITY OF AN EXCITABLE DENDRITIC TREE

			 Bartlett W. Mel
		 Computation and Neural Systems
	       California Institute of Technology

Previous comparmental modeling studies have shown that the dendritic
trees of neocortical pyramidal cells may be ``cluster-sensitive'',
i.e. selectively responsive to spatially clustered, rather than
diffuse, patterns of synaptic activation.  The local nonlinear
interactions among synaptic inputs in a cluster sensitive neuron are
crudely analogous to a layer of hidden units in a neural network, and
permit nonlinear pattern discriminations to be carried out within the
dendritic tree of a single cell (Mel 1992ab).  These studies have
suggested that the spatial permutation of synaptic connections onto
the dendritic tree is a crucial determinant of a cell's response
selectivity.

In this paper, the storage capacity of a single cluster sensitive
neuron is examined empirically.  As in (Mel 1992b), an abstract model
neuron, called a ``clusteron'', was used to explore biologically-
plausible Hebb-type learning rules capable of manipulating the
ordering of synaptic inputs onto cluster-senstive dendrites.
Comparisons are made between the storage capacity of a clusteron, a
simple perceptron, and a modeled pyramidal cell with either a passive
or electrically excitable dendritic tree.  Based on the empirically
demonstrated storage capacity of a single biophysically-modeled
pyramidal cell, it is estimated that a 5 x 5 mm slab of neocortex can
``memorize'' on the order of 100,000 sparse random input-output
associations.  Finally, the neurobiological relevance of
cluster-sensitive dendritic processing and learning rules is
considered.

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To get these papers by ftp:

     unix> ftp archive.cis.ohio-state.edu (or 128.146.8.52)
     Name: anonymous
     Password: neuron
     ftp> cd pub/neuroprose
     ftp> binary
     ftp> get mel.synaptic.tar.Z
     ftp> get mel.memory.ps.Z
     ftp> quit
     unix> uncompress mel*Z
     unix> tar xvf mel*tar	
     unix> lpr -s mel.synaptic.ps1 (or however you print postscript)
     unix> lpr -s mel.synaptic.ps2 
     unix> lpr -s mel.synaptic.ps3 
     unix> lpr -s mel.memory.ps 


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