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QUANTITATIVE DESCRIPTION OF DENDRITIC MORPHOLOGY:
A CASE STUDY

Robert E. Burke
aboratory of Neural Control, National Institute of Neurological Disorders and Stroke, NIH

The shapes of trees are like pornography - hard to describe but we know them when we see them.  This is also true of the complex tree-like structures, called dendrites, that form most of the surface of nerve cells that receives synaptic information.  Cable theory indicates that the processing of synaptic information delivered to neuronal dendrites is conditioned by the morphology of the dendrites, as well as the electrical properties of their surface membranes and internal cytoplasm.  Anatomical studies of neurons has provided long lists of quantitative morphological data about the diameters and lengths of the branches that make up neuronal dendrites but there have been relatively few attempts so far to find ways to encapsulate these masses of numbers.  Our work is an attempt to provide a compact description of the dendrites of cat spinal motoneurons by building a computational machine that, when provided with a few parameters, builds structures that have the same statistical properties as real dendrites.  The machine and its parameters can be viewed as encapsulating the morphology of real dendrites.  The limitations and future directions of this approach will be discussed.

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