Optimization principles of dendritic structure
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Optimization principles of dendritic structure Hermann Cuntz*1,2, Alexander Borst3,4 and Idan Segev5,6 Address: 1Wolfson Institute for Biomedical Research, Department of Physiology, University College London, UK, 2Department of Physiology, University College London, UK , 3Max-Planck Institute of Neurobiology, Department of Systems and Computational Neurobiology, Martinsried, Germany, 4Bernstein Center for Computational Neuroscience, Munich, Germany, 5Interdisciplinary Center for Neural Computation, Hebrew University, Jerusalem, Israel and 6Department of Neurobiology, Hebrew University, Jerusalem, Israel Email: Hermann Cuntz* - [email protected]; Alexander Borst - [email protected]; Idan Segev - [email protected] * Corresponding author
Published: 8 June 2007 Theoretical Biology and Medical Modelling 2007, 4:21
doi:10.1186/1742-4682-4-21
Received: 26 March 2007 Accepted: 8 June 2007
This article is available from: http://www.tbiomed.com/content/4/1/21 © 2007 Cuntz et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract Background: Dendrites are the most conspicuous feature of neurons. However, the principles determining their structure are poorly understood. By employing cable theory and, for the first time, graph theory, we describe dendritic anatomy solely on the basis of optimizing synaptic efficacy with minimal resources. Results: We show that dendritic branching topology can be well described by minimizing the path length from the neuron's dendritic root to each of its synaptic inputs while constraining the total length of wiring. Tapering of diameter toward the dendrite tip – a feature of many neurons – optimizes charge transfer from all dendritic synapses to the dendritic root while housekeeping the amount of dendrite volume. As an example, we show how dendrites of fly neurons can be closely reconstructed based on these two principles alone.
Background The anatomy of the dendritic tree is one of the major determinants of synaptic integration [1-6] and the corresponding neural firing behaviour [7,8]. Dendrites come in various shapes and sizes which are thought to reflect their involvement in different computational tasks. However, so far no theory exists that explains how the particular structure of a given dendrite is connected to their particular function. Because dendrites are the main receptive region of neurons, one common requirement for all dendrites is that they need to connect with often wide-spread input sources such as elements which are topographically arranged in sensory maps [9]. This implies that the distance of different synaptic inputs to the output site at the dendritic root may vary dramatically from one synapse to the other. As a result, the impact of different synapses on the neu
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