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      Optimization principles of dendritic structure

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          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.

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          Most cited references29

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          Dendritic computation.

          One of the central questions in neuroscience is how particular tasks, or computations, are implemented by neural networks to generate behavior. The prevailing view has been that information processing in neural networks results primarily from the properties of synapses and the connectivity of neurons within the network, with the intrinsic excitability of single neurons playing a lesser role. As a consequence, the contribution of single neurons to computation in the brain has long been underestimated. Here we review recent work showing that neuronal dendrites exhibit a range of linear and nonlinear mechanisms that allow them to implement elementary computations. We discuss why these dendritic properties may be essential for the computations performed by the neuron and the network and provide theoretical and experimental examples to support this view.
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            Influence of dendritic structure on firing pattern in model neocortical neurons.

            Neocortical neurons display a wide range of dendritic morphologies, ranging from compact arborizations to highly elaborate branching patterns. In vitro electrical recordings from these neurons have revealed a correspondingly diverse range of intrinsic firing patterns, including non-adapting, adapting and bursting types. This heterogeneity of electrical responsivity has generally been attributed to variability in the types and densities of ionic channels. We show here, using compartmental models of reconstructed cortical neurons, that an entire spectrum of firing patterns can be reproduced in a set of neurons that share a common distribution of ion channels and differ only in their dendritic geometry. The essential behaviour of the model depends on partial electrical coupling of fast active conductances localized to the soma and axon and slow active currents located throughout the dendrites, and can be reproduced in a two-compartment model. The results suggest a causal relationship for the observed correlations between dendritic structure and firing properties and emphasize the importance of active dendritic conductances in neuronal function.
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              Branching dendritic trees and motoneuron membrane resistivity.

              W RALL (1959)
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                Author and article information

                Journal
                Theor Biol Med Model
                Theoretical Biology & Medical Modelling
                BioMed Central (London )
                1742-4682
                2007
                8 June 2007
                : 4
                : 21
                Affiliations
                [1 ]Wolfson Institute for Biomedical Research, Department of Physiology, University College London, London, UK
                [2 ]Department of Physiology, University College London, London, UK
                [3 ]Max-Planck Institute of Neurobiology, Department of Systems and Computational Neurobiology, Martinsried, Germany
                [4 ]Bernstein Center for Computational Neuroscience, Munich, Germany
                [5 ]Interdisciplinary Center for Neural Computation, Hebrew University, Jerusalem, Israel
                [6 ]Department of Neurobiology, Hebrew University, Jerusalem, Israel
                Article
                1742-4682-4-21
                10.1186/1742-4682-4-21
                1924501
                17559645
                d741e1f1-fb58-4766-9419-b0c7ba36d966
                Copyright © 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.

                History
                : 26 March 2007
                : 8 June 2007
                Categories
                Research

                Quantitative & Systems biology
                Quantitative & Systems biology

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