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Algorithmic Reconstruction of Motoneuron Morphology

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Encyclopedia of Computational Neuroscience

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Synonyms

Algorithmic generation of motoneuron morphology; Computational synthesis of motoneuron morphology; Computer generation of motoneuron morphology

Definition

Algorithmic reconstruction of neuronal morphology is the process of parameterizing neurite branching patterns, quantifying the parameters for a given population of experimentally reconstructed neurons, and then feeding the data into an algorithm which computationally generates populations of “virtual” neurons.

Detailed Description

Background

Digitization of neuronal morphology is important for computational neuroscience because neuronal morphology affects synaptic integration and firing behavior within individual neurons as well as determining potential connectivity with other neurons (Ascoli 2002). However, experimental reconstruction techniques are still largely manual or, at best, semiautomated, requiring time and skill to accurately capture neuronal morphology. As computational models of the nervous system grow in scale...

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References

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Author information

Authors and Affiliations

  1. Blue Brain Project, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Dr. Joseph Graham

Authors
  1. Dr. Joseph Graham
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Corresponding author

Correspondence to Joseph Graham .

Editor information

Editors and Affiliations

  1. Atlanta, Georgia, USA

    Dieter Jaeger

  2. Department of Biomedical Engineering, Florida International University, Miami, Florida, USA

    Ranu Jung

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© 2014 Springer Science+Business Media New York

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Graham, J. (2014). Algorithmic Reconstruction of Motoneuron Morphology. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_372-2

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  • DOI: https://doi.org/10.1007/978-1-4614-7320-6_372-2

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  • Publisher Name: Springer, New York, NY

  • Online ISBN: 978-1-4614-7320-6

  • eBook Packages: Springer Reference Biomedicine and Life SciencesReference Module Biomedical and Life Sciences

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