T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cells

  1. Marcel Beining  Is a corresponding author
  2. Lucas Alberto Mongiat
  3. Stephan Wolfgang Schwarzacher
  4. Hermann Cuntz
  5. Peter Jedlicka
  1. Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Germany
  2. Universidad Nacional del Comahue-CONICET, Argentina
  3. Goethe University, Germany

Abstract

Compartmental models are the theoretical tool of choice for understanding single neuron computations. However, many models are incomplete, built ad hoc and require tuning for each novel condition rendering them of limited usability. Here, we present T2N, a powerful interface to control NEURON with Matlab and TREES toolbox, which supports generating models stable over a broad range of reconstructed and synthetic morphologies. We illustrate this for a novel, highly-detailed active model of dentate granule cells (GCs) replicating a wide palette of experiments from various labs. By implementing known differences in ion channel composition and morphology, our model reproduces data from mouse or rat, mature or adult-born GCs as well as pharmacological interventions and epileptic conditions. This work sets a new benchmark for detailed compartmental modeling. T2N is suitable for creating robust models useful for large-scale networks that could lead to novel predictions. We discuss possible T2N application in degeneracy studies.

Article and author information

Author details

  1. Marcel Beining

    Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt, Germany
    For correspondence
    beining@fias.uni-frankfurt.de
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6577-2648
  2. Lucas Alberto Mongiat

    Instituto de Investigación en Biodiversidad y Medioambiente, Universidad Nacional del Comahue-CONICET, San Carlos de Bariloche, Argentina
    Competing interests
    The authors declare that no competing interests exist.
  3. Stephan Wolfgang Schwarzacher

    Institute of Clinical Neuroanatomy, Goethe University, Frankfurt, Germany
    Competing interests
    The authors declare that no competing interests exist.
  4. Hermann Cuntz

    Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5445-0507
  5. Peter Jedlicka

    Institute of Clinical Neuroanatomy, Goethe University, Frankfurt, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6571-5742

Funding

Deutsche Forschungsgemeinschaft (CRC1080)

  • Stephan Wolfgang Schwarzacher

Bundesministerium für Bildung und Forschung (01GQ1406)

  • Hermann Cuntz

Alzheimer Forschung Initiative (15038)

  • Peter Jedlicka

Bundesministerium für Bildung und Forschung (01GQ1203A)

  • Peter Jedlicka

Agencia Nacional de Promoción Científica y Tecnológica (PICT2013-2056)

  • Lucas Alberto Mongiat

Deutsche Forschungsgemeinschaft (JE 528/6-1)

  • Peter Jedlicka

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2017, Beining et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Marcel Beining
  2. Lucas Alberto Mongiat
  3. Stephan Wolfgang Schwarzacher
  4. Hermann Cuntz
  5. Peter Jedlicka
(2017)
T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cells
eLife 6:e26517.
https://doi.org/10.7554/eLife.26517

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https://doi.org/10.7554/eLife.26517

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