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Research ArticleMethods, Novel Tools and Methods

Quantifying Repetitive Transmission at Chemical Synapses: A Generative-Model Approach

Alessandro Barri, Yun Wang, David Hansel and Gianluigi Mongillo
eNeuro 28 April 2016, 3 (2) ENEURO.0113-15.2016; https://doi.org/10.1523/ENEURO.0113-15.2016
Alessandro Barri
1 Unité d'Imagerie Dynamique du Neurone, Institut Pasteur, Paris, France
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Yun Wang
2 Caritas St. Elizabeth's Center, Tufts University, Boston, MA, USA
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David Hansel
3Centre National de la Recherche Scientifique, UMR 8119, Paris, France
4 Cerebral Dynamics, Plasticity and Learning, Centre de Neurophysique, Physiologie et Pathologie, Université Descartes, Paris, France
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Gianluigi Mongillo
3Centre National de la Recherche Scientifique, UMR 8119, Paris, France
4 Cerebral Dynamics, Plasticity and Learning, Centre de Neurophysique, Physiologie et Pathologie, Université Descartes, Paris, France
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Article Information

DOI 
https://doi.org/10.1523/ENEURO.0113-15.2016
PubMed 
27200414
Published By 
Society for Neuroscience
History 
  • Received September 24, 2015
  • Revision received March 28, 2016
  • Accepted April 2, 2016
  • Published online April 28, 2016.
Copyright & Usage 
Copyright © 2016 Barri et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.

Author Information

  1. Alessandro Barri1,
  2. Yun Wang2,
  3. David Hansel3,4 and
  4. Gianluigi Mongillo3,4
  1. 1 Unité d'Imagerie Dynamique du Neurone, Institut Pasteur, Paris, France
  2. 2 Caritas St. Elizabeth's Center, Tufts University, Boston, MA, USA
  3. 3Centre National de la Recherche Scientifique, UMR 8119, Paris, France
  4. 4 Cerebral Dynamics, Plasticity and Learning, Centre de Neurophysique, Physiologie et Pathologie, Université Descartes, Paris, France
  1. Correspondence should be addressed to Gianluigi Mongillo, CNRS and Paris Descartes University, 45, rue des Saints-Pères, Paris 75006, France. E-mail: gianluigi.mongillo{at}parisdescartes.fr.
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Author contributions

  1. ↵2 Author Contributions: A.B., D.H., and G.M. designed research; A.B., D.H., and G.M. performed research; A.B., Y.W., D.H., and G.M. analyzed data; A.B., Y.W., D.H., and G.M. wrote the paper.

Disclosures

  • ↵1 The authors declare no competing financial interests.

  • ↵3 This research was conducted within the scope of the France-Israel Laboratory of Neuroscience (FILN-LEA), and supported by the France-Israel High Council for Science and Technology, the French National Research Agency (ANR) and the joint CNRS-JSPS research project.

Funding

  • French National Research Agency (ANR)

  • French National Center for Scientific Research (CNRS)

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  • You are viewing the most recent version of this article.
  • previous version (April 28, 2016).

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Quantifying Repetitive Transmission at Chemical Synapses: A Generative-Model Approach
Alessandro Barri, Yun Wang, David Hansel, Gianluigi Mongillo
eNeuro 28 April 2016, 3 (2) ENEURO.0113-15.2016; DOI: 10.1523/ENEURO.0113-15.2016

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Quantifying Repetitive Transmission at Chemical Synapses: A Generative-Model Approach
Alessandro Barri, Yun Wang, David Hansel, Gianluigi Mongillo
eNeuro 28 April 2016, 3 (2) ENEURO.0113-15.2016; DOI: 10.1523/ENEURO.0113-15.2016
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Keywords

  • expectation-maximization
  • generative modeling
  • quantal analysis
  • repetitive transmission
  • Short-term plasticity

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