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Research ArticleNew Research, Neuronal Excitability

Dynamic Input Conductances Shape Neuronal Spiking

Guillaume Drion, Alessio Franci, Julie Dethier and Rodolphe Sepulchre
eNeuro 18 February 2015, 2 (1) ENEURO.0031-14.2015; DOI: https://doi.org/10.1523/ENEURO.0031-14.2015
Guillaume Drion
1Systems and Modeling, Department of Electrical Engineering and Computer Science, University of Liège, Liège, B-4000, Belgium
2Laboratory of Pharmacology and GIGA Neurosciences, University of Liège, Liège, B-4000, Belgium
3Volen Center and Biology Department, Brandeis University, Waltham, Massachussetts 02454
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Alessio Franci
1Systems and Modeling, Department of Electrical Engineering and Computer Science, University of Liège, Liège, B-4000, Belgium
4Department of Engineering, University of Cambridge, Cambridge, CB2 1PZ, United Kingdom
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Julie Dethier
1Systems and Modeling, Department of Electrical Engineering and Computer Science, University of Liège, Liège, B-4000, Belgium
5Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, New Jersey 08544
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Rodolphe Sepulchre
1Systems and Modeling, Department of Electrical Engineering and Computer Science, University of Liège, Liège, B-4000, Belgium
4Department of Engineering, University of Cambridge, Cambridge, CB2 1PZ, United Kingdom
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Abstract

Assessing the role of biophysical parameter variations in neuronal activity is critical to the understanding of modulation, robustness, and homeostasis of neuronal signalling. The paper proposes that this question can be addressed through the analysis of dynamic input conductances. Those voltage-dependent curves aggregate the concomitant activity of all ion channels in distinct timescales. They are shown to shape the current−voltage dynamical relationships that determine neuronal spiking. We propose an experimental protocol to measure dynamic input conductances in neurons. In addition, we provide a computational method to extract dynamic input conductances from arbitrary conductance-based models and to analyze their sensitivity to arbitrary parameters. We illustrate the relevance of the proposed approach for modulation, compensation, and robustness studies in a published neuron model based on data of the stomatogastric ganglion of the crab Cancer borealis.

  • compensation
  • firing pattern
  • ion channels
  • neuromodulation

Footnotes

  • ↵1 Authors report no conflict of interest.

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.

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Dynamic Input Conductances Shape Neuronal Spiking
Guillaume Drion, Alessio Franci, Julie Dethier, Rodolphe Sepulchre
eNeuro 18 February 2015, 2 (1) ENEURO.0031-14.2015; DOI: 10.1523/ENEURO.0031-14.2015

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Dynamic Input Conductances Shape Neuronal Spiking
Guillaume Drion, Alessio Franci, Julie Dethier, Rodolphe Sepulchre
eNeuro 18 February 2015, 2 (1) ENEURO.0031-14.2015; DOI: 10.1523/ENEURO.0031-14.2015
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Keywords

  • compensation
  • firing pattern
  • Ion channels
  • neuromodulation

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