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Robust Modulation of Integrate-and-Fire Models.

Author information

Affiliations

  • 1. Department of Engineering, University of Cambridge, Cambridge CB2 1PZ, U.K.
      Authors
    • Van Pottelbergh T 1
    • Sepulchre R 1
    (2 authors)
  • 2. Department of Electrical Engineering and Computer Science, University of Liège, Liège 4000, Belgium
      Authors
    • Drion G 2
    (1 author)

ORCIDs linked to this article

Neural Computation, 30 Jan 2018, 30(4):987-1011
https://doi.org/10.1162/neco_a_01065 PMID: 29381445 

Abstract 

By controlling the state of neuronal populations, neuromodulators ultimately affect behavior. A key neuromodulation mechanism is the alteration of neuronal excitability via the modulation of ion channel expression. This type of neuromodulation is normally studied with conductance-based models, but those models are computationally challenging for large-scale network simulations needed in population studies. This article studies the modulation properties of the multiquadratic integrate-and-fire model, a generalization of the classical quadratic integrate-and-fire model. The model is shown to combine the computational economy of integrate-and-fire modeling and the physiological interpretability of conductance-based modeling. It is therefore a good candidate for affordable computational studies of neuromodulation in large networks.

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Read article at publisher's site: https://doi.org/10.1162/neco_a_01065

Read article for free, from open access legal sources, via Unpaywall: https://arxiv.org/pdf/1709.06824Unpaywall

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Funding 

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Engineering and Physical Sciences Research Council (1)