Robust modulation of integrate-and-fire models
Abstract
By controlling the state of neuronal populations, neuromodulators ultimately affect behaviour. A key neuromodulation mechanism is the alteration of neuronal excitability via the modulation of ion channel expression. This type of neuromodulation is normally studied via conductance-based models, but those models are computationally challenging for large-scale network simulations needed in population studies. This paper studies the modulation properties of the Multi-Quadratic Integrate-and-Fire (MQIF) model, a generalisation of the classical Quadratic Integrate-and-Fire (QIF) model. The model is shown to combine the computational economy of integrate-and-fire modelling and the physiological interpretability of conductance-based modelling. It is therefore a good candidate for affordable computational studies of neuromodulation in large networks.
Cite
@article{arxiv.1709.06824,
title = {Robust modulation of integrate-and-fire models},
author = {Tomas Van Pottelbergh and Guillaume Drion and Rodolphe Sepulchre},
journal= {arXiv preprint arXiv:1709.06824},
year = {2020}
}
Comments
This is the authors' final version. The article has been accepted for publication in Neural Computation