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GIF model extensions
The content of this web page is associated with the publication:
Enhanced sensitivity to rapid input fluctuations by nonlinear threshold dynamics in neocortical pyramidal neurons
S. Mensi, O. Hagens, W. Gerstner and C. Pozzorini
PLOS Computational Biology 2016
In this paper, the GIF model introduced in our previous publication (Pozzorini et al. PLOS Comp. Biol. 2015) is extended by:
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Transforming the spike-triggered current in to a spike-triggered conductance.
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By coupling (nonlinearly and dynamically) the firing threshold to the subthreshold membrane potential.
The nonlinear coupling between membrane potential and firing threshold can be expressed either as a linear combination of rectangular basis functions (allowing for a non-parametric fit) or as a smooth linear rectifier accounting for fast Na-channel inactivation.
These models are now available in the GIFFittingToolbox originally introduced in Pozzorini et al. 2015. More instructions and concrete examples on how to fit these models to intracellular recordigns will be posted soon.
The GIFFittingToolbox now includes several variants of the Generalized Integrate-and-Fire model:
Generalized Integrate-and-Fire model introduced in Pozzorini et al. 2015. Spikes are generated stochastically according to the escape rate model; the sub-threshold dynamics of the membrane potential is described by a leaky integrator extended with a spike-triggered conductance; the firing threshold dynamics is given by a baseline and includes spike-triggered movements.
Detailed instructions on how to fit a GIF model to data can be found here. Before moving to the other models, make sure you understand how to fit this model to data.
GIF model extended with a dynamic, nonlinear coupling between membrane potential and firing threshold
iGIF_Na
gGIF