neuronalAPTrain

<p>Voltage data in mV simulated with Hodgkin Huxley model (parameters: C=1, 
	gNa=232, gK=45, gL=0.215, vK=-12, vNa=115, vL=10.6, bar(alphaN)=0.95, 
	bar(betaN)=1.3, bar(alphaM)=1, bar(betaM)=1.15, bar(alphaH)=1, 
	bar(betaH)=1) and applied current of 4.5 microA 1 millisecond. The 
	simulation has been done with a modified NeuroDynex Python module.</p>

datasets

Provides a collection of functions to fit and explore single, multi-component and restricted Frequency Modulated Moebius (FMM) models. 'FMM' is a nonlinear parametric regression model capable of fitting non-sinusoidal shapes in rhythmic patterns. Details about the mathematical formulation of 'FMM' models can be found in Rueda et al. (2019) <doi:10.1038/s41598-019-54569-1>.

Itziar Fernandez

Rhythmic Patterns Modeling by FMM Models

Yolanda Larriba

Christian Canedo

Alejandro Rodriguez-Collado

Adrian Lamela

Cristina Rueda

neuronalAPTrain function

Format

Neuronal AP Train Data simulated with Hodgkin-Huxley model — neuronalAPTrain

Neuronal AP Train Data simulated with Hodgkin-Huxley model

neuronalAPTrain: Neuronal AP Train Data simulated with Hodgkin-Huxley model

Description

Usage

Arguments

Format

References

Examples