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Hyperpolarization-Activated Current Induces Period-Doubling Cascades and Chaos in a Cold Thermoreceptor Model

Overview of attention for article published in Frontiers in Computational Neuroscience, March 2017
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Title
Hyperpolarization-Activated Current Induces Period-Doubling Cascades and Chaos in a Cold Thermoreceptor Model
Published in
Frontiers in Computational Neuroscience, March 2017
DOI 10.3389/fncom.2017.00012
Pubmed ID
Authors

Kesheng Xu, Jean P. Maidana, Mauricio Caviedes, Daniel Quero, Pablo Aguirre, Patricio Orio

Abstract

In this article, we describe and analyze the chaotic behavior of a conductance-based neuronal bursting model. This is a model with a reduced number of variables, yet it retains biophysical plausibility. Inspired by the activity of cold thermoreceptors, the model contains a persistent Sodium current, a Calcium-activated Potassium current and a hyperpolarization-activated current (Ih) that drive a slow subthreshold oscillation. Driven by this oscillation, a fast subsystem (fast Sodium and Potassium currents) fires action potentials in a periodic fashion. Depending on the parameters, this model can generate a variety of firing patterns that includes bursting, regular tonic and polymodal firing. Here we show that the transitions between different firing patterns are often accompanied by a range of chaotic firing, as suggested by an irregular, non-periodic firing pattern. To confirm this, we measure the maximum Lyapunov exponent of the voltage trajectories, and the Lyapunov exponent and Lempel-Ziv's complexity of the ISI time series. The four-variable slow system (without spiking) also generates chaotic behavior, and bifurcation analysis shows that this is often originated by period doubling cascades. Either with or without spikes, chaos is no longer generated when the Ih is removed from the system. As the model is biologically plausible with biophysically meaningful parameters, we propose it as a useful tool to understand chaotic dynamics in neurons.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 5%
Unknown 18 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 32%
Student > Ph. D. Student 5 26%
Professor > Associate Professor 2 11%
Student > Master 1 5%
Other 1 5%
Other 1 5%
Unknown 3 16%
Readers by discipline Count As %
Neuroscience 5 26%
Mathematics 4 21%
Physics and Astronomy 3 16%
Engineering 2 11%
Environmental Science 1 5%
Other 0 0%
Unknown 4 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 March 2017.
All research outputs
#20,408,464
of 22,958,253 outputs
Outputs from Frontiers in Computational Neuroscience
#1,161
of 1,347 outputs
Outputs of similar age
#268,257
of 307,830 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#22
of 25 outputs
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