Contributions of adaptation currents to dynamic spike threshold on slow timescales: Biophysical insights from conductance-based models

Guosheng Yi, Jiang Wang, Xile Wei, Bin Deng, Huiyan Li, Yanqiu Che

Research output: Contribution to journalArticle

Abstract

Spike-frequency adaptation (SFA) mediated by various adaptation currents, such as voltage-gated K+ current (IM), Ca2+-gated K+ current (IAHP), or Na+-activated K+ current (IKNa), exists in many types of neurons, which has been shown to effectively shape their information transmission properties on slow timescales. Here we use conductance-based models to investigate how the activation of three adaptation currents regulates the threshold voltage for action potential (AP) initiation during the course of SFA. It is observed that the spike threshold gets depolarized and the rate of membrane depolarization (dV/dt) preceding AP is reduced as adaptation currents reduce firing rate. It is indicated that the presence of inhibitory adaptation currents enables the neuron to generate a dynamic threshold inversely correlated with preceding dV/dt on slower timescales than fast dynamics of AP generation. By analyzing the interactions of ionic currents at subthreshold potentials, we find that the activation of adaptation currents increase the outward level of net membrane current prior to AP initiation, which antagonizes inward Na+ to result in a depolarized threshold and lower dV/dt from one AP to the next. Our simulations demonstrate that the threshold dynamics on slow timescales is a secondary effect caused by the activation of adaptation currents. These findings have provided a biophysical interpretation of the relationship between adaptation currents and spike threshold.

Original languageEnglish (US)
Pages (from-to)81-99
Number of pages19
JournalCommunications in Nonlinear Science and Numerical Simulation
Volume47
DOIs
StatePublished - Jun 1 2017

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Conductance
Spike
Time Scales
Chemical activation
Action Potential
Neurons
Membranes
Depolarization
Threshold voltage
Activation
Model
Neuron
Electric potential
Membrane Currents
Voltage
Membrane
Interaction

All Science Journal Classification (ASJC) codes

  • Numerical Analysis
  • Modeling and Simulation
  • Applied Mathematics

Cite this

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title = "Contributions of adaptation currents to dynamic spike threshold on slow timescales: Biophysical insights from conductance-based models",
abstract = "Spike-frequency adaptation (SFA) mediated by various adaptation currents, such as voltage-gated K+ current (IM), Ca2+-gated K+ current (IAHP), or Na+-activated K+ current (IKNa), exists in many types of neurons, which has been shown to effectively shape their information transmission properties on slow timescales. Here we use conductance-based models to investigate how the activation of three adaptation currents regulates the threshold voltage for action potential (AP) initiation during the course of SFA. It is observed that the spike threshold gets depolarized and the rate of membrane depolarization (dV/dt) preceding AP is reduced as adaptation currents reduce firing rate. It is indicated that the presence of inhibitory adaptation currents enables the neuron to generate a dynamic threshold inversely correlated with preceding dV/dt on slower timescales than fast dynamics of AP generation. By analyzing the interactions of ionic currents at subthreshold potentials, we find that the activation of adaptation currents increase the outward level of net membrane current prior to AP initiation, which antagonizes inward Na+ to result in a depolarized threshold and lower dV/dt from one AP to the next. Our simulations demonstrate that the threshold dynamics on slow timescales is a secondary effect caused by the activation of adaptation currents. These findings have provided a biophysical interpretation of the relationship between adaptation currents and spike threshold.",
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Contributions of adaptation currents to dynamic spike threshold on slow timescales : Biophysical insights from conductance-based models. / Yi, Guosheng; Wang, Jiang; Wei, Xile; Deng, Bin; Li, Huiyan; Che, Yanqiu.

In: Communications in Nonlinear Science and Numerical Simulation, Vol. 47, 01.06.2017, p. 81-99.

Research output: Contribution to journalArticle

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T2 - Biophysical insights from conductance-based models

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AU - Wang, Jiang

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AU - Deng, Bin

AU - Li, Huiyan

AU - Che, Yanqiu

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