ArticleJournal of computational neuroscience2014
Determining the contributions of divisive and subtractive feedback in the Hodgkin-Huxley model.
Article in Journal of computational neuroscience, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- A pilot study of ion current estimation by ANN from action potential waveforms.Journal of biological physics · 2022Article
- Quantitative roles of ion channel dynamics on ventricular action potential.Channels (Austin, Tex.) · 2021Article
- Mathematical model of the ventricular action potential and effects of isoproterenol-induced cardiac hypertrophy in rats.European biophysics journal : EBJ · 2020Article
- Statistical Approaches for the Analysis of Dependency Among Neurons Under Noise.Entropy (Basel, Switzerland) · 2020Article
- Phasic Firing and Coincidence Detection by Subthreshold Negative Feedback: Divisive or Subtractive or, Better, Both.Frontiers in computational neuroscience · 2017Article
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4 authors.
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Abstract
The Hodgkin-Huxley (HH) model is the basis for numerous neural models. There are two negative feedback processes in the HH model that regulate rhythmic spiking. The first is an outward current with an activation variable n that has an opposite influence to the excitatory inward current and therefore provides subtractive negative feedback. The other is the inactivation of an inward current with an inactivation variable h that reduces the amount of positive feedback and therefore provides divisive feedback. Rhythmic spiking can be obtained with either negative feedback process, so we ask what is gained by having two feedback processes. We also ask how the different negative feedback processes contribute to spiking. We show that having two negative feedback processes makes the HH model more robust to changes in applied currents and conductance densities than models that possess only one negative feedback variable. We also show that the contributions made by the subtractive and divisive feedback variables are not static, but depend on time scales and conductance values. In particular, they contribute differently to the dynamics in Type I versus Type II neurons.
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