ArticleJournal of computational neuroscience2016
Impact of slow K(+) currents on spike generation can be described by an adaptive threshold model.
Article in Journal of computational neuroscience, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Article
- Large coefficient of variation of inter-spike intervals induced by noise current in the resonate-and-fire model neuron.Cognitive neurodynamics · 2022Article
- Kv1 channels regulate variations in spike patterning and temporal reliability in the avian cochlear nucleus angularis.Journal of neurophysiology · 2022Article
- A convolutional neural network for estimating synaptic connectivity from spike trains.Scientific reports · 2021Article
- The effect of inhibition on rate code efficiency indicators.PLoS computational biology · 2019Article
- Adaptive integrate-and-fire model reproduces the dynamics of olfactory receptor neuron responses in a moth.Journal of the Royal Society, Interface · 2019Article
- The impact of spike-frequency adaptation on balanced network dynamics.Cognitive neurodynamics · 2019Article
- The relationship between nernst equilibrium variability and the multifractality of interspike intervals in the hippocampus.Journal of computational neuroscience · 2017Article
- Modulation of neuronal dynamic range using two different adaptation mechanisms.Neural regeneration research · 2017Article
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2 authors.
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Abstract
A neuron that is stimulated by rectangular current injections initially responds with a high firing rate, followed by a decrease in the firing rate. This phenomenon is called spike-frequency adaptation and is usually mediated by slow K(+) currents, such as the M-type K(+) current (I M ) or the Ca(2+)-activated K(+) current (I AHP ). It is not clear how the detailed biophysical mechanisms regulate spike generation in a cortical neuron. In this study, we investigated the impact of slow K(+) currents on spike generation mechanism by reducing a detailed conductance-based neuron model. We showed that the detailed model can be reduced to a multi-timescale adaptive threshold model, and derived the formulae that describe the relationship between slow K(+) current parameters and reduced model parameters. Our analysis of the reduced model suggests that slow K(+) currents have a differential effect on the noise tolerance in neural coding.
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