Slow sodium-channel inactivation underlies spike threshold variability

Harrison, Paul Michael; Wall, Mark J.; Richardson, Magnus J. E.

doi:10.1186/1471-2202-14-s1-p322

Cited by 2 publications

(4 citation statements)

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“…We begin with the general equations of an excitable neuron. Since the AP generation threshold depends on the complex interaction of different ion channels and the stimulus 22 23 24 , it is necessary to distinguish gating variables, membrane potential and external current. On the other hand, considering the important role of adaptation of the ion channels in threshold variation, we directly write the time derivative of ion channel gating variables in the the adaptation form.…”

Section: Resultsmentioning

confidence: 99%

“…The ion channel subunits with long characteristic times may induce the threshold variation related to previous spikes2345. According to ref.…”

Section: Discussionmentioning

confidence: 99%

“…Separatrix-crossing framework includes different ion channel gating variables with different characteristic times. The ion channel subunits with long characteristic times may induce the threshold variation related to previous spikes 23 45 . According to ref.…”

Section: Discussionmentioning

confidence: 99%

“…Indeed, recent experiments have shown that the threshold of cortical neurons in vivo positively correlates with the membrane potential and negatively correlates with the rate of membrane depolarization 1 2 3 . Additionally, more ion channel types may participate in determining the threshold variation 22 23 . In principle, the relationship of threshold with either the membrane potential or the rising rate is determined by the activation and inactivation of all ion channels 24 25 .…”

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confidence: 99%

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Spike-Threshold Variability Originated from Separatrix-Crossing in Neuronal Dynamics

Wang

et al. 2016

Sci Rep

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The threshold voltage for action potential generation is a key regulator of neuronal signal processing, yet the mechanism of its dynamic variation is still not well described. In this paper, we propose that threshold phenomena can be classified as parameter thresholds and state thresholds. Voltage thresholds which belong to the state threshold are determined by the ‘general separatrix’ in state space. We demonstrate that the separatrix generally exists in the state space of neuron models. The general form of separatrix was assumed as the function of both states and stimuli and the previously assumed threshold evolving equation versus time is naturally deduced from the separatrix. In terms of neuronal dynamics, the threshold voltage variation, which is affected by different stimuli, is determined by crossing the separatrix at different points in state space. We suggest that the separatrix-crossing mechanism in state space is the intrinsic dynamic mechanism for threshold voltages and post-stimulus threshold phenomena. These proposals are also systematically verified in example models, three of which have analytic separatrices and one is the classic Hodgkin-Huxley model. The separatrix-crossing framework provides an overview of the neuronal threshold and will facilitate understanding of the nature of threshold variability.

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Section: Resultsmentioning

confidence: 99%

“…The ion channel subunits with long characteristic times may induce the threshold variation related to previous spikes2345. According to ref.…”

Section: Discussionmentioning

confidence: 99%