Action potential initiation mechanisms: analysis and numerical study
Date
2022
Authors
Aldohbeyb, Ahmed A., author
Lear, Kevin L., advisor
Vigh, Jozsef, committee member
Prasad, Ashok, committee member
Venayagamoorthy, Karan, committee member
Journal Title
Journal ISSN
Volume Title
Abstract
Action potentials (AP) are the unitary elements of information processing in the nervous system. Understanding AP initiation mechanisms is a fundamental step in determining how neurons encode information. However, variation in neuronal response is a characteristic of mammalian neurons, which further complicate the analysis of neuronal firing dynamics. Several studies have associated the variation in AP onset with the type and densities of voltage-gated ion channels, diversity in synaptic inputs, neuron intrinsic properties, cooperative Na+ gating, or AP backpropagation. But the mechanisms that underlie the response variability remain unclear and subject to debate. Even though all these studies tried to answer the same question, the definition of AP onset and rapidity differs between them, highlighting the need for a more systematic and consistent method to quantify AP onset features, and hence analyzing the variation in AP onset. Two novel methods were developed to quantify AP rapidity. The proposed methods have lower relative variation, higher ability to classify neuron types, and higher sensitivity and specificity to voltage-gated Na+ channels parameters than current methods. AP rapidity was used to analyze different factors impacting the AP activation mechanism. However, the prior rapidity quantification methods are subjectively based on the researcher's judgment, which complicates the comparison between different studies. Thus, we proposed a more systematic and consistent method based on the full-width or half-width at half the rising phase peak of the membrane potential's second-time derivative (Vm). First, using an HH-type model, we showed that the peak width methods are sensitive to changes in the Na+ channel parameters and conductance and minimally impacted by changes in the K+ channel parameters compared to the phase slope, the standard quantification method. Second, we compared the peak width methods to the two prior methods, phase slope and error ratio, using recordings from cortical and hippocampal pyramidal neurons, hippocampal PVBCs, and FS cortical neurons found in online databases. The results showed that the new methods have the lowest variation between neurons within a specific type while significantly differentiating several neuron types. Together, the two studies showed that the peak width methods provide another sensitive tool to investigate the mechanisms impacting AP onset dynamics and provide a better tool to study Na+ channels kinetics and AP onset features. A conductance-based model that includes dynamics of ion concentration and cooperative Na+ channels was developed to investigate the mechanisms responsible for observed neuronal response variation. Random response variability has previously been observed in spike trains evoked from individual neurons by the same DC stimulus, but we observed systematic variation. The first APs' in a burst had attributes that were comparable regardless of the stimulus strength, while the subsequent APs' attributes monotonically change during bursts, and the magnitude of change increases with stimulus strength. These two spike train features were observed in three different neuron types (n = 51), indicating a shared mechanism is responsible for the spike train pattern. Various existing computational models fail to replicate the monotonic variation in AP attributes. We proposed incorporating ion concentration dynamics and cooperative gating to account for the missing behavior. A model with dynamic reversal potential but without cooperative Na+ channel gating reproduces the AP attribute's variation during bursts, but not the first APs' attributes. The first APs' attributes were reproduced only in the presence of a fraction of cooperative Na+ channels. Cooperative gating also enhanced the magnitude of modeled variation of some AP attributes to better match the electrophysiological recordings. Therefore, we conclude that changes in ion concentration dynamics could be responsible for the monotonic change in some AP's attributes during normal neuronal firing, and cooperative gating can enhance this effect. Thus, the two mechanisms contribute to the observed variability in neuronal response, especially the variation in AP rapidity.
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Subject
AP rapidity
hippocampal neurons
neuron classification
cortical neurons
action potential
IFWd2