The impact of dynamic reversal potential on the evolution of action potential attributes during spike trains

TL;DR

The study explores how changes in ion concentrations and sodium channel cooperation affect the variability of action potentials in neurons during bursts.

Contribution

The paper introduces a novel mechanism involving dynamic reversal potential and cooperative sodium channel gating to explain AP variability.

Findings

AP attributes in bursts show two patterns: first APs are consistent, and subsequent APs change monotonically.

Including ion concentration dynamics in models reproduces AP attribute variation linked to dynamic reversal potential.

Cooperative sodium gating restores first AP attributes and enhances modeled variation.

Abstract

Action potentials (AP) are the basic elements of information processing in the nervous system. Understanding AP generation mechanisms is a critical step to understand how neurons encode information. However, an individual neuron might fire APs with various shapes even in response to the same stimulus, and the mechanisms responsible for this variability remain unclear. Therefore, we analyzed four AP attributes including AP rapidity and threshold during consecutive bursts from three neuron types using intracellular electrophysiological recordings. In response to consecutive current steps, the AP attributes in evoked spike trains show two distinctive patterns across different neurons: (1) The first APs from each train always have comparable properties regardless of the stimulus strength; (2) The attributes of the subsequent APs during each pulse monotonically change during the burst, where the magnitude of AP attribute change during each pulse increases with increasing stimulation strength. Various conductance-based models were explored to determine if they replicated the observed AP bursts. The observed patterns could not be replicated using the classical HH-type models, or modified HH model with cooperative Na+ gating. However, adding ion concentration dynamics to the model reproduced the AP attribute variation, and the magnitude of change during a pulse correlated with change in dynamic reversal potential (DRP), but failed to replicate the first AP attributes pattern. Then, the role of cooperative Na+ gating on neuronal firing dynamics was investigated. Inclusion of cooperative gating restored the first APs’ attributes and enhanced the magnitude of modeled variation of some AP attributes to better agree with observed data. We conclude that changes in local ion concentrations could be responsible for the monotonic change in APs attributes during neuronal bursts, and cooperative gating of Na+ channels can enhance the effect. Thus, the two mechanisms could contribute to the observed variability in neuronal response.

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