Liu Zichao, Li Yinyun
School of Systems Science, Beijing Normal University, Beijing, China.
Computational Neuroscience Unit, Okinawa Institute of Science and Technology, Okinawa, Japan.
PLoS Comput Biol. 2025 Jun 30;21(6):e1012883. doi: 10.1371/journal.pcbi.1012883. eCollection 2025 Jun.
Electrodiffusion plays a crucial role in modulating ion channel conductivity and neural firing dynamics within the nervous system. However, the relationship among ion electrodiffusion, concentration changes, as well as channel conductivity and neuronal discharge behaviors is not quite clear. In this work, we introduce a novel Gauss-Nernst-Planck (GNP) approach to investigate how electrodiffusive dynamics influence ion channel rectification and neural activity. We have analytically demonstrated how the membrane conductance changes along with voltage and ion concentrations due to the electrodiffusive dynamics, bridging the gap between the permeability-based Goldman-Hodgkin-Katz (GHK) model and conductance-based models. We characterize the rectification properties of [Formula: see text], [Formula: see text] and leaky channels by estimating their single-channel permeabilities and conductance. By integrating these rectifying channels into neurodynamic models, our GNP neurodynamic model reveals how electrodiffusive dynamics fundamentally shape neural firing by modulating membrane conductance and the interplay between passive and active ion transport-mechanisms, which exhibits difference from conventional conductance-based neurodynamic models especially when ion concentration accumulates to high levels. Furthermore, we have explored how the electrodiffusive dynamics influence the pathological neural events by modulating the stability of neurodynamic system. This study provides a fundamental mechanistic understanding of electrodiffusion regulation in neural activity and establishes a robust framework for future research in neurophysiology.
电扩散在调节神经系统中的离子通道电导率和神经放电动力学方面起着至关重要的作用。然而,离子电扩散、浓度变化以及通道电导率与神经元放电行为之间的关系尚不完全清楚。在这项工作中,我们引入了一种新颖的高斯-能斯特-普朗克(GNP)方法来研究电扩散动力学如何影响离子通道整流和神经活动。我们已经通过分析证明了由于电扩散动力学,膜电导如何随电压和离子浓度变化,弥合了基于渗透率的戈德曼-霍奇金- Katz(GHK)模型和基于电导的模型之间的差距。我们通过估计它们的单通道渗透率和电导来表征[公式:见原文]、[公式:见原文]和泄漏通道的整流特性。通过将这些整流通道整合到神经动力学模型中,我们的GNP神经动力学模型揭示了电扩散动力学如何通过调节膜电导以及被动和主动离子传输机制之间的相互作用从根本上塑造神经放电,这与传统的基于电导的神经动力学模型有所不同,尤其是当离子浓度积累到高水平时。此外,我们已经探索了电扩散动力学如何通过调节神经动力学系统的稳定性来影响病理性神经事件。这项研究为神经活动中的电扩散调节提供了基本的机制理解,并为神经生理学的未来研究建立了一个强大的框架。