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多室神经元的精细结构能够同时捕捉时空特性，具有丰富的响应和内在机理。本研究基于Pinsky-Rinzel两室神经元模型，提出多室神经元通道阻塞与噪声对神经元响应状态影响的分析方法。首先，Ca2+离子浓度影响神经递质释放的概率，对多室神经元的节律性放电具有关键作用，因此特别引入Ca2+离子通道阻塞，构建带离子通道阻塞的多室神经元模型。其次推导跃迁矩阵等核心参数构建Pinsky-Rinzel神经元Conductance噪声模型，并与subunit噪声模型对比。最终，通过单参数Hopf分岔解释各个离子通道阻塞下的动力学过程；双参数分岔显示K+离子的Hopf节点随输入电流呈近似线性递增关系，而Na+离子则近似为线性下降和指数上升两阶段；通过变异系数等指标发现K+适度阻塞促进放电，Na+阻塞抑制放电，Ca2+阻塞总体上促进放电的特性。另外，在低于阈值信号刺激时，两种噪声模型均产生随机共振，Conductance模型表现出更强的编码能力。本研究揭示了离子通道阻塞与噪声在神经信号传递中的复杂机制，为研究神经信息编码提供新的视角和工具。
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关键词:
- Pinsky-Rinzel神经元 /
- 通道噪声 /
- 通道阻塞 /
- Hopf分岔分析
The fine structure of multi-compartment neurons captures both temporal and spatial characteristics, offering rich responses and intrinsic mechanisms. However, current studies on the effects of channel blocking and noise on neuronal response states are predominantly limited to single-compartment neurons. This study introduces an analytical method to explore the internal mechanisms of channel blocking and noise effects on the response states of multi-compartment neurons, using the smooth Pinsky-Rinzel two-compartment neuron model as a case study. Potassium, sodium, and calcium ion channel blocking coefficients were separately introduced to develop a smooth Pinsky-Rinzel neuron model with ion channel blocking. Methods such as single-parameter bifurcation analysis, double-parameter bifurcation analysis, coefficient of variation, and frequency characteristics analysis were employed to examine the effects of various ion channel blockings on neuronal response states. Additionally, smooth Pinsky-Rinzel neuron subunit noise models and Conductance noise models were constructed to investigate their response characteristics using interspike interval analysis and coefficient of variation indicators. Subthreshold stimulation was used to explore the presence of stochastic resonance phenomena. Single-parameter bifurcation analysis of the ion channel blocking model elucidated the dynamic processes of two torus bifurcations and limit point bifurcations in Pinsky-Rinzel neuron firing under potassium ion blocking. Double-parameter bifurcation analysis revealed a near-linear increase in the Hopf bifurcation node of potassium ions with input current, whereas sodium ions exhibited a two-stage pattern of linear decline followed by exponential rise. Analysis of average firing frequency and coefficient of variation indicated that moderate potassium channel blocking promoted firing, sodium channel blocking inhibited firing, and calcium channel blocking showed complex characteristics but primarily promoted firing. Subthreshold stimulation of the channel noise model demonstrated stochastic resonance phenomena in both models, accompanied by more intense chaotic firing, highlighting the positive role of noise in neural signal transmission. Interspike interval and coefficient of variation indicators showed consistent variation levels for both noise models, with the conductance model displaying greater sensitivity to membrane area and stronger encoding capabilities. This study analyzed the general frequency characteristics of potassium and sodium ions on a multi-compartment neuron model through ion channel blocking models, providing particular insights into the unique effects of calcium ions. Further, the study explored stochastic resonance using ion channel noise models, supporting the theory of noise-enhanced signal processing and offering new perspectives and tools for future research on complex information encoding in neural systems. By constructing ion channel blocking models, the research analyzed the effects of potassium and sodium ions on the frequency characteristics of multi-compartment neurons and revealed the special influences of calcium ions. Using ion channel noise models, the study investigated stochastic resonance, supporting the theory that noise enhances signal processing. This research offers new perspectives and tools for studying complex information encoding in neural systems.-
Keywords:
- Pinsky-Rinzel neuron /
- channel noise /
- Channel blocking /
- Hopf bifurcation analysis
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