Scholarlink

<p>In this study, we formulate fractional and random extensions of the coupled Konno–Oono system for the dynamics of the neuron circuit. The fractional framework, based on the truncated <i>M</i>-fractional derivative, accounts for memory effects and long-range temporal correlations associated with synaptic plasticity. In contrast, the stochastic component captures synaptic transmission variability arising from ion-channel fluctuations and random neurotransmitter release. Using the Extended Hyperbolic Function Method, various exact soliton solutions are obtained in both the fractional and stochastic models. The obtained results explain the propagation of a localized, stable waveform in neural media under the combined effects of memory and noise. Graphical analyses are presented to illustrate the impact of different fractional orders and noise intensities on the system’s dynamical behavior. The proposed formulation offers a unified analytic framework for the investigation of nonlinear propagation of the synapse waves in the complex environment of the neurons.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Modeling synaptic dynamics in neurons via soliton solutions of fractional and stochastic coupled Konno–Oono systems

  • 期刊论文

  • 发表日期：

    2026年4月6日

查看全文
  • Musarat Bibi,
  • Salah Mahmoud Boulaaras,
  • Muhammad Shoaib Saleem

摘要

In this study, we formulate fractional and random extensions of the coupled Konno–Oono system for the dynamics of the neuron circuit. The fractional framework, based on the truncated M-fractional derivative, accounts for memory effects and long-range temporal correlations associated with synaptic plasticity. In contrast, the stochastic component captures synaptic transmission variability arising from ion-channel fluctuations and random neurotransmitter release. Using the Extended Hyperbolic Function Method, various exact soliton solutions are obtained in both the fractional and stochastic models. The obtained results explain the propagation of a localized, stable waveform in neural media under the combined effects of memory and noise. Graphical analyses are presented to illustrate the impact of different fractional orders and noise intensities on the system’s dynamical behavior. The proposed formulation offers a unified analytic framework for the investigation of nonlinear propagation of the synapse waves in the complex environment of the neurons.