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Hindmarsh-Rose neuron model with memristors

机译:Hindmarsh玫瑰神经元模型与留念

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摘要

We analyze single and coupled Hindmarsh-Rose neurons in the presence of a time varying electromagnetic field which results from the exchange of ions across the membrane. Memristors are used to model the relation between magnetic flux of the electromagnetic field and the membrane potential of interacting neurons. The bifurcation analysis of Hindmarsh-Rose neurons has been carried out by varying the modulation intensity of induced current on the membrane potential. Many important dynamical behaviors such as synchrony, desynchrony, amplitude death, anti-phase oscillations, coexistence of resting and spiking state, and near death rare spikes are observed when the neurons are coupled using electrical and chemical synapses. In all cases the transverse Lyapunov exponents are plotted to observe the point of transition from desynchrony to synchrony. The memristor based analysis on neural networks can contribute to biological system modeling and can be used as a synapse in hardware of artificial neural networks.
机译:我们在存在变化的电磁场存在下分析单次和偶联的Hindmarsh玫瑰神经元,这导致离子交换膜穿过膜。存储器用于建模电磁场磁通与相互作用神经元的膜电位之间的关系。通过改变膜电位上的诱导电流的调节强度来进行Hindmarsh玫瑰神经元的分叉分析。当神经元使用电气和化学突触耦合时,观察到许多重要的动态行为,如同步,去年性,振幅死亡,抗阶段振荡,抗阶段振荡,静息和尖峰状态的共存以及近死稀有尖峰。在所有情况下,横向Lyapunov指数被绘制以观察从Desynchrony到同步的转型点。基于Memristor对神经网络的分析可以促进生物系统建模,并且可以用作人工神经网络硬件的突触。

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