The firing of a neuron model is mainly affected by the following factors:the magnetic field,external forcing current,time delay,etc.In this paper,a new time-delayed electromagnetic field coupled dual Hindmarsh-Rose ne...The firing of a neuron model is mainly affected by the following factors:the magnetic field,external forcing current,time delay,etc.In this paper,a new time-delayed electromagnetic field coupled dual Hindmarsh-Rose neuron network model is constructed.A magnetically controlled threshold memristor is improved to represent the self-connected and the coupled magnetic fields triggered by the dynamic change of neuronal membrane potential for the adjacent neurons.Numerical simulation confirms that the coupled magnetic field can activate resting neurons to generate rich firing patterns,such as spiking firings,bursting firings,and chaotic firings,and enable neurons to generate larger firing amplitudes.The study also found that the strength of magnetic coupling in the neural network also affects the number of peaks in the discharge of bursting firing.Based on the existing medical treatment background of mental illness,the effects of time lag in the coupling process against neuron firing are studied.The results confirm that the neurons can respond well to external stimuli and coupled magnetic field with appropriate time delay,and keep periodic firing under a wide range of external forcing current.展开更多
Objective The relationship between compressed dorsal root ganglion （DRG） neurons and firing pattern and sensitivity of neurons was studied in chronically the Hindmarsh-Rose （HR） neuronal model. Methods Spontane- o...Objective The relationship between compressed dorsal root ganglion （DRG） neurons and firing pattern and sensitivity of neurons was studied in chronically the Hindmarsh-Rose （HR） neuronal model. Methods Spontane- ous activities from single fibers of chronically compressed DRG neurons in rats were recorded, and divided into periodic and non-periodic firing patterns. The sensitivity of the two kinds of firing pattern neuron to sympathetic stimulation （SS） was compared. Result It was found that 27.3% of periodic firing neurons and 93.2% of non-periodic firing neurons responded to SS respectively （ periodic vs non-periodic, P 〈 0.01 ）. The responses to SS with different stimulation time were greater non-periodic firing neurons than periodic firing neurons （P 〈 0.01 ）. The non-periodic firing neurons obviously responded to SS. After the firing pattern of these neurons transformed to periodic firing pattern, their responses to SS disappeared or decreased obviously. The HR neuronal model exhibited a significantly greater response to perturbation in non-periodic （chaotic） firing pattern than in periodic firing pattern. Conelusion The non-periodic firing neurons with deterministic chaos are more sensitive to external stimuli than the periodic firing neurons.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.61873186)。
文摘The firing of a neuron model is mainly affected by the following factors:the magnetic field,external forcing current,time delay,etc.In this paper,a new time-delayed electromagnetic field coupled dual Hindmarsh-Rose neuron network model is constructed.A magnetically controlled threshold memristor is improved to represent the self-connected and the coupled magnetic fields triggered by the dynamic change of neuronal membrane potential for the adjacent neurons.Numerical simulation confirms that the coupled magnetic field can activate resting neurons to generate rich firing patterns,such as spiking firings,bursting firings,and chaotic firings,and enable neurons to generate larger firing amplitudes.The study also found that the strength of magnetic coupling in the neural network also affects the number of peaks in the discharge of bursting firing.Based on the existing medical treatment background of mental illness,the effects of time lag in the coupling process against neuron firing are studied.The results confirm that the neurons can respond well to external stimuli and coupled magnetic field with appropriate time delay,and keep periodic firing under a wide range of external forcing current.
基金This work was supported by the National Natural Science Foundation of China （30030040）.
文摘Objective The relationship between compressed dorsal root ganglion （DRG） neurons and firing pattern and sensitivity of neurons was studied in chronically the Hindmarsh-Rose （HR） neuronal model. Methods Spontane- ous activities from single fibers of chronically compressed DRG neurons in rats were recorded, and divided into periodic and non-periodic firing patterns. The sensitivity of the two kinds of firing pattern neuron to sympathetic stimulation （SS） was compared. Result It was found that 27.3% of periodic firing neurons and 93.2% of non-periodic firing neurons responded to SS respectively （ periodic vs non-periodic, P 〈 0.01 ）. The responses to SS with different stimulation time were greater non-periodic firing neurons than periodic firing neurons （P 〈 0.01 ）. The non-periodic firing neurons obviously responded to SS. After the firing pattern of these neurons transformed to periodic firing pattern, their responses to SS disappeared or decreased obviously. The HR neuronal model exhibited a significantly greater response to perturbation in non-periodic （chaotic） firing pattern than in periodic firing pattern. Conelusion The non-periodic firing neurons with deterministic chaos are more sensitive to external stimuli than the periodic firing neurons.
文摘已有的帕金森神经网络模型并未包含基底神经回路中的所有神经核团.因此,在研究发病机理和寻找最佳深部脑刺激(deep brain stimulation,DBS)的刺激靶点时忽略了其他核团潜在的影响.本文根据基底神经回路结构,利用Hindmarsh-Rose(HR)神经元模型成功构建了完整的帕金森神经网络模型.三种不同外加刺激下的数值仿真结果表明,缺失黑质致密部(substantia nigra pars compacta,SNc)核团的帕金森神经网络会出现神经元高度同步行为和异常β振荡活动,符合目前公认的帕金森发病机理,从而验证了所提的模型的合理性.此外,受生物伦理、实验难度的影响,电子神经网络更适合帕金森DBS治疗方案研究,因此,本文以SNc核团为例在现场可编程逻辑门阵列(field programmable gate array,FPGA)平台上构建了不同外加刺激下的SNc核团数字电路.电路实验结果能完整呈现出与数值仿真一致的放电行为,表明了数字电路设计的正确性.本文所设计的电路占用较低的数字电路资源,为帕金森神经网络电路实现做好基础准备.
