摘要
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.
The existing Parkinson’s neural network models do not include all the nuclei in the basal ganglia circuitry.Therefore,they neglect the potential effects of other nuclei when investigating the pathogenesis and searching for optimal deep brain stimulation(DBS)targets.In this paper,a complete Parkinson’s neural network model was successfully constructed based on the structure of the basal ganglia neural circuit using the Hindmarsh-Rose(HR)neuron model.Numerical simulation results under three different external stimuli showed that the Parkinson’s neural network without the substantia nigra pars compacta(SNc)nucleus exhibits high synchronization among neurons and abnormal beta oscillations,which are consistent with the accepted pathogenesis of Parkinson disease,validating the rationality of the proposed model.In addition,due to ethical and experimental difficulties,electronic neural networks are more suitable for researching Parkinson’s DBS treatment plans.Therefore,this paper constructed digital circuits of the SNc nucleus under different external stimuli on the field programmable gate array(FPGA)platform by taking the SNc nuclei as an example.The experimental results of the circuit fully demonstrated the firing behavior consistent with the numerical simulation,demonstrating the correctness of the digital circuit design.The designed digital circuit occupies less digital circuit resources and lays a foundation for the implementation of Parkinson’s neural network circuits.
作者
蔡建明
包涵
边逸轩
徐权
陈墨
包伯成
CAI JianMing;BAO Han;BIAN YiXuan;XU Quan;CHEN Mo;BAO BoCheng(School of Microelectronics and Control Engineering,Changzhou University,Changzhou 213159,China)
出处
《中国科学：技术科学》
EI
CSCD
北大核心
2024年第8期1586-1600,共15页
Scientia Sinica(Technologica)
基金
国家自然科学基金青年科学基金(批准号:62201094)
国家自然科学基金(批准号:12172066,52277001)
江苏省高等学校基础科学(自然科学)研究面上项目(编号:22KJB510001)资助。
