基于HH模型的神经元网络的数值模拟与FPGA实现

目的提出了一种数值模拟结合硬件实现生物神经元网络的方法。方法运用Simulink与Dsp builder软件分别对HH模型神经元组成的神经元链网络、神经元环网络进行建模仿真,进而运用FPGA硬件实现生物神经元网络。结果通过对比,两种软件的仿真结果相同,验证了建模的一致性;再现了神经元链网络的神经元动作电位传导特性,神经元环网络的同步放电特性。FPGA硬件结果与对应的软件仿真结果相同,验证了硬件结果的正确性。结论运用FPGA实现具有生物特性的神经元网络是可行的。

神经元网络的FPGA硬件仿真方法

提出了一种利用FPGA对生物神经元网络进行硬件仿真的方法。该方法充分考虑了多进程流水线模型中各神经元状态输出的时序问题,设计了节点选择器完成对流水线数据通路输出数据的保存和选择功能,实现了多状态耦合情况下精确的仿真方法。最后,利用该方法对Morris-Lecar神经元网络模型进行了FPGA硬件仿真,再现了Morris-Lecar神经元网络的非线性动力学特性。

Phenomenological Simulation Study of Neuronal Activity Synchronization in 110 Elements Network

The phenomenon of activity synchronization in biological neural network is considered. Simulation of neurons dynamics in the 6-layer neural network with 110 elements in different regimes： regular spikes, chaotic spikes, regular and chaotic bursting, etc was performed. Izhykevich＇s phenomenological model that displays different types of activity inherent for real biological neurons was used for simulation. Space-time diagram for the entire network and raster plots for the whole structure and for each layer separately were built for visual inspection of neural network activity synchronization. Synchronization coefficients based on cross-correlation times of action potentials for all neurons pairs were calculated for the whole neural system and for each layer separately.