Izhikevich neural network synchronous discharging simulation platform based on FPGA

Abstract

The invention provides an Izhikevich neural network synchronous discharging simulation platform based on an FPGA. The simulation platform comprises an FPGA neural network computing processor and an upper computer which are connected with each other. The FPGA neural network computing processor comprises an FPGA chip, an off-chip memorizer array and an Ethernet communication module, wherein the FPGA chip receives an upper computer control signal output by the off-chip memorizer array, and receives a presynaptic membrane potential signal output by the off-chip memorizer array. The upper computer is in communication with the FPGA chip and the off-chip memorizer array through a VB programming realization man-machine operating interface and the Ethernet communication module, and a neural network model is established on the FPGA chip through Verilog HDL language programming. The Izhikevich neural network synchronous discharging simulation platform has the advantages that the hardware modeling of the phenotype and physiological type neural network model is achieved through an animal-free experiment serving as a biological neural network on the basis of an FPGA neural network experiment platform conducting computation at a high speed, and the consistency with true biological nerve cells on the time scale can be achieved.

Description

technical field [0001] The invention relates to biomedical engineering technology, in particular to an FPGA-based Izhikevich neuron network synchronous discharge simulation platform. Background technique [0002] There are about 100 billion neurons in the brain, and each neuron communicates with other 100 billion neurons through synapses. Neurons form a variety of functionally specific neural circuits, through various neurotransmitters and their receptors. The body transmits information and produces advanced functions of the brain. The processing of neural information by the brain is completed through the cooperation of neurons in different brain regions, and synchronization, as a typical manifestation of the discharge activity of neuron clusters, is an important mechanism of neural information processing. Synchronous activity between neurons plays a key role in the transmission and processing of neural information in different brain regions, which can integrate and coordin...

AI Technical Summary

Problems solved by technology

[0005] The existing technology is still in the basic stage, so there are still the following disadvantages: there is no dedicated FPGA experiment platform for synchronous simulation of neuron networks; the hardware simulation neuron network model implemented by FPGA is small in scale, invariable in scale, and poor in network connection flexibility; The human-machine interface is not yet perfect, and real-time control operation and data analysis cannot be performed, so it is difficult to analyze the dynamic characteristics of the neural network with FPGA

Images