FPGA-based experimental platform for neuron stochastic response and resonance under electrical stimulation

Abstract

The invention provides an FPGA based under-electric-stimulation neuron random response and resonance experiment platform. An FPGA development board of the experiment platform comprises an FPGA chip I, an FPGA chip II, an FPGA chip III, an FPGA chip IV, a USB interface module and an SDRAM storage module. The FPGA chip II, the FPGA chip III and the FPGA chip IV receive stimulation signals output by the FPGA chip I respectively. Digital signals generated by the FPGA chip II, the FPGA chip III and the FPGA chip IV are input in the FPGA chip I to be calculated. Signals output by the FPGA chip I are input in the USB interface module to perform data communication with an upper computer, and the calculated signals are input in the SDRAM storage module to be subjected to data storage. The experiment platform has the advantages that the platform is used as the biological neural network non-animal experiment and high-speed computation FPGA neural network experiment platform, phenomenon and physiological neuron model hardware building is achieved, and the neuron model can be consistent with a real biological neuron on the time scale.

Description

technical field [0001] The invention relates to biomedical engineering technology, in particular to an FPGA-based experimental platform for neuron random response and resonance under electrical stimulation. Background technique [0002] In the nervous system, noise acts on the action potentials of neurons. The traditional idea is that noise is unfavorable to the transmission of information between neurons. However, studies have shown that random noise of appropriate intensity can effectively improve the ability of excitable neurons to respond to and process external stimulus signals. The main reason is that noise triggers stochastic resonance in the nervous system. With the in-depth study of stochastic resonance, researchers have found that not only Gaussian noise can have a positive effect on bistable systems, but also other signals, such as chaotic signals or high-frequency periodic stimulation. The vibration resonance phenomenon can be produced by using high-frequency pe...

AI Technical Summary

Problems solved by technology

[0005] The existing technology is still in the basic stage, so there are still the following shortcomings: there is no FPGA-based dedicated neuron resonance phenomenon and electromagnetic field stimulation experimental platform with complete functions; the hardware simulation neuron model implemented by FPGA has a relatively simple structure and low precision ; The man-machine interface is not yet perfect, and real-time control operation and data analysis cannot be performed. Therefore, it is difficult to analyze the dynamic characteristics of FPGA hardware neurons.

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