Intelligent acupuncture neuron network experimental platform

Abstract

The invention provides an intelligent acupuncture neuron network experimental platform. The platform comprises four component parts: a neuron simulation circuit, a chemical synapse simulation circuit, a network connection matrix and a supervisory computer system, wherein the neuron simulation circuit is used for simulating the electrophysiological characteristics of four biological neurons; the chemical synapse simulation circuit is used for simulating the electrophysiological characteristics of 16 chemical synapses; the network connection matrix can realize synaptic connection of any two of the four neurons; and the supervisory computer system is used for setting parameters of a biological system and observing the experimental result. Both the number of the biological neurons simulated by the neuron simulation circuit and the chemical synapse simulation circuit and the number of the synaptic connections capable of being connected to the network connection matrix can be expanded by a multi-circuit series connection method. The platform has the advantage of realizing non-animal experiment of the biological neuron system, realizing a biologically inspired intelligent operational system, researching the conduction and the interaction rule of an acupuncture electric signal, and simplifying the research processes of the biological neuron networks with different structures and sizesby using the network connection matrix with a variable topological structure.

Description

technical field [0001] The invention relates to an acupuncture neuron network experiment platform, in particular to an intelligent acupuncture neuron network experiment platform with a variable model and network topology. Background technique [0002] The existing experimental platform is based on a specific neuron model, and the corresponding analog circuit is designed; multiple identical neuron analog circuits are connected by wires to form neuron networks with various topological structures. Such an experimental platform has the following shortcomings: [0003] 1. The experiment has poor flexibility and is not easy for experimenters to operate. Existing electronic neuron systems use resistor divider to modify the parameters of the neuron model. This method not only affects the accuracy of the parameters, but also makes the process of parameter setting very complicated, requiring a certain amount of microelectronics. The basics and corresponding equipment; and in the con...

AI Technical Summary

Problems solved by technology

[0003] 1. The experiment has poor flexibility and is not easy for experimenters to operate

Existing electronic neuron systems use resistor divider to modify the parameters of the neuron model. This method not only affects the accuracy of the parameters, but also makes the process of parameter setting very complicated, requiring a certain amount of microelectronics. The basic and corresponding equipment; and in the configuration of the network topology, the method of manual configuration is used to connect two neurons that need synaptic connection through wires. It is almost impossible to use this method to form a complex neuron network. is impossible

[0004] 2. The scalability of the system is not good

This makes it difficult to realize the commercialization of such experimental systems

[0005] 3. Lack of intelligent model management system

In the existing electronic neuron network experiment system, because many characteristics of the system are manually configured, such as the neuron model, the key parameters of the synapse model and the network structure, these characteristics are difficult to be managed by the computer, let alone through software. The configuration reproduces the experimental results, which has caused great difficulties for researchers in the later analysis and research of data and the realization of repeated experiments

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