Calculation method of neural synaptic plasticity based on calcium concentration

Abstract

The invention relates to a calculation method of neural synaptic plasticity based on calcium concentration, which relates to the field of brain simulation, in particular to the calculation problem ofneural synaptic plasticity of impulse neural network in brain simulation. The first is the calculation of calcium ion concentration. According to the membrane potential values of presynaptic neurons and postsynaptic neurons at the initial time t0 and the initial connecting weight w0 of synapses, the calcium ion concentrations in dendrites and spines at the next time t1 are calculated respectivelyfor the synapses that need to be calculated. Secondly, according to the calcium ion concentration in dendritic spine, the direction of weight change was obtained by comparing with the calcium ion concentration threshold Ca0s and Ca1s. According to the synaptic state tag Tag and the plasticity related protein PRP concentration, the change of synaptic weight was calculated, and the new weight at time t1 was obtained. the above procedure is repeated to calculate the strength of synaptic connections within the simulation time. The method of the invention is applied to constructing a brain-like neural network, completing the simulation of the learning and memory process required by the brain-like intelligence, realizing the universal strong artificial intelligence, and is applied to intelligentmedia, medical treatment and the like.

Description

technical field [0001] The invention relates to the field of brain simulation, in particular to the calculation problem of the neurosynaptic plasticity of the pulse neural network in the brain simulation. Background technique [0002] The brain contains hundreds of millions of neurons, which are connected to each other to form a neural network. The part of the neuron connection is called a synapse. Taking the human brain as an example, each neuron is connected to thousands to tens of thousands of neurons, so the number of connections in the brain is very large. Perceptual and cognitive processes change the strength, or weight, of synaptic connections. This phenomenon of changes in the weight of synaptic connections is called synaptic plasticity, and it is the brain's main way of learning and memory. How to accurately calculate the change process of these synaptic weights is the key to brain simulation. The calculation method of synaptic plasticity closest to the prior art...

AI Technical Summary

Problems solved by technology

The calculation method of synaptic plasticity closest to the prior art is the method described by Graupner et al. in Calcium-based plasticity model explains sensitivity of synaptic changes to spike pattern, rate, and dendritic location. The problem is that it does not consider neurons Influence of protein concentration and dendritic spine state on synaptic plasticity, leading to computational inaccuracies, etc.

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