Optimal control method of integral distribution neuron model

Inactive Publication Date: 2016-11-23
JIANGNAN UNIV
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Problems solved by technology

However, there is usually a large variability in the number of action potential firings as an indicator. In the past decade, it has been considered that neural firing time encodes sensory stimuli has received more and more attention.

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  • Optimal control method of integral distribution neuron model
  • Optimal control method of integral distribution neuron model
  • Optimal control method of integral distribution neuron model

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Embodiment

[0027] Example: Consider an integral firing neuron model: In the formula, the time constant is τ=5, the input impedance is R=1, and the membrane potential threshold is V th =-50, the resting potential is V r =-55, the leakage conductance equilibrium potential is E L =-65, the range of input stimulation current I(t) is [5, 20]. The neuron model was discretized using the Euler method, and the iteration step size was dt=0.01.

[0028] The working process of the inventive method is as figure 1 As shown, the specific implementation method can be divided into the following steps:

[0029] (1) Set the expected release time t * =2, so as to determine the size of the control sequence solution space dimension D=200, the search population size M=10, and take the hybridization probability p c =0.95, mutation probability p v =0.1, randomly generate M initial individuals, determine the evolution algebra variable k=1, and the maximum evolution algebra K max =15

[0030] (2) Generat...

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Abstract

The invention discloses an optimal control method for an integral firing neuron model, which utilizes the advantages of the breadth of the group search and the depth of the local search in the Memetic algorithm, and uses the potential firing time error of the integral firing neuron model as the evaluation function of the optimization algorithm , the diversity of particles is increased through the crossover and mutation among individuals, and the optimal control sequence of the integral firing neuron model is determined by minimizing the evaluation function, so as to achieve the control purpose of completing the firing of neurons at the desired time.

Description

technical field [0001] The invention relates to the fields of neuroscience and intelligent optimization, in particular to an optimal control method of an integral distribution neuron model. Background technique [0002] Spike discharge plays an important role in the transmission of information in the nervous system. The firing sequence of neurons not only contains the communication information between neurons, but also reflects the structure of the nervous system and the state of neurons. Therefore, it is of great significance to perform sufficient signal analysis on this sequence. Oscillatory activity is ubiquitous in the nervous system, and its synchronized behavior has become the focus of attention in neuroinformatics research. Some neurological diseases, such as Parkinson's disease, are caused by the abnormal synchronous activity of neurons. An effective treatment for Parkinson's disease, deep brain stimulation, essentially applies electrical stimulation controls to n...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/02
Inventor 楼旭阳
Owner JIANGNAN UNIV
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