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Coupled neuron group-based electroencephalogram activity simulation method and system

A technology of brain electrical activity and simulation method, applied in the field of image processing, can solve problems such as blank, and achieve the effect of high temporal resolution

Pending Publication Date: 2022-05-24
SUN YAT SEN UNIV
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  • Claims
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Problems solved by technology

[0004] At present, in SEEG-based radiofrequency thermocoagulation ablation, the relevant research is still blank by constructing a coupled neuron group model to simulate EEG activity and provide reference for doctors to adjust surgical plans

Method used

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  • Coupled neuron group-based electroencephalogram activity simulation method and system
  • Coupled neuron group-based electroencephalogram activity simulation method and system
  • Coupled neuron group-based electroencephalogram activity simulation method and system

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Embodiment

[0056] as Figure 1 As shown, the present embodiment provides a computationally active simulation method based on a coupled neuron population, comprising the following steps:

[0057] S1: EEG pretreatment;

[0058] Including: fragment capture of the signal, semaphore removal, and sample rate adjustment of the data;

[0059] In the present embodiment, the use of MATLAB software to intercept the EEG signal from background activity gradually into a high-frequency low-amplitude and high-amplitude oscillation data fragments, remove the electrode channel with more defects, adjust the data sampling rate, to facilitate data processing.

[0060] as Figure 2 As shown, the EDFbrowser is used to view the EEG signal gradually changing from background activity to high frequency low amplitude and high amplitude oscillation, end time point, and to find out the electrode channel with more defects;

[0061] In the present embodiment, the EEG signal is acquired using a Nicoli recording system, in ord...

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Abstract

The invention discloses an electroencephalogram activity simulation method and system based on a coupled neuron group. The method comprises the following steps that electroencephalogram signals are preprocessed; calculating Pearson's correlation coefficients among the channel signals to represent synchronous connection degrees among the channel signals, and forming a matrix by the calculated Pearson's correlation coefficients; constructing a coupled neuron group model, and mutually connecting excitability, slow-speed inhibition and fast-speed inhibition intermediate neuron sub-clusters with different parameters to form the neuron group model; by removing different neuron groups to simulate results of necrosis of different regions of the brain and comparing electroencephalogram signals output by the remaining neuron groups and high-frequency energy value changes of all channels, the influence degree of necrosis of different regions of the brain on high-frequency electroencephalogram activity is judged, and therefore the region with the maximum influence on the high-frequency electroencephalogram activity is determined. According to the invention, more stereoscopic and deeper electrophysiological information of the brain can be explored, and the time resolution is higher.

Description

Technical field [0001] The present invention relates to the field of image processing technology, specifically to a brain electrical activity simulation method and system based on a coupled neuron population. Background [0002] Currently, there are two main types of modeling methods used to study the electrical behavior of neuronal populations and the relationship between this electrical behavior and the observed EEG signals. One is based on networks, networks are composed of a large number of base cells, such models mainly describe the behavior of individual neurons at the microscopic level, but do not well describe the overall performance of complex electrical behavior of the brain, such models are representative of Hodgkin-Huxley model, Chay model and so on. The other type is the modeling method of lumpparameter, represented by the neuronal swarm model, which does not need to model each cell microscopically, avoids the complex connections and excessively high dimensions in th...

Claims

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Application Information

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IPC IPC(8): A61B5/37A61B5/372A61B5/388A61B5/00
CPCA61B5/37A61B5/372A61B5/388A61B5/7203A61B5/7235A61B5/7264
Inventor 罗洁陆奕伶
Owner SUN YAT SEN UNIV
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