Mathematics supernormal teenager brain functional connection network analysis method based on resting state EEG signal

Abstract

The invention discloses a mathematics supernormal teenager brain functional connection network analysis method based on resting state EEG signals. The method comprises: based on a resting state EEG signal, using a phase lag algorithm based on Wilcoxon signed-rank test (PLWT) to establish a connection network, so as to measure the connection network using graph theory indexes, and depicting connection network characteristics of mathematics supernormal teenagers, including active brain regions and graph theory indexes. Compared with the prior art, the method has the following advantages: comparing the connection network characteristics of mathematics supernormal teenagers, depicted based on the resting state EEG signals, with that based on task state EEG signal analysis, obtained characteristics are simpler and more universal, and the applied PLWT method performs phase synchronization determination of EEG signals by a Wilcoxon signed-rank test framework, to explore internal connection network, prevent subjective setting of a threshold value, and reduce undetermined factors in the connection network analysis.

Description

technical field [0001] The invention belongs to the field of computational neuroscience, and in particular relates to constructing a mathematically supernormal juvenile brain functional connection network based on a resting state EEG signal under the framework of a hypothesis test, and analyzing its graph theory index. Background technique [0002] The human brain can be regarded as a complex network with a high "small world" topological property. Different functional areas interact and coordinate with each other to complete complex cognitive functions. Therefore, it is very important to study the interactions in the network of brain connections. The connection network can be divided into three types: (1) structural network (structure network), which is composed of electrical or chemical connections between neuron synapses, and this network is generally determined by physical anatomy or by nuclear magnetic imaging methods; ( 2) Functional network, which describes the stati...

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Problems solved by technology

However, they all have some shortcomings and disadvantages, such as: SC can only measure the linear coherence between signals; PLV will be seriously affected by volume conduction; although PLI can avoid volume conduction effects, it is easily affected by small disturbances; WPLI in PLI Based on the weighting operation, so as to reduce the impact of small phase differences, but it will still incorporate noise, and the large phase difference plays a dominant role

More importantly, the above-mentioned algorithms all have a common problem: a threshold must be used to determine connectivity, and the setting of this threshold is highly subjective, which increases the uncertainty of connectivity analysis

However, previous studies have been keen to analyze the characteristics of the brain functional connection network in the reasoning tasks of adolescents with superior mathematics, and the analysis of the connection network in the resting state has not been involved.

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