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Space complexity analysis method orienting to brain image signals

A technology of space complexity and analysis method, applied in the field of space complexity analysis for brain image signals

Inactive Publication Date: 2018-06-15
SOUTHEAST UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0005] In view of this, the main purpose of the present invention is to provide a spatial complexity analysis method for brain image signals to overcome the shortcomings of the above-mentioned existing spatial complexity analysis methods

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  • Space complexity analysis method orienting to brain image signals
  • Space complexity analysis method orienting to brain image signals
  • Space complexity analysis method orienting to brain image signals

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Embodiment Construction

[0026] The technical solution of the present invention will be described in detail below in conjunction with the drawings and embodiments.

[0027] Such as figure 1 As shown, a method for analyzing spatial complexity of brain image signals provided by the present invention comprises the following steps:

[0028] Step S1: Acquiring brain imaging data by means of brain imaging.

[0029] In this step, any known brain imaging means can be used to acquire the nerve signal data of the brain.

[0030] Step S2: Preprocessing the brain image data.

[0031] In this step, preprocessing should be performed in combination with the characteristics of different brain imaging methods and the purpose of the researcher, so as to reduce the noise of the signal. For example, for EEG data, preprocessing generally includes: re-referencing, filtering (including high-pass filtering, low-pass filtering, band-pass filtering, and notch filtering), bad guide removal, and removal of physiological and n...

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Abstract

The invention discloses a space complexity analysis method orienting to brain image signals. The method comprises the following steps: S1, acquiring brain image data; S2, preprocessing the brain imagedata; S3, extracting signals of different brain areas based on the preprocessed brain image data; S4, estimating the time domain average regular space complexity of the signals of the different brainareas and the contribution rate of each brain area for the time domain average regular space complexity; and S5, estimating the time domain variability of the regular space complexity of the signalsof the different brain areas and the time domain variability of the contribution rate of each brain area for the regular space complexity. With the method provided by the invention, the limitation ofthe existing analysis technology for the space complexity of the brain image signals is overcome.

Description

technical field [0001] The invention relates to a space complexity analysis method for brain image signals. Background technique [0002] When the human brain is in a resting state or completing a certain task, various regions of the brain will be activated, and there will be certain functional connections or information flow between brain regions. The functional connection between various brain regions is crucial for people to complete various mental processes. At present, the international mainstream brain functional connectivity technologies are mainly: functional connectivity between brain regions, functional connectivity based on seed points, functional connectivity based on independent component analysis, and functional connectivity based on complex networks. In addition, researchers can use methods based on spatial complexity to study the overall functional connectivity level of systems composed of different brain regions. [0003] The spatial complexity of neural...

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Application Information

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IPC IPC(8): A61B5/0476A61B5/04A61B5/00
CPCA61B5/00A61B5/7235A61B5/316A61B5/369
Inventor 禹东川贾会宾
Owner SOUTHEAST UNIV