Artificial immune method for constructing brain effect connection network from fMRI data

Abstract

An artificial immune method for constructing a brain effect connection network from fMRI data. On the basis of a biological immune system, an artificial immune system combined with the fMRI data is disclosed and can be used for construction of the brain effect connection network. The artificial immune method particularly comprises the following steps of: carrying out experimental design, i.e. performing functional magnetic resonance scanning by using a resting-state experiment; carrying out fMRI data acquisition, i.e. under the condition of reducing a head movement and other errors as further as possible, carrying out scanning to obtain fMRI image data; carrying out pre-processing, i.e. performing pre-processing on the data by using a statistical method, and removing errors and noise which are caused by partial outside factors; selecting a region in which the user is interested, and selecting a brain region related to the study; constructing the effect connection network by a method of optimizing Bayesian network structure learning by using the artificial immune system, and searching the effect connection network matched with an fMRI data set by means of the network structure learning; and carrying out analysis, i.e. analyzing the constructed network and mining biological characteristics exposed by a network structure.

Description

technical field [0001] The invention relates to a brain effect network construction method of fMRI functional magnetic resonance imaging data, in particular to a Bayesian network structure learning method based on an artificial immune system. Background technique [0002] Functional magnetic resonance imaging (functional magenetic resonance imaging, fMRI) is a magnetic resonance imaging-based, non-invasive, non-invasive and very effective brain functional imaging technology. Because of its reliable theoretical basis, good spatial and temporal resolution and many other characteristics, it provides favorable conditions for the experimental research of cognitive neuroscience. At the same time, it has very important clinical significance in pathological research and has a wide application prospect. and important scientific value. In particular, brain networks constructed by analyzing fMRI data can help understand the complex workings of the human brain and provide insights into...

AI Technical Summary

Problems solved by technology

This method makes full use of the advantages of the Bayesian network method, and uses the diversity generation and maintenance mechanism of the immune system to maintain the diversity of the population, and overcomes the problem that the general optimization process is prone to fall into local optimum and premature convergence. The optimal network structure finally obtained is closer to the brain effect connection network reflected by fMRI data

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