Encephalic region causal connection detection method combining functional magnetic resonance imaging (FMRI) and magnetoencephalography (MEG)

A brain area, causal technology, applied in the field of image processing, can solve problems such as low spatial resolution and difficulty in accurately locating intracranial signal sources.

Inactive Publication Date: 2012-06-13
INST OF AUTOMATION CHINESE ACAD OF SCI
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However, due to the difficulty of accurately locating the source o

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  • Encephalic region causal connection detection method combining functional magnetic resonance imaging (FMRI) and magnetoencephalography (MEG)
  • Encephalic region causal connection detection method combining functional magnetic resonance imaging (FMRI) and magnetoencephalography (MEG)
  • Encephalic region causal connection detection method combining functional magnetic resonance imaging (FMRI) and magnetoencephalography (MEG)

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[0015] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0016] The present invention mainly considers utilizing the advantages of high spatial resolution of functional magnetic resonance imaging (FMRI) technology to locate the position information of key neurons on the FMRI image of the brain, and then obtain the high-resolution time series of the above-mentioned neurons with MEG technology, so as On the premise that the spatiotemporal two-dimensional information of brain signal activity may not be lost, the Granger causal analysis method is used to accurately detect the strength and direction of causal connections in brain regions.

[0017] figure 1 It is a specific embodiment of the method for detecting the strength and direction of the causal connection of brain regions inv...

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Abstract

The invention relates to an encephalic region causal connection detection method combining functional magnetic resonance imaging (FMRI) and magnetoencephalography (MEG), which comprises the following steps that: firstly, a coordinate of an active region is extracted from a FMRI image after the data preprocessing; secondly, an encephalic region time sequence of a corresponding position region is extracted from an MEG data after being preprocessed on the basis of the extracted FMRI active region coordinate; and thirdly, the causal connection strength and direction between every two adjacent encephalic regions are calculated according to the extracted MEG encephalic region time sequence, and an oriented network image is used for displaying a remarkable connection. The method is a valid encephalic region causal connection detection method combining two imaging modes such as FMRI and MEG, so the encephalic region causal connection can be more complete and more accurate to detect compared to the detection method by only utilizing the FMRI image.

Description

technical field [0001] The invention belongs to the field of image processing, in particular to a method for detecting causal connection of brain regions using brain functional imaging technology, in particular to a method for combining functional magnetic resonance imaging (FMRI) and magnetoencephalography (magneto encephalography, MEG) A method for the detection of district causal connectivity strength and direction. Background technique [0002] With the advancement of science and technology, non-invasive brain functional imaging technology is changing with each passing day, providing a broad stage for us to use a variety of imaging technologies for brain cognition and research. A single imaging modality, because the imaging mechanism determines that each imaging technique has corresponding advantages and disadvantages, so there is no single imaging method suitable for all experimental research or clinical applications. At present, Functional Magnetic Resonance Imaging (...

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Application Information

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IPC IPC(8): G06T7/00G06T5/00
Inventor 田捷白丽君尤优博
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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