Electromagnetic brain mapping
Электромагнитное картирование мозга
2001-01-01
SCID: 54.1/b4n5rvns
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MEG/EEGforward modelinginverse problemphase synchrony estimationsource localization
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Abstract (AI)
There has been tremendous advances in our ability to produce images of human brain function. Applications of functional brain imaging extend from improving our understanding of the basic mechanisms of cognitive processes to better characterization of pathologies that impair normal function. Magnetoencephalography (MEG) and electroencephalography (EEG) (MEG/EEG) localize neural electrical activity using noninvasive measurements of external electromagnetic signals. Among the available functional imaging techniques, MEG and EEG uniquely have temporal resolutions below 100 ms. This temporal precision allows us to explore the timing of basic neural processes at the level of cell assemblies. MEG/EEG source localization draws on a wide range of signal processing techniques including digital filtering, three-dimensional image analysis, array signal processing, image modeling and reconstruction, and, blind source separation and phase synchrony estimation. We describe the underlying models currently used in MEG/EEG source estimation and describe the various signal processing steps required to compute these sources. In particular we describe methods for computing the forward fields for known source distributions and parametric and imaging-based approaches to the inverse problem.
Key Findings
1
MEG and EEG provide noninvasive localization of neural electrical activity with temporal resolution below 100 ms, enabling exploration of neural process timing at cell-assembly scale.
2
MEG/EEG source localization relies on a range of signal processing techniques including digital filtering, 3D image analysis, array signal processing, image modeling/reconstruction, blind source separation, and phase synchrony estimation.
3
Methods for computing forward fields for known source distributions and both parametric and imaging-based approaches to the inverse problem are presented.
4
The paper describes current models used for MEG/EEG source estimation and the sequential signal-processing steps required to compute source solutions.
Research Object
Magnetoencephalography (MEG) and electroencephalography (EEG) measurements of human brain electromagnetic activity
Research Subject
Methods and models for MEG/EEG source localization and electromagnetic brain mapping, including forward-field computation, inverse problem approaches, signal processing steps (filtering, array processing, image modeling/reconstruction, blind source separation, phase synchrony estimation)
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2001-01-01
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