Truncated RAP-MUSIC (TRAP-MUSIC) for MEG and EEG source localization

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http://hdl.handle.net/10138/300720

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Mäkelä , N , Stenroos , M , Sarvas , J & Ilmoniemi , R J 2018 , ' Truncated RAP-MUSIC (TRAP-MUSIC) for MEG and EEG source localization ' , NeuroImage , vol. 167 , pp. 73–83 . https://doi.org/10.1016/j.neuroimage.2017.11.013

Title: Truncated RAP-MUSIC (TRAP-MUSIC) for MEG and EEG source localization
Author: Mäkelä, Niko; Stenroos, Matti; Sarvas, Jukka; Ilmoniemi, Risto J.
Contributor: University of Helsinki, HUS Medical Imaging Center
University of Helsinki, BioMag Laboratory
Date: 2018-02-15
Language: eng
Number of pages: 11
Belongs to series: NeuroImage
ISSN: 1053-8119
URI: http://hdl.handle.net/10138/300720
Abstract: Electrically active brain regions can be located applying MUltiple SIgnal Classification (MUSIC) on magneto-or electroencephalographic (MEG; EEG) data. We introduce a new MUSIC method, called truncated recursively-applied-and-projected MUSIC (TRAP-MUSIC). It corrects a hidden deficiency of the conventional RAP-MUSIC algorithm, which prevents estimation of the true number of brain-signal sources accurately. The correction is done by applying a sequential dimension reduction to the signal-subspace projection. We show that TRAP-MUSIC significantly improves the performance of MUSIC-type localization; in particular, it successfully and robustly locates active brain regions and estimates their number. We compare TRAP-MUSIC and RAP-MUSIC in simulations with varying key parameters, e.g., signal-to-noise ratio, correlation between source time-courses, and initial estimate for the dimension of the signal space. In addition, we validate TRAP-MUSIC with measured MEG data. We suggest that with the proposed TRAP-MUSIC method, MUSIC-type localization could become more reliable and suitable for various online and offline MEG and EEG applications.
Subject: EEG
EEG/MEG DATA
Electroencephalography
HEAD
HUMAN BRAIN
Inverse methods
LOCATION
MAGNETOENCEPHALOGRAPHY
MEG
MINIMUM-VARIANCE BEAMFORMERS
MODEL
Magnetoencephalography
Multiple sources
RECONSTRUCTION
SKULL
Source localization
217 Medical engineering
3112 Neurosciences
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