Interpretation of the MEG-MUSIC scan in biomagnetic source localization

Conference · Wed Sep 01 00:00:00 EDT 1993

OSTI ID:10191934

Mosher, J C; Lewis, P S ^[1]; Leahy, R M ^[2]

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1. Los Alamos National Lab., NM (United States)
2. University of Southern California, Los Angeles, CA (United States). Signal and Image Processing Inst.

MEG-Music is a new approach to MEG source localization. MEG-Music is based on a spatio-temporal source model in which the observed biomagnetic fields are generated by a small number of current dipole sources with fixed positions/orientations and varying strengths. From the spatial covariance matrix of the observed fields, a signal subspace can be identified. The rank of this subspace is equal to the number of elemental sources present. This signal sub-space is used in a projection metric that scans the three dimensional head volume. Given a perfect signal subspace estimate and a perfect forward model, the metric will peak at unity at each dipole location. In practice, the signal subspace estimate is contaminated by noise, which in turn yields MUSIC peaks which are less than unity. Previously we examined the lower bounds on localization error, independent of the choice of localization procedure. In this paper, we analyzed the effects of noise and temporal coherence on the signal subspace estimate and the resulting effects on the MEG-MUSIC peaks.

• Research Organization: Los Alamos National Lab., NM (United States)
• Sponsoring Organization: USDOE, Washington, DC (United States)
• DOE Contract Number: W-7405-ENG-36
• OSTI ID: 10191934
• Report Number(s): LA-UR-93-2986; CONF-9308165-1; ON: DE93040125
• Resource Relation: Conference: BIOMAG 93: international conference on biomagnetism,Vienna (Austria),16-20 Aug 1993; Other Information: PBD: [1993]
• Country of Publication: United States
• Language: English

Related Subjects

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTANT EFFECTS ON LIVING ORGS. AND BIOL. MAT.
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
DIAGNOSTIC TECHNIQUES
ALGORITHMS
BIOELECTRICITY
MAGNETIC FIELDS
DIPOLES
NOISE
IMAGE PROCESSING
ERRORS
MONTE CARLO METHOD
SIGNALS
560000
990200
BIOMEDICAL SCIENCES
APPLIED STUDIES
MATHEMATICS AND COMPUTERS