TY - JOUR
T1 - Simultaneous estimation and testing of sources in multiple MEG data sets
AU - Bijma, Fetsje
AU - de Munck, Jan C.
AU - Huizenga, Hilde M.
AU - Heethaar, Rob M.
AU - Nehorai, Arye
PY - 2005/9
Y1 - 2005/9
N2 - The proposed Extended Couple Dipole Model (ECDM) is a trilinear component model that can be used to analyze multiple, related MEG data sets simultaneously. Related MEG data sets are data sets that contain activity of the same sources or activity of sources that have proportional source amplitudes. The simultaneous model uses a set of common sources and a set of common source time functions (wave shapes) to model the measured data in each data set. The set of common sources contains all sources that are active in at least one of the data sets to be analyzed. The number of common spatial and temporal components is specified by the user. The model for each data set is a linear combination of these common spatial and temporal components. This linear combination is estimated in a coupling matrix. Unlike the Coupled Dipole Model, where the user selects certain entries of the coupling matrix to be zero, the entire coupling matrix is estimated in the ECDM. This yields a more objective and statistically transparent estimation method, of which the identifiability constraints do not depend on the user's chosen design as in the CDM. Cramér-Rao Bounds are derived for the ECDM, and the significance of the estimated source activity is computed and illustrated by confidence regions around estimated source time functions.
AB - The proposed Extended Couple Dipole Model (ECDM) is a trilinear component model that can be used to analyze multiple, related MEG data sets simultaneously. Related MEG data sets are data sets that contain activity of the same sources or activity of sources that have proportional source amplitudes. The simultaneous model uses a set of common sources and a set of common source time functions (wave shapes) to model the measured data in each data set. The set of common sources contains all sources that are active in at least one of the data sets to be analyzed. The number of common spatial and temporal components is specified by the user. The model for each data set is a linear combination of these common spatial and temporal components. This linear combination is estimated in a coupling matrix. Unlike the Coupled Dipole Model, where the user selects certain entries of the coupling matrix to be zero, the entire coupling matrix is estimated in the ECDM. This yields a more objective and statistically transparent estimation method, of which the identifiability constraints do not depend on the user's chosen design as in the CDM. Cramér-Rao Bounds are derived for the ECDM, and the significance of the estimated source activity is computed and illustrated by confidence regions around estimated source time functions.
KW - Component model
KW - Confidence intervals
KW - Constrained Cramèr-Rao Bound
KW - Coupled dipole model
KW - MEG
KW - Spatiotemporal covariance
KW - Trilinear model
UR - https://www.scopus.com/pages/publications/27644577859
U2 - 10.1109/TSP.2005.853097
DO - 10.1109/TSP.2005.853097
M3 - Article
AN - SCOPUS:27644577859
SN - 1053-587X
VL - 53
SP - 3449
EP - 3460
JO - IEEE Transactions on Signal Processing
JF - IEEE Transactions on Signal Processing
IS - 9
ER -