Summary
Objective
: The objective of this study is to explore suitable spatial filters for inverse estimation
of cortical equivalent dipole layer imaging from the scalp electroencephalogram. We
utilize cortical dipole source imaging to locate the possible generators of scalpmeasured
movement-related potentials (MRPs) in human.
Methods
: The effects of incorporating signal and noise covariance into inverse procedures
were examined by computer simulations and experimental study. The parametric projection
filter (PPF) and parametric Weiner filter (PWF) were applied to an inhomogeneous threesphere
head model under various noise conditions.
Results
: The present simulation results suggest that the PWF incorporating signal information
provides better cortical dipole layer imaging results than the PPF and Tikhonov regularization
under the condition of moderate and high correlation between signal and noise distributions.
On the other hand, the PPF has better performance than other inverse filters under
the condition of low correlation between signal and noise distributions. The proposed
methods were applied to self-paced MRPs in order to identify the anatomic substrate
locations of neural generators. The dipole layer distributions estimated by means
of PPF are well-localized as compared with blurred scalp potential maps and dipole
layer distribution estimated by Tikhonov regularization. The proposed methods demonstrated
that the contralateral premotor cortex was preponderantly activated in relation to
movement performance.
Conclusions
: In cortical dipole source imaging, the PWF has better performance especiallywhen
the correlation between the signal and noise is high. The proposed inverse method
was applicable to human experiments of MRPs if the signal and noise covariances were
obtained.
Keywords
High-resolution EEG - cortical dipole imaging - inverse problem - parametric Weiner
filter - signal and noise covariance - movement-related potential