Background: A new realistic geometry (RG) spline Laplacian estimation technique has been developed for high-resolution EEG imaging. Methods: Estimation of the parameters associated with the spline Laplacian is formulated by seeking the general inverse of a transfer matrix. The number of spline parameters, which need to be determined through regularization, is reduced to one in the present approach, thus enabling easy implementation of the RG spline Laplacian estimator. Results: Computer simulation studies have been conducted to test the feasibility of the new approach in a 3-concentric-sphere head model. The new technique has also been applied to human visual evoked potential data with a RG head model. Conclusions: The present numerical and experimental results demonstrate the feasibility of the new approach and indicate that the RG spline Laplacian can be estimated easily from the surface potentials and the scalp geometry.
Bibliographical noteFunding Information:
The authors would like to thank Dr D Wu for useful discussions on the Laplacian estimation algorithm, and Dr H Sasaki for discussion on the human experimentation and for providing the boundary element model of the subject used in this work. This work was supported in part by NSF CAREER Award BES-9875344.
- High-resolution electroencephalogram
- Inverse problem
- Laplacian mapping
- Realistic geometry head model
- Surface Laplacian