High-resolution EEG: A new realistic geometry spline Laplacian estimation technique

Bin He, Jie Lian, Guanglin Li

Research output: Contribution to journalArticlepeer-review

71 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)845-852
Number of pages8
JournalClinical Neurophysiology
Volume112
Issue number5
DOIs
StatePublished - 2001

Bibliographical note

Funding 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.

Keywords

  • Electroencephalography
  • High-resolution electroencephalogram
  • Inverse problem
  • Laplacian mapping
  • Realistic geometry head model
  • Regularization
  • Surface Laplacian
  • VEP

Fingerprint Dive into the research topics of 'High-resolution EEG: A new realistic geometry spline Laplacian estimation technique'. Together they form a unique fingerprint.

Cite this