Spatio-Temporal Cortical Source Imaging of Brain Electrical Activity by Means of Time-Varying Parametric Projection Filter

Junichi Hori, Masaaki Aiba, Bin He

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


In the present study, we explore suitable spatio-temporal filters for inverse estimation of an equivalent dipole-layer distribution from the scalp electroencephalogram (EEG) for imaging of brain electric sources. We propose a time-varying parametric projection filter (tPPF) for the spatio-temporal EEG analysis. The performance of this tPPF algorithm was evaluated by computer simulation studies. An inhomogeneous three-concentric-spheres model was used in the present simulation study to represent the head volume conductor. An equivalent dipole layer was used to represent equivalently brain electric sources and estimated from the scalp potentials. The tPPF filter was tested to remove time-varying noise such as instantaneous artifacts caused by eyes-blink. The present simulation results indicate that the proposed time-variant tPPF method provides enhanced performance in rejecting time-varying noise, as compared with the time-invariant parametric projection filter.

Original languageEnglish (US)
Pages (from-to)768-777
Number of pages10
JournalIEEE Transactions on Biomedical Engineering
Issue number5
StatePublished - May 2004

Bibliographical note

Funding Information:
Manuscript received September 30, 2002; revised August 10, 2003. This work was supported in part by the National Science Foundation under CAREER Award BES-9875344, in part by Japanese Society for the Promotion of Science under Grant-In-Aid for Scientific Research 13480291, and in part by Niigata University under Grant for Promotion of Research Projects, and in part by the National Institutes of Health (NIH) under Grant 1RO1EB00178. Asterisk indicates corresponding author.


  • Equivalent dipole sources
  • Eyes blink artifact elimination
  • High-resolution EEG
  • Inverse problem
  • Parametric projection filter
  • Spatio-temporal inverse filter


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