Asymptotic SNR of scalar and vector minimum-variance beanformers for neuromagnetic source reconstruction

Kensuke Sekihara, Srikantan S. Nagarajan, David Poeppel, Alec Marantz

Research output: Contribution to journalArticle


To reconstruct neuromagnetic sources, the minimum-variance, beamformer has been extended to incorporate the three-dimensional vector nature of the sources, and two types of extensions-the scalar- and vector-type extensions-have been proposed. This paper discusses the asymptotic signal-to-noise ratio (SNR) of the outputs of these two types of beamformers. We first show that these two types of beamformers give exactly the same output power and output SNR if the beamformer pointing direction is optimized. We then compare the output SNR of the beamformer with optimum direction to that of the conventional vector beamformer formulation where the beamformer pointing direction is not optimized. The comparison shows that the beamformer with optimum direction gives an output SNR superior to that of the conventional vector beamformer. Numerical examples validating the results of the analysis are presented.

Original languageEnglish (US)
Pages (from-to)1726-1734
Number of pages9
JournalIEEE Transactions on Biomedical Engineering
Issue number10
StatePublished - Oct 1 2004



  • Biomagnetism
  • Inverse problems
  • Magnetoencephalography
  • Minimum-variance beamformer
  • Neural signal processing

ASJC Scopus subject areas

  • Biomedical Engineering

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