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Soft/hard focalization in the EEG inverse problem

Presented at Bordeaux (France), Jul 17-20
Publication date2005
Abstract

We present in this paper a novel statistical based focalized reconstruction method for the underdetermined EEG (electroencephalogram) inverse problem. The algorithm is based on the representation of non-Gaussian distributions as an infinite mixture of Gaussians (IMG) and relies on an iterative procedure consisting out of alternated variance estimation/linear inversion operations. By taking into account noise statistics, it performs implicit spurious data rejection and produces robust focalized solutions allowing for straightforward discrimination of active/non-active brain regions. We apply the proposed reconstruction procedure to average evoked potentials EEG data and compare the reconstruction results with the corresponding known physiological responses.

Keywords
  • Additive noise
  • Art
  • Brain modeling
  • Electrodes
  • Electroencephalography
  • Hospitals
  • Inverse problems
  • Noise robustness
  • Psychiatry
  • Volume measurement
Citation (ISO format)
ALECU, Teodor et al. Soft/hard focalization in the EEG inverse problem. In: IEEE/SP 13th Workshop on Statistical Signal Processing, 2005 (SSP′05). Bordeaux (France). [s.l.] : [s.n.], 2005. p. 978–983. doi: 10.1109/SSP.2005.1628737
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