Decomposition of magnetoencephalographic data into components corresponding to deep and superficial sources

ÖZKURT T. E., Sun M., Sclabassi R. J.

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, cilt.55, sa.6, ss.1716-1727, 2008 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 55 Sayı: 6
  • Basım Tarihi: 2008
  • Doi Numarası: 10.1109/tbme.2008.919120
  • Dergi Adı: IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1716-1727
  • Anahtar Kelimeler: beamspace, biomagnetism, inverse problem, magnetoencephalography (MEG), signal space separation (SSS), source localization, spatial filtering, spherical harmonics, MEG, SPACE, EEG
  • Orta Doğu Teknik Üniversitesi Adresli: Hayır

Özet

We extend the signal space separation (SSS) method to decompose multichannel magnetoencephalographic (MEG) data into regions of interest inside the head. It has been shown that the SSS method can transform MEG data into a signal component generated by neurobiological sources and a noise component generated by external sources outside the head. In this paper, we show that the signal component obtained by the SSS method can be further decomposed by a simple operation into signals originating from deep and superficial sources within the brain. This is achieved by using a scheme that exploits the beamspace methodology that relies on a linear transformation that maximizes the power of the source space of interest. The efficiency and accuracy of the algorithm are demonstrated by experiments utilizing both simulated and real MEG data.