Scientific article
Open access

Estimating EEG source dipole orientation based on singular-value decomposition for connectivity analysis

Published inBrain Topography, vol. 32, no. 4, p. 704-719
Publication date2019

In the last decade, the use of high-density electrode arrays for EEG recordings combined with the improvements of source reconstruction algorithms has allowed the investigation of brain networks dynamics at a sub-second scale. One powerful tool for investigating large-scale functional brain networks with EEG is time-varying effective connectivity applied to source signals obtained from electric source imaging. Due to computational and interpretation limitations, the brain is usually parcelled into a limited number of regions of interests (ROIs) before computing EEG connectivity. One specific need and still open problem is how to represent the time- and frequency-content carried by hundreds of dipoles with diverging orientation in each ROI with one unique representative time-series. The main aim of this paper is to provide a method to compute a signal that explains most of the variability of the data contained in each ROI before computing, for instance, time-varying connectivity. As the representative time-series for a ROI, we propose to use the first singular vector computed by a singularvalue decomposition of all dipoles belonging to the same ROI. We applied this method to two real datasets (visual evoked potentials and epileptic spikes) and evaluated the time-course and the frequency content of the obtained signals. For each ROI, both the time-course and the frequency content of the proposed method reflected the expected time-course and the scalp-EEG frequency content, representing most of the variability of the sources (~80%) and improving connectivity results in comparison to other procedures used so far. We also confirm these results in a simulated dataset with a known ground truth.

  • EEG
  • Source space activity
  • Dipole orientation
  • Visual evoked potentials
  • Epilepsy
Citation (ISO format)
RUBEGA, Maria et al. Estimating EEG source dipole orientation based on singular-value decomposition for connectivity analysis. In: Brain Topography, 2019, vol. 32, n° 4, p. 704–719. doi: 10.1007/s10548-018-0691-2
Main files (2)
Article (Published version)
Article (Accepted version)
ISSN of the journal0896-0267

Technical informations

Creation10/14/2019 12:06:00 PM
First validation10/14/2019 12:06:00 PM
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