Brain source localization techniques: Evaluation study using simulated EEG data

Rasha Hyder, Nidal Kamel, Tong Boon Tang, Jose bornot

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Several methods have been proposed over the past few decades as a solution to the brain sources localization problem using EEG signals. In this paper the performances of different brain source localization techniques, including the Minimum Norm Estimates (MNE), Low Resolution Electrical Tomography (LORETA) and Multiple Sparse Priors (MSP), are assessed and compared. Due to the lack of the baseline, the evaluation is conducted using simulated dipolar source distributions constrained to the cortical surface. We corroborate in the superiority of MSP over LORETA and MNE in accurately estimating the locations of the simulated sources, however we found that MNE and LORETA may account as a better measure for asymmetric activations.
Original languageEnglish
Title of host publication2014 IEEE Conference on Biomedical Engineering and Sciences (IECBES)
Number of pages6
Publication statusPublished online - 26 Feb 2015


  • EEG
  • Source localization
  • Simulated dipoles
  • Inversion techniques


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