Depth-sensitive algorithm to localize sources using minimum norm estimations

B. Pinto, A. C. Sousa, Carla Quintão

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

Abstract

The main objective of this paper is to apply and evaluate the neural source localisation accuracy of a new depth-sensitive algorithm using physiological data. This new algorithm is based on the behaviour of the dispersion of the minimum norm solutions (MNE), and was already tested with simulated data [1], yielding an accuracy of 2 to 4 mm in noise-free situations, and a mean accuracy of 10 mm for more disadvantageous situations. We estimate now the neural source depth in EEG recordings, namely in focal epileptic interictal paroxisms and in N100 auditory evoked potentials of normal volunteers. We show that the accuracy of the method is comparable with the commonly used dipolar localizations, when it was applied to those bio-signal recordings. It was revealed that, under adequate constraints, the algorithm is suitable for the estimation of the depth of one or two simultaneous neural generators, using a rather simple MNE approach. This study, demonstrating that MNE can handle spatial-limited sources successfully, opens the possibility to localize both quasi-punctual and extended neural generators using only the simplest MNE algorithm.

Original languageEnglish
Title of host publication13th Mediterranean Conference on Medical and Biological Engineering and Computing 2013 - MEDICON 2013
Pages1726-1729
Number of pages4
Volume41
DOIs
Publication statusPublished - 2014
Event13th Mediterranean Conference on Medical and Biological Engineering and Computing 2013, MEDICON 2013 - Seville, Spain
Duration: 25 Sep 201328 Sep 2013

Conference

Conference13th Mediterranean Conference on Medical and Biological Engineering and Computing 2013, MEDICON 2013
CountrySpain
CitySeville
Period25/09/1328/09/13

Keywords

  • Depth-sensitive miminum norm estimation
  • EEG source localization

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