Signal space separation beamformer

Abstract

Event Abstract Back to Event Signal space separation beamformer Samu Taulu1*, Jiri Vrba1, Jukka Nenonen1 and Antti Ahonen1 1 Elekta Oy, Finland We have combined signal space separation and beamformers (SSS beamformer). The SSS beamformer differs from the conventional beamformer by operating on the magnetostatic multipole moments instead of physical MEG sensors. SSS represents the MEG signals by a truncated spherical harmonic function expansion that has spatially different components and truncation orders for brain signals and external interference. We tested the method by simulation in the presence of simulated brain noise. The SSS beamformer performs at least as well as the conventional beamformer, provided that the order of the internal expansion is sufficiently high. For beamformer outputs which depend on power or power difference normalized by the projected noise, the spatial resolution of the SSS beamformer is significantly better than that of the conventional beamformers if the sources are deep, and about the same as that of the conventional beamformer when the sources are superficial. For dual-state beamformer outputs which depend on the ratio of powers, the SSS and conventional beamfomers have the same spatial resolution. These observations are consistent with the different characteristics of the signal vectors composed of the multipole moments or the outputs of the physical sensors. The signal vector comprised of multipoles tends to exhibit a larger change with respect to a modification of the source configuration than the corresponding signal vector of physical sensors, especially for relatively deep sources. The sensor noise covariance matrix in the SSS basis is non-diagonal. The SSS beamformers with diagonalized noise covariance matrix exhibit better spatial resolution than that with non-diagonal noise covariance matrix. In summary, the SSS beamformers are computationally more efficient than the conventional beamformers and provide at least the same or better spatial resolution as compared to conventional beamformers. Conference: Biomag 2010 - 17th International Conference on Biomagnetism , Dubrovnik, Croatia, 28 Mar - 1 Apr, 2010. Presentation Type: Poster Presentation Topic: MEG Modeling Citation: Taulu S, Vrba J, Nenonen J and Ahonen A (2010). Signal space separation beamformer. Front. Neurosci. Conference Abstract: Biomag 2010 - 17th International Conference on Biomagnetism . doi: 10.3389/conf.fnins.2010.06.00061 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 21 Mar 2010; Published Online: 21 Mar 2010. * Correspondence: Samu Taulu, Elekta Oy, Helsinki, Finland, samu.taulu@neuromag.fi Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Samu Taulu Jiri Vrba Jukka Nenonen Antti Ahonen Google Samu Taulu Jiri Vrba Jukka Nenonen Antti Ahonen Google Scholar Samu Taulu Jiri Vrba Jukka Nenonen Antti Ahonen PubMed Samu Taulu Jiri Vrba Jukka Nenonen Antti Ahonen Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.