New Perspectives on the Use of Spatial Filters in Magnetoencephalographic Array Processing

Autores/as

  • Claudia Carolina Zaragoza Martínez Centro de Investigación y de Estudios Avanzados del IPN
  • David Gutiérrez Centro de Investigación y de Estudios Avanzados del IPN

DOI:

https://doi.org/10.13053/cys-20-1-2185

Palabras clave:

Magnetoencephalography, beamformer, spatial filtering, neural activity indexes, dipole source localization.

Resumen

The increase in computer power of the last few decades has allowed the resurgence of the theory behind spatial filtering (a.k.a. beamforming) and its application to array signal processing. That is the case of magnetoencephalographic (MEG) data, which relies on dense arrays of detectors in order to measure the brain activity non-invasively. In particular, spatial filters are used in MEG signal processing to estimate the magnitude and location of the current sources within the brain. This is achieved by calculating different beamformer-based indexes which usually involve a large computational complexity. Here, a new perspective on how today’s computers make it possible to handle such complexity is presented, up to the point when new and ever more complex neural activity indexes can be developed. Such is the case of indexes based on eigenspace projections and reduced-rank beamformers, whose applicability is shown in this paper for the case of using real MEG measurements and realistic models.

Biografía del autor/a

Claudia Carolina Zaragoza Martínez, Centro de Investigación y de Estudios Avanzados del IPN

received the B.Sc. degree in electronic engineering from the Technological Institute of Madero City, Tamaulipas, in 2009, and the M.Sc. and Ph.D. degrees in biomedical engineering and physics from the Center for Research and Advanced Studies (Cinvestav), Monterrey’s Unit, in 2011 and 2015, respectively. Her research interests are in the area of biomedical signal processing, specifically in neuroelectrical signal processing with EEG and MEG data.

David Gutiérrez, Centro de Investigación y de Estudios Avanzados del IPN

better known as Dania  Gutiérrez, received the B.Sc. degree (with honors) in electrical engineering from the National Autonomous University of Mexico (UNAM), Mexico, in 1997, the M.Sc. degree in electrical engineering and computer sciences, as well as the Ph.D. degree in bioengineering from the University of Illinois at Chicago (UIC), in 2000 and 2005, respectively. From March 2005 to May 2006, she held a postdoctoral fellowship at the Department of Computer Systems Engineering and Automation, Institute of Research in Applied Mathematics and Systems (IIMAS), UNAM. In June 2006, she joined the Center for Research and Advanced Studies (Cinvestav) at Monterrey, Mexico. There, she is an associate professor in the area of medical sciences, as well as the current academic secretary. Dr. Guti´ errez’s research interests are in statistical signal processing and its applications to biomedicine. She is also interested in computer sciences, neurosciences, and robotics. Dr. Gutiérrez is a former Fulbright Scholar, and a former student fellow of the Mexican Council for Science and Technology (Conacyt). She has been a member of Conacyt’s researchers system (SNI) since 2007, from which she currently holds the Level-I fellowship. She is also a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE).

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Publicado

2016-03-31

Número

Vol. 20 Núm. 1 (2016): Thematic Issue: Topic Trends in Computing Research (Guest Editor: Claudia P. Ayala)

Sección

Artículos

Licencia

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