title: Clustering strategies for optimal trial selection in multisensor environments. An eigenvector based approach.
abstract: BACKGROUND
  Quite often, magnetoencephalography (MEG) measurements are contaminated by a series of artifacts that degrade the quality of the various source localization methods applied to them. In particular, eye blinking, minor head movement and related activities are a constant source of measurement contamination. In order to solve this problem, trial selection and rejection is applied, a task that is usually performed manually.
  
  
  METHODS
  The present work shows an automatic trial selection and rejection algorithm based on clustering techniques. These techniques employ a measurement of the dissimilarity of the items belonging to a set. This measure, based on the projection of the eigenvector corresponding to the largest eigenvalue of the covariance matrix, is provided and its rationale is explained. Subsequently, covariance matrices belonging to the selected cluster are averaged and used in the well-known Linearly Constrained Minimum Variance (LCMV) Beamformer.
  
  
  RESULTS
  The results show a marked improvement of the specificity of the localization algorithm compared to the application of the LCMV without clustering.
  
  
  CONCLUSIONS
  The method shows a marked reduction in computational cost compared with other data cleaning procedure widely used: Independent Component Analysis (ICA).
  
  
  CONCLUSIONS
  Thus, we propose clustering techniques to be used in brain localization activity algorithms.
authors.affiliation: Instituto de Magnetismo Aplicado, Universidad Complutense de Madrid, ADIF, CSIC, Madrid, Spain. Electronic address: adehoyos@externos.adif.es.
authors.forename: Alfonso
authors.initials: A
authors.lastname: de Hoyos
authors.affiliation: Grupo de Procesado de Datos y Simulación, Escuela Técnica Superior de Ingenieros de Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain. Electronic address: javierp@grpss.ssr.upm.es.
authors.forename: Javier
authors.initials: J
authors.lastname: Portillo
authors.affiliation: Instituto de Magnetismo Aplicado, Universidad Complutense de Madrid, ADIF, CSIC, Madrid, Spain; Departamento de Física de Materiales, Facultad de Ciencias Físicas, Universidad Complutense de Madrid, Madrid, Spain. Electronic address: pmarin@externos.adif.es.
authors.forename: Pilar
authors.initials: P
authors.lastname: Marín
authors.affiliation: Laboratorio de Neurociencia Cognitiva y Computacional, UCM-UPM. Centro de Tecnología Biomédica, Spain; Departamento de Psicología Básica II, Facultad de Psicología, Universidad Complutense de Madrid, Madrid, Spain. Electronic address: fmaestuu@psi.ucm.es.
authors.forename: F
authors.initials: F
authors.lastname: Maestú
authors.affiliation: Departamento de Radiodiagnóstico del Hospital General Universitario Gregorio Marañón, Madrid, Spain. Electronic address: javier.lafuente@telefonica.net.
authors.forename: J Lafuente
authors.initials: JL
authors.lastname: M
authors.affiliation: Instituto de Magnetismo Aplicado, Universidad Complutense de Madrid, ADIF, CSIC, Madrid, Spain; Departamento de Física de Materiales, Facultad de Ciencias Físicas, Universidad Complutense de Madrid, Madrid, Spain. Electronic address: antonio.hernando@externos.adif.es.
authors.forename: Antonio
authors.initials: A
authors.lastname: Hernando
mesh_terms: D000328:Adult; D000465:Algorithms; D001307:Auditory Perception / Q000502:physiology; D001921:Brain / Q000502:physiology; D001931:Brain Mapping / Q000379:methods*; D016000:Cluster Analysis; D001330:Electronic Data Processing; D006801:Humans; D008279:Magnetic Resonance Imaging; D015225:Magnetoencephalography / Q000379:methods*; D012815:Signal Processing, Computer-Assisted
keywords: Clustering; Eigenvector; High-resolution spatial filtering; Linear Constrained Minimum Variance (LCMV); Magnetoencephalography; Spatial beamforming