Cover Image
QR Code

Multivariate assessment of event-related potentials with the t-CWT method.

Background: Event-related brain potentials (ERPs) are usually assessed with univariate statistical tests although they are essentially multivariate objects. Brain-computer interface applications are a notable exception to this practice, because they are based on multivariate classification of single...

Full description

Published in:BMC Neuroscience Vol. 16; pp. 1 - 21
Main Author: Bostanov, Vladimir
Format: equations & formulas tables/charts Journal Article
Published: BioMed Central 11/5/2015
Online Access:View this record in EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=110802786&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 110802786
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        14712202
        1CI8
      jtl: BMC Neuroscience
      issn: 14712202
      maglogo: N
    pubinfo:
      dt: 11/5/2015
      vid: 16
      pid: 24147
      pub: BioMed Central
    artinfo:
      ui:
        110802786
        110802786
        NLM26541673
        110802786
        10.1186/s12868-015-0185-z
        NLM26541673
        PMC4635610
        110802786
      ppf: 1
      ppct: 20
      formats:
      tig:
        atl: Multivariate assessment of event-related potentials with the t-CWT method.
      aug:
        au: Bostanov, Vladimir
        affil: Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Gartenstr. 29, 72074 Tübingen, Germany
      sug:
        subj:
          Multivariate Analysis
          Electroencephalography Methods
          Evoked Potentials Physiology
          Data Analysis, Statistical
          Signal Processing, Computer Assisted
          Factor Analysis
      ab: Background: Event-related brain potentials (ERPs) are usually assessed with univariate statistical tests although they are essentially multivariate objects. Brain-computer interface applications are a notable exception to this practice, because they are based on multivariate classification of single-trial ERPs. Multivariate ERP assessment can be facilitated by feature extraction methods. One such method is t-CWT, a mathematical-statistical algorithm based on the continuous wavelet transform (CWT) and Student's t-test.Results: This article begins with a geometric primer on some basic concepts of multivariate statistics as applied to ERP assessment in general and to the t-CWT method in particular. Further, it presents for the first time a detailed, step-by-step, formal mathematical description of the t-CWT algorithm. A new multivariate outlier rejection procedure based on principal component analysis in the frequency domain is presented as an important pre-processing step. The MATLAB and GNU Octave implementation of t-CWT is also made publicly available for the first time as free and open source code. The method is demonstrated on some example ERP data obtained in a passive oddball paradigm. Finally, some conceptually novel applications of the multivariate approach in general and of the t-CWT method in particular are suggested and discussed.Conclusions: Hopefully, the publication of both the t-CWT source code and its underlying mathematical algorithm along with a didactic geometric introduction to some basic concepts of multivariate statistics would make t-CWT more accessible to both users and developers in the field of neuroscience research.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N