Multivariate assessment of event-related potentials with the t-CWT method. Issue 1 (December 2015)

• Record Type: Journal Article
• Authors: Bostanov, Vladimir
• Is Part Of: BMC neuroscience. Volume 16:Issue 1(2015)
• Page Start: 1
• Page End: 20
• Publication Date: 2015-12
• Subjects: Event-related brain potentials -- ERP -- Continuous wavelet transform -- CWT -- t-CWT -- Principal component analysis -- PCA -- Multivariate statistics; Neurosciences -- Periodicals; 573.805
• DOI: 10.1186/s12868-015-0185-z
• Languages: English
• ISSNs: 1471-2202

Abstract

Abstract 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.