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Weeda, Wouter

EEG/MEG components: A new statistical approach to analyze their (co)variance properties

Wouter Weeda (NWO PhD student)
Developmental Psychology
Department of Psychology
FMG, University of Amsterdam
Roetersstraat 15
1018 WB Amsterdam
Phone: +31 20 525 6908 / 6830 (secretary)
E-mail: Wouter Weeda
Project: NWO project at University of Amsterdam

Project running from: 1 March 2006 – 1 March 2010
Supervisors: Prof. dr M.W. Van der Molen, dr H.M. Huizenga

Summary of project

In this project the primary aim is to assess variance and covariance properties of EEG/MEG components, without the need to localize these components. Such a method should meet several criteria. First, it is necessary that signal variance can be dissociated from noise variance. Second, it should be possible to disentangle latency variance and tests of amplitude and latency variance parameters. Third, it is neccessary that the amplitude covariance between components can be estimated and tested. Existing methods (e.g. variance, complexity, wavelets, independent component analysis, parallel factor analysis) are adequate to answer other reseacrh quetions, but they do not meet the aforementioned criteria, and thus are not suited for the present purposes.

We therefore develop a new statistical method that does meet these criteria. By modeling EEG/MEG by a sum of a) partly random temporal component functions and b) a noise variance model, it will become possible to reliably assess variations in amplitude and latency, and the covariance of amplitudes. Since the proposed method is new and by no means straigthforward, it will be developed in several subprojects that have substantial merits in their own right.

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