DocumentCode :
1037572
Title :
Is it positive or negative? On determining ERP components
Author :
Graben, Peter Beim ; Frisch, Stefan
Author_Institution :
Inst. of Linguistics, Univ. of Potsdam, Leipzig, Germany
Volume :
51
Issue :
8
fYear :
2004
Firstpage :
1374
Lastpage :
1382
Abstract :
In most experiments using event-related brain potentials (ERPs), there is a straightforward way to define-on theoretical grounds-which of the conditions tested is the experimental condition and which is the control condition. If, however, theoretical assumptions do not give sufficient and unambiguous information to decide this question, then the interpretation of an ERP effect becomes difficult, especially if one takes into account that certain effects can be both a positivity or a negativity on the basis of the morphology of the pattern as well as with respect to peak latency (regard for example, N400 and P345). Exemplified with an ERP experiment on language processing, we present such a critical case and offer a possible solution on the basis of nonlinear data analysis. We show that a generalized polarity histogram, the word statistics of symbolic dynamics, is in principle able to distinguish negative going ERP components from positive ones when an appropriate encoding strategy, the half wave encoding is employed. We propose statistical criteria which allow to determine ERP components on purely methodological grounds.
Keywords :
bioelectric potentials; data analysis; electroencephalography; encoding; statistical analysis; symbol manipulation; control condition; event-related brain potentials; experimental condition; generalized polarity histogram; half wave encoding; language processing; negative ERP components; nonlinear data analysis; pattern morphology; positive ERP components; symbolic dynamics; Data analysis; Delay; Encoding; Enterprise resource planning; Histograms; Morphology; Natural languages; Statistics; Testing; Voltage control; Algorithms; Computer Simulation; Electroencephalography; Evoked Potentials; Humans; Models, Neurological; Models, Statistical; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2004.827558
Filename :
1315859
Link To Document :
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