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Single trial ERP reading based on parallel factor analysis
Author(s) -
Vanderperren Katrien,
Mijović Bogdan,
Novitskiy Nikolay,
Vanrumste Bart,
Stiers Peter,
Van den Bergh Bea R. H.,
Lagae Lieven,
Sunaert Stefan,
Wagemans Johan,
Van Huffel Sabine,
De Vos Maarten
Publication year - 2013
Publication title -
psychophysiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.661
H-Index - 156
eISSN - 1469-8986
pISSN - 0048-5772
DOI - 10.1111/j.1469-8986.2012.01405.x
Subject(s) - preprocessor , task (project management) , psychology , electroencephalography , reading (process) , pattern recognition (psychology) , computer science , cognitive psychology , speech recognition , artificial intelligence , neuroscience , management , political science , law , economics
The extraction of task‐related single trial ERP features has recently gained much interest, in particular in simultaneous EEG‐fMRI applications. In this study, a specific decomposition known as parallel factor analysis ( PARAFAC ) was used, in order to retrieve the task‐related activity from the raw signals. Using visual detection task data, acquired in normal circumstances and simultaneously with fMRI , differences between distinct task‐related conditions can be captured in the trial signatures of specific PARAFAC components when applied to ERP data arranged in C hannels × T ime × T rials arrays, but the signatures did not correlate with the fMRI data. Despite the need for parameter tuning and careful preprocessing, the approach is shown to be successful, especially when prior knowledge about the expected ERPs is incorporated.