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Single trial ERP reading based on parallel factor analysis

Authors

  • Katrien Vanderperren,

    Corresponding author
    1. IBBT-KU Leuven Future Health Department, Leuven, Belgium
    • Department of Electrical Engineering, ESAT-SCD, Katholieke Universiteit Leuven, Leuven, Belgium
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  • Bogdan Mijović,

    1. Department of Electrical Engineering, ESAT-SCD, Katholieke Universiteit Leuven, Leuven, Belgium
    2. IBBT-KU Leuven Future Health Department, Leuven, Belgium
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  • Nikolay Novitskiy,

    1. Laboratory of Experimental Psychology, Katholieke Universiteit Leuven, Leuven, Belgium
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  • Bart Vanrumste,

    1. Department of Electrical Engineering, ESAT-SCD, Katholieke Universiteit Leuven, Leuven, Belgium
    2. Biosciences and Technology Department, MOBILAB, Katholieke Hogeschool Kempen, Geel, Belgium
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  • Peter Stiers,

    1. Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
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  • Bea R. H. Van den Bergh,

    1. Department of Psychology, Tilburg University, Tilburg, The Netherlands
    2. Department of Psychology, Katholieke Universiteit Leuven, Leuven, Belgium
    3. Flemish Government, Department of Welfare, Public Health and Family, Brussels, Belgium
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  • Lieven Lagae,

    1. Department of Pediatric Neurology, Katholieke Universiteit Leuven, Leuven, Belgium
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  • Stefan Sunaert,

    1. Department of Radiology, Katholieke Universiteit Leuven, Leuven, Belgium
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  • Johan Wagemans,

    1. Laboratory of Experimental Psychology, Katholieke Universiteit Leuven, Leuven, Belgium
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  • Sabine Van Huffel,

    1. Department of Electrical Engineering, ESAT-SCD, Katholieke Universiteit Leuven, Leuven, Belgium
    2. IBBT-KU Leuven Future Health Department, Leuven, Belgium
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  • Maarten De Vos

    1. Department of Electrical Engineering, ESAT-SCD, Katholieke Universiteit Leuven, Leuven, Belgium
    2. Department of Psychology, Neuropsychology Lab, Oldenburg University, Oldenburg, Germany
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  • This research is supported by the Research Council KU Leuven: GOA MaNet and CoE EF/05/006; IUAP P6/04 (DYSCO, 2007–2011); the Flemish Government: G.0427.10N Integrated EEG-fMRI, IWT-TBM080658-MRI and IBBT; and Neuromath (COST-BM0601). K. Vanderperren is supported by a PhD grant from the Agency for Innovation by Science and Technology (IWT), M. De Vos by an Alexander von Humboldt grant, and J. Wagemans by long-term structural funding from the Flemish Government (METH/08/02).

Address correspondence to: Katrien Vanderperren, Kasteelpark Arenberg 10—Box 2446, B-3001 Leuven, Belgium. E-mail: katrien.vanderperren@esat.kuleuven.be

Abstract

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 Channels × Time × Trials 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.

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