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Visual Mismatch Negativity as a Non-attentional Reaction to Change in Repetition Pattern

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Innovations in Biomedical Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 526))

Abstract

Mismatch negativity (MMN) is an event related potential generated by brain’s electric activation as an automatic response to change in repetitive stimulation. Two scenarios of an oddball experiment were performed among 9 students of University of Silesia at the age of 20–25 years, with the use of standard, deviant and distractor events. Difference deviant-standard waveforms were obtained, which presented posterior negativity in the range 140–200 ms after stimulus onset. Subtraction of the standard from deviant ERP waveforms, irrelevance to participant’s task, and independence from stimulus physical parameters imply that the posterior negativity evoked in this study seems to be a visual mismatch negativity as a result of pre-attentive central visual processing.

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Authors and Affiliations

  1. Department of Medical Physics, Institute of Physics, University of Silesia, Uniwersytecka Street 4, 40-007, Katowice, Poland

    Karina Maciejewska, Zofia Drzazga & Agnieszka Trojankowska

Authors
  1. Karina Maciejewska
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  2. Zofia Drzazga
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  3. Agnieszka Trojankowska
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Corresponding author

Correspondence to Karina Maciejewska .

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Editors and Affiliations

  1. Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland

    Marek Gzik

  2. Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland

    Ewaryst Tkacz

  3. Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland

    Zbigniew Paszenda

  4. Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland

    Ewa Piętka

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Maciejewska, K., Drzazga, Z., Trojankowska, A. (2017). Visual Mismatch Negativity as a Non-attentional Reaction to Change in Repetition Pattern. In: Gzik, M., Tkacz, E., Paszenda, Z., Piętka, E. (eds) Innovations in Biomedical Engineering. Advances in Intelligent Systems and Computing, vol 526. Springer, Cham. https://doi.org/10.1007/978-3-319-47154-9_34

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  • DOI: https://doi.org/10.1007/978-3-319-47154-9_34

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47153-2

  • Online ISBN: 978-3-319-47154-9

  • eBook Packages: EngineeringEngineering (R0)

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