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The effects of attention and task-relevance on the processing of syntactic violations during listening to two concurrent speech streams

  • Orsolya Szalárdy
  • Brigitta Tóth
  • Dávid Farkas
  • Annamária Kovács
  • Gábor Urbán
  • Gábor Orosz
  • Beáta Tünde Szabó
  • László Hunyadi
  • Botond Hajdu
  • István Winkler
Article
  • 1 Downloads

Abstract

The notion of automatic syntactic analysis received support from some event-related potential (ERP) studies. However, none of these studies tested syntax processing in the presence of a concurrent speech stream. Here we present two concurrent continuous speech streams, manipulating two variables potentially affecting speech processing in a fully crossed design: attention (focused vs. divided) and task (lexical – detecting numerals vs. syntactical – detecting syntactic violations). ERPs elicited by syntactic violations and numerals as targets were compared with those for distractors (task-relevant events in the unattended speech stream) and attended and unattended task-irrelevant events. As was expected, only target numerals elicited the N2b and P3 components. The amplitudes of these components did not significantly differ between focused and divided attention. Both task-relevant and task-irrelevant syntactic violations elicited the N400 ERP component within the attended but not in the unattended speech stream. P600 was only elicited by target syntactic violations. These results provide no support for the notion of automatic syntactic analysis. Rather, it appears that task-relevance is a prerequisite of P600 elicitation, implying that in-depth syntactic analysis occurs only for attended speech under everyday listening situations.

Keywords

Concurrent speech streams Syntactic violation processing Lexical processing Attention N400 P600 N2b P3 

Notes

Acknowledgements

This work was funded by the Hungarian Academy of Sciences’ Lendület project [LP2012-36/2012] awarded to István Winkler. The authors are grateful to Zsuzsanna D’Albini and Zsuzsanna Kovács for collecting the EEG data, to Ágnes Palotás for text editing, László Liszkai for audio recording and editing, and to Ferenc Elek and Péter Scherer for voicing the texts.

Supplementary material

13415_2018_614_MOESM1_ESM.docx (1.4 mb)
ESM 1 (DOCX 1383 kb)

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Copyright information

© Psychonomic Society, Inc. 2018

Authors and Affiliations

  • Orsolya Szalárdy
    • 1
    • 2
  • Brigitta Tóth
    • 1
  • Dávid Farkas
    • 1
  • Annamária Kovács
    • 1
    • 3
  • Gábor Urbán
    • 1
    • 4
  • Gábor Orosz
    • 1
    • 5
  • Beáta Tünde Szabó
    • 1
    • 6
  • László Hunyadi
    • 7
  • Botond Hajdu
    • 1
  • István Winkler
    • 1
  1. 1.Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural SciencesHungarian Academy of SciencesBudapestHungary
  2. 2.Research Centre for Natural SciencesHungarian Academy of SciencesBudapestHungary
  3. 3.Department of Telecommunications and Media Informatics, Faculty of Electrical Engineering and InformaticsBudapest University of Technology and EconomicsBudapestHungary
  4. 4.Department of Cognitive Science, Faculty of Natural SciencesBudapest University of Technology and EconomicsBudapestHungary
  5. 5.Faculty of Education and PsychologyEötvös Loránd UniversityBudapestHungary
  6. 6.Faculty of Information Technology and BionicsPázmány Péter Catholic UniversityBudapestHungary
  7. 7.Department of General and Applied LinguisticUniversity of DebrecenDebrecenHungary

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