Cover not available
Article published In:
Interpreting
Vol. 24:1 (2022) ► pp.1–37

When two languages are competing

An ERP study of sentence processing in expert and novice interpreters

| National Taiwan University
| National Taiwan Normal University
| National Taiwan Normal University
Past studies have shown that expert interpreters were better than novices at using contextual cues to anticipate upcoming information. However, whether such sensitivity to contextual cues can be traced by means of neural signatures is relatively unexplored. The present study used event-related brain potentials (ERPs) along with a language-switching paradigm – including non-switched (Chinese–Chinese, L1–L1) and switched (Chinese–English, L1–L2) conditions – to investigate whether interpreters with many years of experience, interpreters with a few years of experience and post-graduate-level interpreting students differed in the way they process contextually congruent or incongruent sentence-final target words. The results show that while the manipulations of congruency and switching independently induced a strong brain response in all three groups, the interaction between the two factors elicited different patterns across groups during 500–700 ms: (1) while a sustained congruency effect was found in the two less-experienced groups for the switched condition, such an effect was observed in the most experienced group for both switched and non-switched conditions; (2) only the least-experienced group showed a frontal negativity towards incongruent trials in the switched condition. These 200 ms transient group differences revealed that it might be possible to trace the development of interpreting ability by examining the ERP components in a language-switching setting.
Keywords: interpreting expertise, N400, PNP, language switching
Article outline
  • 1.Introduction
    • 1.1N400 and associated cognitive functions
    • 1.2Post-N400 positivity (PNP) and associated cognitive functions
    • 1.3ERP studies on interpreting
    • 1.4The present study
  • 2.Methods
    • 2.1Participants
    • 2.2Materials
    • 2.3Procedure
    • 2.4Data acquisition and preprocessing
    • 2.5Data analysis
  • 3.Results
    • 3.1Behavioral data
    • 3.2ERP data
      • 3.2.1300–500 ms
      • 3.2.2500–700 ms
      • 3.2.3700–1000 ms
  • 4.Discussion
  • 5.Conclusion
  • Notes
  • References
Published online: 16 November 2021
DOI logo
https://doi.org/10.1075/intp.00069.fan
References (63)
References
Brothers, T., Swaab, T. Y. & Traxler, M. J. (2017). Goals and strategies influence lexical prediction during sentence comprehension. Journal of Memory and Language 93 1, 203–216. DOI logoGoogle Scholar
Brothers, T., Wlotko, E. W., Warnke, L. & Kuperberg, G. R. (2020). Going the extra mile: Effects of discourse context on two late positivities during language comprehension. Neurobiology of Language 1 (1), 135–160. DOI logoGoogle Scholar
Brouwer, H. & Crocker, M. W. (2017). On the proper treatment of the N400 and P600 in language comprehension. Frontiers in Psychology 8 (1327). DOI logoGoogle Scholar
Brouwer, H., Crocker, M. W., Venhuien, N. J. & Hoeks, J. C. J. (2017). A neurocomputational model of the N400 and the P600 in language processing. Cognitive Science 41 1, 1318–1352. DOI logoGoogle Scholar
Brouwer, H., Fitz, H. & Hoeks, J. (2012). Getting real about semantic illusions: Rethinking the functional role of the P600 in language comprehension. Brain Research 1446 1, 127–143. DOI logoGoogle Scholar
Bühler, H. (1986). Linguistic (semantic) and extra-linguistic (pragmatic) criteria for the evaluation of conference interpretation and interpreters. Multilingua, 5 (4), 231–235.Google Scholar
Chan, S. (2019). An elephant needs a head but a horse does not: An ERP study of classifier-noun agreement in Mandarin. Journal of Neurolinguistics 52 1, 100852. DOI logoGoogle Scholar
Chiaro, D. & Nocella, G. (2004). Interpreters’ perception of linguistic and non-linguistic factors affecting quality: A survey through the world wide web. Meta 49 (2), 278–293. DOI logoGoogle Scholar
Collart, A. & Chan, S. (2021). Processing past time reference in a tenseless language: An ERP study on the Mandarin aspectual morphemes -le and -guo. Journal of Neurolinguistics 59 1, 100998. DOI logoGoogle Scholar
Davenport, T. & Coulson, S. (2011). Predictability and novelty in literal language comprehension: An ERP study. Brain Research 14181, 70–82. DOI logoGoogle Scholar
Delogu, F., Brouwer, H. & Crocker, M. W. (2019). Event-related potentials index lexical retrieval (N400) and integration (P600) during language comprehension. Brain and Cognition 135 1, 103569. DOI logoGoogle Scholar
Delogu, F., Drenhaus, H. & Crocker, M. W. (2018). On the predictability of event boundaries in discourse: An ERP investigation. Memory & Cognition 46 (2), 315–325. DOI logoGoogle Scholar
DeLong, K. A. & Kutas, M. (2020). Comprehending surprising sentences: Sensitivity of post-N400 positivities to contextual congruity and semantic relatedness. Language, Cognition and Neuroscience. DOI logoGoogle Scholar
DeLong, K. A., Urbach, T. P., Groppe, D. M. & Kutas, M. (2011). Overlapping dual ERP responses to low cloze probability sentence continuations.Psychophysiology 48 (9), 1203–1207. DOI logoGoogle Scholar
Delorme, A. & Makeig, S. (2004). EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods 134 (1), 9–21. DOI logoGoogle Scholar
Dijkstra, T. & van Heuven, W. J. B. (2002). The architecture of the bilingual word recognition system: From identification to decision. Bilingualism: Language and Cognition 5 (3), 175–197. DOI logoGoogle Scholar
Elmer, S., Meyer, M. & Jäncke, L. (2010). Simultaneous interpreters as a model for neuronal adaptation in the domain of language processing. Brain Research 1317 1, 147–156. DOI logoGoogle Scholar
Federmeier, K. D. & Kutas, M. (1999). A rose by any other name: Long-term memory structure and sentence processing. Journal of Memory and Language 41 1, 469–495. DOI logoGoogle Scholar
Federmeier, K. D., Kutas, M. & Dickson, D. S. (2016). A common neural progression to meaning in about a third of a second. In G. Hickok & S. L. Small (Eds.), Neurobiology of language. New York: Academic Press, 557–567. DOI logoGoogle Scholar
Federmeier, K. D., Wlotko, E. W., De Ochoa-Dewald, E. & Kutas, M. (2007). Multiple effects of sentential constraint on word processing. Brain Research 1146 1, 75–84. DOI logoGoogle Scholar
Friederici, A. D. (2002). Towards a neural basis of auditory sentence processing. Trends in Cognitive Sciences 6 (2), 78–84. DOI logoGoogle Scholar
(2011). The brain basis of language processing: From structure to function. Physiological Reviews 91 (4), 1357–1392. DOI logoGoogle Scholar
Gile, D. (2009). Basic concepts and models for interpreter and translator training. Amsterdam: John Benjamins. DOI logoGoogle Scholar
Hagoort, P. (2003). How the brain solves the binding problem for language: A neurocomputational model of syntactic processing. Neuroimage 20 1(Supplement 1), S18–S29. DOI logoGoogle Scholar
Hodzik, E. & Williams, J. N. (2017). Predictive processes during simultaneous interpreting from German into English. Interpreting 19 (1), 1–20. DOI logoGoogle Scholar
Jung, T.-P., Makeig, S., Westerfield, M., Townsend, J., Courchesne, E. & Sejnowski, T. J. (2000). Removal of eye artifacts from visual event-related potentials in normal and clinical subjects. Clinical Neurophysiology 111 1, 1745–1758. DOI logoGoogle Scholar
Kolk, H. & Chwilla, D. (2007). Late positivities in unusual situations. Brain and Language 100 (3), 257–261. DOI logoGoogle Scholar
Kuperberg, G. R. (2007). Neural mechanisms of language comprehension: Challenges to syntax. Brain Research 1146 1, 23–49. DOI logoGoogle Scholar
Kuperberg, G. R., Paczynski, M. & Ditman, T. (2011). Establishing causal coherence across sentences: An ERP study. Journal of Cognitive Neuroscience 23 (5), 1230–1246. DOI logoGoogle Scholar
Kutas, M. & Federmeier, K. D. (2000). Electrophysiology reveals semantic memory use in language comprehension. Trends in Cognitive Sciences 4 (12), 463–470. DOI logoGoogle Scholar
(2009). N400. Scholarpedia 4 (10), 7790. DOI logoGoogle Scholar
(2011). Thirty years and counting: Finding meaning in the N400 component of the event-related brain potential (ERP). Annual Review of Psychology 62 1, 621–647. DOI logoGoogle Scholar
Kutas, M. & Hillyard, S. A. (1980). Reading senseless sentences: Brain potentials reflect semantic incongruity. Science 207 (4427), 203–205. DOI logoGoogle Scholar
(1984). Brain potentials during reading reflect word expectancy and semantic association. Nature 307 (5947), 161–163. DOI logoGoogle Scholar
Landauer, T., Foltz, P. W. & Laham, D. (1998). An introduction to latent semantic analysis. Discourses Processes 25 (2&3), 259–284. DOI logoGoogle Scholar
Lee, T.-H. (2002). Ear voice span in English into Korean simultaneous interpretation. Meta 47 (4), 596–606. DOI logoGoogle Scholar
Lenth, R. (2020). EMMEANS: Estimated Marginal Means, aka Least-Squares Means. R package version 1.4.8. [URL]
Liao, C.-H. & Chan, S.-H. (2016). Direction matters: Event-related brain potentials reflect extra processing costs in switching from the dominant to the less dominant language. Journal of Neurolinguistics 40 1, 79–97. DOI logoGoogle Scholar
Liu, M. (2008). How do experts interpret? Implications from research in interpreting studies and cognitive science. In G. Hansen, A. Chesterman & H. Gerzymisch-Arbogast (Eds.), Efforts and models in interpreting and translation research: A tribute to Daniel Gile. Amsterdam: John Benjamins, 159–177.Google Scholar
Lopez-Calderon, J. & Luck, S. J. (2014). ERPLAB: An open-source toolbox for the analysis of event-related potentials. Frontiers in Human Neuroscience 81. DOI logoGoogle Scholar
Luck, S. J. (2014). An introduction to the event-related potential technique (2nd ed.). Cambridge, MA: MIT Press.Google Scholar
MathWorks (2005). MATLAB: The language of technical computing: Desktop tools and development environment, version 7. Natick, MA: The MathWorks.Google Scholar
Morales, J., Padilla, F., Gómez-Ariza, C. J. & Bajo, M. T. (2015). Simultaneous interpretation selectively influences working memory and attentional networks. Acta Psychologica 1551, 82–91. DOI logoGoogle Scholar
Moreno, E. M., Federmeier, K. D. & Kutas, M. (2002). Switching languages, switching palabras (words): An electrophysiological study of code switching. Brain and Language 80 (2), 188–207. DOI logoGoogle Scholar
Ness, T. & Meltzer-Asscher, A. (2018). Lexical inhibition due to failed prediction: Behavioral evidence and ERP correlates. Journal of Experimental Psychology: Learning, Memory, and Cognition 44 (8), 1269–1285. DOI logoGoogle Scholar
Oldfield, R. C. (1971). The assessment and analysis of handedness: The Edinburgh inventory. Neuropsychologia 9 (1), 97–113. DOI logoGoogle Scholar
Osterhout, L. & Holcomb, P. J. (1992). Event-related potentials elicited by syntactic anomaly. Journal of Memory and Language 311, 785–806. DOI logoGoogle Scholar
Pires, L., Leitão, J., Guerrini, C. & Simões, M. R. (2014). Event-related brain potentials in the study of inhibition: Cognitive control, source localization and age-related modulations. Neuropsychology Review 24 (4), 461–490. DOI logoGoogle Scholar
Proverbio, A. M., Leoni, G. & Zani, A. (2004). Language switching mechanisms in simultaneous interpreters: An ERP study. Neuropsychologia 42 (12), 1636–1656. DOI logoGoogle Scholar
R Core Team (2018). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. URL [URL]
Singmann, H., Bolker, B., Westfall, J., Aust, F. & Ben-Shachar, M. S. (2020). afex: Analysis of Factorial Experiments. R package version 0.28-0. [URL]
Tanner, D., Morgan-Short, K. & Luck, S. J. (2015). How inappropriate high-pass filters can produce artifactual effects and incorrect conclusions in ERP studies of language and cognition. Psychophysiology 52 (8), 997–1009. DOI logoGoogle Scholar
Taylor, W. L. (1953). Cloze procedure: A new tool for measuring readability. Journalism Quarterly 30 1, 415–433. DOI logoGoogle Scholar
Van der Meij, M., Cuetos, F., Carreiras, M. & Barber, H. A. (2011). Electrophysiological correlates of language switching in second language learners. Psychophysiology 48 (1), 44–54. DOI logoGoogle Scholar
Van Heuven, W. J. B. & Dijkstra, T. (2010). Language comprehension in the bilingual brain: fMRI and ERP support for psycholinguistic models. Brain Research Reviews 64 (1), 104–122. DOI logoGoogle Scholar
Van Petten, C. & Luka, B. J. (2006). Neural localization of semantic context effects in electromagnetic and hemodynamic studies. Brain and Language 97 (3), 279–293. DOI logoGoogle Scholar
(2012). Prediction during language comprehension: benefits, costs, and ERP components. International Journal of Psychophysiology 83 (2), 176–190. DOI logoGoogle Scholar
Wittenberg, E., Paczynski, M., Wiese, H., Jackendoff, R. & Kuperberg, G. (2014). The difference between “giving a rose” and “giving a kiss”: Sustained neural activity to the light verb construction. Journal of Memory and Language 73 1, 31–42. DOI logoGoogle Scholar
Xiang, M. & Kuperberg, G. (2015). Reversing expectations during discourse comprehension. Language, Cognition, and Neuroscience 30 (6), 648–672. DOI logoGoogle Scholar
Yang, C., Perfetti, C. A. & Liu, Y. (2010). Sentence integration processes: An ERP study of Chinese sentence comprehension with relative clauses. Brain & Language 112 1, 85–100. DOI logoGoogle Scholar
Zhang, Y., Zhang, J. & Min, B. (2012). Neural dynamics of animacy processing in language comprehension: ERP evidence from the interpretation of classifier–noun combinations. Brain and Language 120 (3), 321–331. DOI logoGoogle Scholar
Cited by (3)

Cited by three other publications

Amos, Rhona M., Kilian G. Seeber & Martin J. Pickering
2023. Student interpreters predict meaning while simultaneously interpreting - even before training. Interpreting. International Journal of Research and Practice in Interpreting 25:2 ► pp. 211 ff. DOI logo
Hodzik, Ena
2023. Predictive processes in interpreters. Translation, Cognition & Behavior 6:2 ► pp. 141 ff. DOI logo
Özkan, Deniz, Ena Hodzik & Ebru Diriker
2023. Simultaneous interpreting experience enhances the use of case markers for prediction in Turkish. Interpreting. International Journal of Research and Practice in Interpreting 25:2 ► pp. 186 ff. DOI logo

This list is based on CrossRef data as of 4 july 2024. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.