1887
Volume 24, Issue 1
  • ISSN 1384-6647
  • E-ISSN: 1569-982X
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Abstract

Abstract

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.

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2021-11-16
2024-03-28
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References

  1. Brothers, T. , Swaab, T. Y. & Traxler, M. J.
    (2017) Goals and strategies influence lexical prediction during sentence comprehension. Journal of Memory and Language93, 203–216. 10.1016/j.jml.2016.10.002
    https://doi.org/10.1016/j.jml.2016.10.002 [Google Scholar]
  2. 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 Language1(1), 135–160. 10.1162/nol_a_00006
    https://doi.org/10.1162/nol_a_00006 [Google Scholar]
  3. Brouwer, H. & Crocker, M. W.
    (2017) On the proper treatment of the N400 and P600 in language comprehension. Frontiers in Psychology8(1327). 10.3389/fpsyg.2017.01327
    https://doi.org/10.3389/fpsyg.2017.01327 [Google Scholar]
  4. 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 Science41, 1318–1352. 10.1111/cogs.12461
    https://doi.org/10.1111/cogs.12461 [Google Scholar]
  5. Brouwer, H. , Fitz, H. & Hoeks, J.
    (2012) Getting real about semantic illusions: Rethinking the functional role of the P600 in language comprehension. Brain Research1446, 127–143. 10.1016/j.brainres.2012.01.055
    https://doi.org/10.1016/j.brainres.2012.01.055 [Google Scholar]
  6. 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]
  7. Chan, S.
    (2019) An elephant needs a head but a horse does not: An ERP study of classifier-noun agreement in Mandarin. Journal of Neurolinguistics52, 100852. 10.1016/j.jneuroling.2019.100852
    https://doi.org/10.1016/j.jneuroling.2019.100852 [Google Scholar]
  8. Chernov, G. V.
    (2004) Inference and anticipation in simultaneous interpreting: A probability-prediction model. Amsterdam: John Benjamins. 10.1075/btl.57
    https://doi.org/10.1075/btl.57 [Google Scholar]
  9. Chiaro, D. & Nocella, G.
    (2004) Interpreters’ perception of linguistic and non-linguistic factors affecting quality: A survey through the world wide web. Meta49(2), 278–293. 10.7202/009351ar
    https://doi.org/10.7202/009351ar [Google Scholar]
  10. Chmiel, A.
    (2021) Effects of simultaneous interpreting experience and training on anticipation, as measured by word-translation latencies. Interpreting23(1), 18–44. 10.1075/intp.00048.chm
    https://doi.org/10.1075/intp.00048.chm [Google Scholar]
  11. 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 Neurolinguistics59, 100998. 10.1016/j.jneuroling.2021.100998
    https://doi.org/10.1016/j.jneuroling.2021.100998 [Google Scholar]
  12. Davenport, T. & Coulson, S.
    (2011) Predictability and novelty in literal language comprehension: An ERP study. Brain Research1418, 70–82. 10.1016/j.brainres.2011.07.039
    https://doi.org/10.1016/j.brainres.2011.07.039 [Google Scholar]
  13. Delogu, F. , Brouwer, H. & Crocker, M. W.
    (2019) Event-related potentials index lexical retrieval (N400) and integration (P600) during language comprehension. Brain and Cognition135, 103569. 10.1016/j.bandc.2019.05.007
    https://doi.org/10.1016/j.bandc.2019.05.007 [Google Scholar]
  14. Delogu, F. , Drenhaus, H. & Crocker, M. W.
    (2018) On the predictability of event boundaries in discourse: An ERP investigation. Memory & Cognition46(2), 315–325. 10.3758/s13421‑017‑0766‑4
    https://doi.org/10.3758/s13421-017-0766-4 [Google Scholar]
  15. DeLong, K. A. & Kutas, M.
    (2020) Comprehending surprising sentences: Sensitivity of post-N400 positivities to contextual congruity and semantic relatedness. Language, Cognition and Neuroscience. 10.1080/23273798.2019.1708960
    https://doi.org/10.1080/23273798.2019.1708960 [Google Scholar]
  16. DeLong, K. A. , Urbach, T. P. , Groppe, D. M. & Kutas, M.
    (2011) Overlapping dual ERP responses to low cloze probability sentence continuations. Psychophysiology48 (9), 1203–1207. 10.1111/j.1469‑8986.2011.01199.x
    https://doi.org/10.1111/j.1469-8986.2011.01199.x [Google Scholar]
  17. Delorme, A. & Makeig, S.
    (2004) EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods134(1), 9–21. 10.1016/j.jneumeth.2003.10.009
    https://doi.org/10.1016/j.jneumeth.2003.10.009 [Google Scholar]
  18. Dijkstra, T. & van Heuven, W. J. B.
    (2002) The architecture of the bilingual word recognition system: From identification to decision. Bilingualism: Language and Cognition5(3), 175–197. 10.1017/S1366728902003012
    https://doi.org/10.1017/S1366728902003012 [Google Scholar]
  19. Elmer, S. , Meyer, M. & Jäncke, L.
    (2010) Simultaneous interpreters as a model for neuronal adaptation in the domain of language processing. Brain Research1317, 147–156. 10.1016/j.brainres.2009.12.052
    https://doi.org/10.1016/j.brainres.2009.12.052 [Google Scholar]
  20. Federmeier, K. D. & Kutas, M.
    (1999) A rose by any other name: Long-term memory structure and sentence processing. Journal of Memory and Language41, 469–495. 10.1006/jmla.1999.2660
    https://doi.org/10.1006/jmla.1999.2660 [Google Scholar]
  21. 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. 10.1016/B978‑0‑12‑407794‑2.00045‑6
    https://doi.org/10.1016/B978-0-12-407794-2.00045-6 [Google Scholar]
  22. Federmeier, K. D. , Wlotko, E. W. , De Ochoa-Dewald, E. & Kutas, M.
    (2007) Multiple effects of sentential constraint on word processing. Brain Research1146, 75–84. 10.1016/j.brainres.2006.06.101
    https://doi.org/10.1016/j.brainres.2006.06.101 [Google Scholar]
  23. Friederici, A. D.
    (2002) Towards a neural basis of auditory sentence processing. Trends in Cognitive Sciences6(2), 78–84. 10.1016/S1364‑6613(00)01839‑8
    https://doi.org/10.1016/S1364-6613(00)01839-8 [Google Scholar]
  24. (2011) The brain basis of language processing: From structure to function. Physiological Reviews91(4), 1357–1392. 10.1152/physrev.00006.2011
    https://doi.org/10.1152/physrev.00006.2011 [Google Scholar]
  25. Gile, D.
    (2009) Basic concepts and models for interpreter and translator training. Amsterdam: John Benjamins. 10.1075/btl.8
    https://doi.org/10.1075/btl.8 [Google Scholar]
  26. Hagoort, P.
    (2003) How the brain solves the binding problem for language: A neurocomputational model of syntactic processing. Neuroimage20(Supplement 1), S18–S29. 10.1016/j.neuroimage.2003.09.013
    https://doi.org/10.1016/j.neuroimage.2003.09.013 [Google Scholar]
  27. Hodzik, E. & Williams, J. N.
    (2017) Predictive processes during simultaneous interpreting from German into English. Interpreting19(1), 1–20. 10.1075/intp.19.1.01hod
    https://doi.org/10.1075/intp.19.1.01hod [Google Scholar]
  28. 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 Neurophysiology111, 1745–1758. 10.1016/S1388‑2457(00)00386‑2
    https://doi.org/10.1016/S1388-2457(00)00386-2 [Google Scholar]
  29. Kolk, H. & Chwilla, D.
    (2007) Late positivities in unusual situations. Brain and Language100(3), 257–261. 10.1016/j.bandl.2006.07.006
    https://doi.org/10.1016/j.bandl.2006.07.006 [Google Scholar]
  30. Kuperberg, G. R.
    (2007) Neural mechanisms of language comprehension: Challenges to syntax. Brain Research1146, 23–49. 10.1016/j.brainres.2006.12.063
    https://doi.org/10.1016/j.brainres.2006.12.063 [Google Scholar]
  31. Kuperberg, G. R. , Paczynski, M. & Ditman, T.
    (2011) Establishing causal coherence across sentences: An ERP study. Journal of Cognitive Neuroscience23(5), 1230–1246. 10.1162/jocn.2010.21452
    https://doi.org/10.1162/jocn.2010.21452 [Google Scholar]
  32. Kutas, M. & Federmeier, K. D.
    (2000) Electrophysiology reveals semantic memory use in language comprehension. Trends in Cognitive Sciences4(12), 463–470. 10.1016/S1364‑6613(00)01560‑6
    https://doi.org/10.1016/S1364-6613(00)01560-6 [Google Scholar]
  33. (2009) N400. Scholarpedia4(10), 7790. 10.4249/scholarpedia.7790
    https://doi.org/10.4249/scholarpedia.7790 [Google Scholar]
  34. (2011) Thirty years and counting: Finding meaning in the N400 component of the event-related brain potential (ERP). Annual Review of Psychology62, 621–647. 10.1146/annurev.psych.093008.131123
    https://doi.org/10.1146/annurev.psych.093008.131123 [Google Scholar]
  35. Kutas, M. & Hillyard, S. A.
    (1980) Reading senseless sentences: Brain potentials reflect semantic incongruity. Science207(4427), 203–205. 10.1126/science.7350657
    https://doi.org/10.1126/science.7350657 [Google Scholar]
  36. (1984) Brain potentials during reading reflect word expectancy and semantic association. Nature307(5947), 161–163. 10.1038/307161a0
    https://doi.org/10.1038/307161a0 [Google Scholar]
  37. Landauer, T. , Foltz, P. W. & Laham, D.
    (1998) An introduction to latent semantic analysis. Discourses Processes25(2&3), 259–284. 10.1080/01638539809545028
    https://doi.org/10.1080/01638539809545028 [Google Scholar]
  38. Lee, T.-H.
    (2002) Ear voice span in English into Korean simultaneous interpretation. Meta47(4), 596–606. 10.7202/008039ar
    https://doi.org/10.7202/008039ar [Google Scholar]
  39. Lenth, R.
    (2020) EMMEANS: Estimated Marginal Means, aka Least-Squares Means. R package version 1.4.8. https://CRAN.R-project.org/package=emmeans
  40. 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 Neurolinguistics40, 79–97. 10.1016/j.jneuroling.2016.06.004
    https://doi.org/10.1016/j.jneuroling.2016.06.004 [Google Scholar]
  41. 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]
  42. Lopez-Calderon, J. & Luck, S. J.
    (2014) ERPLAB: An open-source toolbox for the analysis of event-related potentials. Frontiers in Human Neuroscience8. 10.3389/fnhum.2014.00213
    https://doi.org/10.3389/fnhum.2014.00213 [Google Scholar]
  43. Luck, S. J.
    (2014) An introduction to the event-related potential technique (2nd ed.). Cambridge, MA: MIT Press.
    [Google Scholar]
  44. MathWorks
    MathWorks (2005) MATLAB: The language of technical computing: Desktop tools and development environment, version 7. Natick, MA: The MathWorks.
    [Google Scholar]
  45. Morales, J. , Padilla, F. , Gómez-Ariza, C. J. & Bajo, M. T.
    (2015) Simultaneous interpretation selectively influences working memory and attentional networks. Acta Psychologica155, 82–91. 10.1016/j.actpsy.2014.12.004
    https://doi.org/10.1016/j.actpsy.2014.12.004 [Google Scholar]
  46. Moreno, E. M. , Federmeier, K. D. & Kutas, M.
    (2002) Switching languages, switching palabras (words): An electrophysiological study of code switching. Brain and Language80(2), 188–207. 10.1006/brln.2001.2588
    https://doi.org/10.1006/brln.2001.2588 [Google Scholar]
  47. Ness, T. & Meltzer-Asscher, A.
    (2018) Lexical inhibition due to failed prediction: Behavioral evidence and ERP correlates. Journal of Experimental Psychology: Learning, Memory, and Cognition44(8), 1269–1285. 10.1037/xlm0000525
    https://doi.org/10.1037/xlm0000525 [Google Scholar]
  48. Oldfield, R. C.
    (1971) The assessment and analysis of handedness: The Edinburgh inventory. Neuropsychologia9(1), 97–113. 10.1016/0028‑3932(71)90067‑4
    https://doi.org/10.1016/0028-3932(71)90067-4 [Google Scholar]
  49. Osterhout, L. & Holcomb, P. J.
    (1992) Event-related potentials elicited by syntactic anomaly. Journal of Memory and Language31, 785–806. 10.1016/0749‑596X(92)90039‑Z
    https://doi.org/10.1016/0749-596X(92)90039-Z [Google Scholar]
  50. 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 Review24(4), 461–490. 10.1007/s11065‑014‑9275‑4
    https://doi.org/10.1007/s11065-014-9275-4 [Google Scholar]
  51. Proverbio, A. M. , Leoni, G. & Zani, A.
    (2004) Language switching mechanisms in simultaneous interpreters: An ERP study. Neuropsychologia42(12), 1636–1656. 10.1016/j.neuropsychologia.2004.04.013
    https://doi.org/10.1016/j.neuropsychologia.2004.04.013 [Google Scholar]
  52. R Core Team
    R Core Team (2018) R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. URLhttps://www.R-project.org/
    [Google Scholar]
  53. Singmann, H. , Bolker, B. , Westfall, J. , Aust, F. & Ben-Shachar, M. S.
    (2020) afex: Analysis of Factorial Experiments. R package version 0.28-0. https://CRAN.R-project.org/package=afex
  54. 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. Psychophysiology52(8), 997–1009. 10.1111/psyp.12437
    https://doi.org/10.1111/psyp.12437 [Google Scholar]
  55. Taylor, W. L.
    (1953) Cloze procedure: A new tool for measuring readability. Journalism Quarterly30, 415–433. 10.1177/107769905303000401
    https://doi.org/10.1177/107769905303000401 [Google Scholar]
  56. Van der Meij, M. , Cuetos, F. , Carreiras, M. & Barber, H. A.
    (2011) Electrophysiological correlates of language switching in second language learners. Psychophysiology48(1), 44–54. 10.1111/j.1469‑8986.2010.01039.x
    https://doi.org/10.1111/j.1469-8986.2010.01039.x [Google Scholar]
  57. Van Heuven, W. J. B. & Dijkstra, T.
    (2010) Language comprehension in the bilingual brain: fMRI and ERP support for psycholinguistic models. Brain Research Reviews64(1), 104–122. 10.1016/j.brainresrev.2010.03.002
    https://doi.org/10.1016/j.brainresrev.2010.03.002 [Google Scholar]
  58. Van Petten, C. & Luka, B. J.
    (2006) Neural localization of semantic context effects in electromagnetic and hemodynamic studies. Brain and Language97(3), 279–293. 10.1016/j.bandl.2005.11.003
    https://doi.org/10.1016/j.bandl.2005.11.003 [Google Scholar]
  59. (2012) Prediction during language comprehension: benefits, costs, and ERP components. International Journal of Psychophysiology83(2), 176–190. 10.1016/j.ijpsycho.2011.09.015
    https://doi.org/10.1016/j.ijpsycho.2011.09.015 [Google Scholar]
  60. 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 Language73, 31–42. 10.1016/j.jml.2014.02.002
    https://doi.org/10.1016/j.jml.2014.02.002 [Google Scholar]
  61. Xiang, M. & Kuperberg, G.
    (2015) Reversing expectations during discourse comprehension. Language, Cognition, and Neuroscience30(6), 648–672. 10.1080/23273798.2014.995679
    https://doi.org/10.1080/23273798.2014.995679 [Google Scholar]
  62. Yang, C. , Perfetti, C. A. & Liu, Y.
    (2010) Sentence integration processes: An ERP study of Chinese sentence comprehension with relative clauses. Brain & Language112, 85–100. 10.1016/j.bandl.2009.10.005
    https://doi.org/10.1016/j.bandl.2009.10.005 [Google Scholar]
  63. 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 Language120(3), 321–331. 10.1016/j.bandl.2011.10.007
    https://doi.org/10.1016/j.bandl.2011.10.007 [Google Scholar]
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  • Article Type: Research Article
Keyword(s): interpreting expertise; language switching; N400; PNP
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