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An examination of L2-L1 noncognate translation priming in the lexical decision task: insights from distributional and frequency-based analyses

Published online by Cambridge University Press:  02 February 2017

MARIKO NAKAYAMA*
Affiliation:
Faculty of Arts, Letters and Sciences, Waseda University Department of Psychology, Rikkyo University
STEPHEN J. LUPKER
Affiliation:
Department of Psychology, University of Western Ontario
YOSHIHIRO ITAGUCHI
Affiliation:
School of Health Sciences, Sapporo Medical University
*
Address for correspondence: Mariko Nakayama, Department of Psychology, Rikkyo University, 1-2-26 Kitano, Niza, Saitama, Japan352-0003mariko_nakayama@rikkyo.ac.jp

Abstract

The main fact that is currently known about the nature of masked L2-L1 noncognate translation priming effects in the lexical decision task is simply that those effects are significant in some studies but not in others. In an effort to better understand these effects, we examined the data pattern for very proficient Japanese–English bilinguals using RT distributional analyses. We also examined the impacts of prime and target frequency on the priming effect. Significant priming was present even on the fastest trials, becoming larger on slower trials. Nonetheless, priming effects were generally constant across prime and target frequency with the only exception being when very high frequency L2 primes were used. In that situation, priming and target frequency were negatively related, a result that essentially produced the observed pattern of increasing priming on slower trials. Implications of these results and potential reasons for the presence/absence of L2-L1 priming effects are discussed.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2017 

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Footnotes

This research was supported by a grant from the Japan Society for the Promotion of Science (JSPS) to Mariko Nakayama.

References

Amano, N., & Kondo, H. (2003). NTT database series: Lexical characteristics of Japanese language (version 2). Tokyo: Sanseido. [CD-ROM]Google Scholar
Balota, D. A., & Yap, M. J. (2011). Moving beyond the mean in studies of mental chronometry: The power of response time distributional analyses. Current Directions in Psychological Science, 20, 160166.CrossRefGoogle Scholar
Balota, D. A., Aschenbrenner, A. J., & Yap, M. J. (2013). Additive effects of word frequency and stimulus quality: The influence of trial history and data transformations. Journal of Experimental Psychology: Learning, Memory and Cognition, 39, 15631571.Google Scholar
Balota, D. A., Yap, M. J., Cortese, M. J., & Watson, J. M. (2008). Beyond mean response latency: Response time distributional analysis of semantic priming. Journal of Memory and Language, 59, 495523.Google Scholar
Bates, D., Maechler, M., Bolker, B., & Walker, S. (2015). lme4: Linear mixed-effects models using Eigen and S4. https://CRAN.R-project.org/package=lme4.Google Scholar
Brainard, D. H. (1997). The Psychophysics Toolbox, Spatial Vision, 10, 443446.CrossRefGoogle ScholarPubMed
Brysbaert, M., & New, B. (2009). Moving beyond Kučera and Francis: A critical evaluation of current word frequency norms and the introduction of a new and improved word frequency measure for American English. Behavior Research Methods, 41, 977990.Google Scholar
Brysbaert, M., Warriner, A. B., & Kuperman, V. (2014). Concreteness ratings for 40 thousand generally known English word lemmas. Behavior Research Methods, 46, 904911.Google Scholar
Cousineau, D., Brown, S. D., & Heathcote, A. (2004). Fitting distributions using maximum likelihood: Methods and packages. Behavior Research Methods, Instruments, & Computers, 36, 742756.Google Scholar
Dijkstra, A., & Van Heuven, W. J. B. (2002). The architecture of the bilingual word recognition system: From identification to decision. Bilingualism: Language and Cognition, 5, 175197.Google Scholar
Dimitropoulou, M., Duñabeitia, J. A., & Carreiras, M. (2011a). Masked translation priming effects with low-proficient bilinguals. Memory & Cognition, 39, 260275.Google Scholar
Dimitropoulou, M., Duñabeitia, J. A., & Carreiras, M. (2011b). Two words, one meaning: Evidence of automatic co-activation of translation equivalents. Frontiers in Psychology, 2, 188. http://doi.org/10.3389/fpsyg.2011.00188 Google Scholar
Duyck, W., & Warlop, N. (2009). Translation priming between the native language and a second language. New evidence from Dutch-French Bilinguals. Experimental Psychology, 56, 173189.Google Scholar
Finkbeiner, M., Forster, K. I., Nicol, J., & Nakamura, K. (2004). The role of polysemy in masked semantic and translation priming. Journal of Memory and Language, 51, 122.Google Scholar
Forster, K. I. (2013). How many words can we read at once? More intervenor effects in masked priming. Journal of Memory and Language, 69, 563573.CrossRefGoogle Scholar
Gollan, T. H., Forster, K. I., & Frost, R. (1997). Translation priming with different scripts: Masked priming with cognates and noncognates in Hebrew-English bilinguals. Journal of Experimental Psychology: Learning, Memory, and Cognition, 23, 11221139.Google ScholarPubMed
Gomez, P., Perea, M., & Ratcliff, R. (2013). A diffusion model account of masked vs. unmasked priming: Are they qualitatively different? Journal of Experimental Psychology: Human Perception and Performance, 39, 17311740.Google Scholar
Grainger, J., & Frenck-Mestre, C. (1998). Masked priming by translation equivalents in proficient bilinguals. Language and Cognitive Processes, 13, 601623.Google Scholar
Grainger, J., Lopez, D., Eddy, M., Dufau, S., & Holcomb, P. J. (2012). How word frequency modulates masked repetition priming: An ERP investigation. Psychophysiology, 49, 604616.Google Scholar
Grossi, G. (2006). Relatedness proportion effects on masked associative priming: An ERP study. Psychophysiology, 43, 2130.Google Scholar
Hauk, O., Davis, M. H., Ford, M., Pulvermüller, F., & Marslen-Wilson, W. D. (2006). The time course of visual word recognition as revealed by linear regression analysis of ERP data. Neuroimage, 30, 13831400.Google Scholar
Heathcote, A., Brown, S., & Mewhort, D. J. K. (2002). Quantile maximum likelihood estimation of response time distributions. Psychonomics Bulletin & Review, 9, 394401.Google Scholar
Heathcote, A., Popiel, S. J., & Mewhort, D. J. K. (1991). Analysis of response time distributions: An example using the Stroop Task. Psychological Bulletin, 109, 340347.Google Scholar
Hoshino, N., Midgley, K. J., Holcomb, P. J., & Grainger, J. (2010). An ERP investigation of masked cross-script translation priming. Brain Research, 1344, 159172.Google Scholar
Jiang, N. (1999). Testing processing explanations for the asymmetry in masked cross-language priming. Bilingualism: Language and Cognition, 2, 5975.Google Scholar
Jiang, N., & Forster, K. I. (2001). Cross-language priming asymmetries in lexical decision and episodic recognition. Journal of Memory and Language, 44, 3251.Google Scholar
Kim, J., & Davis, C. (2003). Task effects in masked cross-script translation and phonological priming. Journal of Memory and Language, 49, 484499.CrossRefGoogle Scholar
Kleiner, M., Brainard, D., & Pelli, D. (2007). What's new in Psychtoolbox-3? Perception, 36, ECVP Abstract Supplement.Google Scholar
Kuperman, V., Bertram, R., & Baayen, R. H. (2008). Morphological dynamics in compound processing. Language and Cognitive Processes, 23, 10891132.Google Scholar
Kuznetsova, A., Brockhoff, P. B., & Christensen, R. H. B. (2014). lmerTest: Tests for random and fixed effects for linear mixed effect models (lmer objects of lme4 package) https://cran.r-project.org/web/packages/lmerTest/index.html Google Scholar
Lemhöfer, K., Dijkstra, T., Schriefers, H., Baayen, R.H., Grainger, J., & Zwitserlood, P. (2008). Native language influences on word recognition in a second language: a megastudy. Journal of Experimental Psychology: Learning, Memory, and Cognition, 34, 1231 Google Scholar
Lo, S., & Andrews, S. (2015). To transform or not to transform: Using generalized linear mixed models to analyse reaction time data. Frontiers in Psychology, 6, 1171. doi: http://dx.doi.org/10.3389/fpsyg.2015.01171 Google Scholar
Madec, S., Rey, A., Dufau, S., Klein, M., & Grainger, J. (2012). The time course of visual letter perception. Journal of Cognitive Neuroscience, 24, 16451655.Google Scholar
Masson, M. E. J., & Kliegl, R. (2013). Modulation of additive and interactive effects in lexical decision by trial history. Journal of Experimental Psychology: Learning, Memory, and Cognition, 39, 898914.Google Scholar
Miwa, K., Dijkstra, T., Bolger, P., & Baayen, R. H. (2014). Reading English with Japanese in mind: Effects of frequency, phonology, and meaning in different-script bilinguals. Bilingualism: Language and Cognition, 17, 445463.Google Scholar
Nakayama, M., Ida, K., & Lupker (2016). Cross-script L2-L1 noncognate translation priming in lexical decision depends on L2 proficiency: Evidence from Japanese–English bilinguals. Bilingualism: Language & Cognition, 19, 10011022.CrossRefGoogle Scholar
Nakayama, M., Sears, C.R., Hino, Y., & Lupker, S.J. (2013). Masked translation priming with Japanese–English bilinguals: Interactions between cognate status, target frequency, and L2 proficiency. Journal of Cognitive Psychology, 25, 949981.Google Scholar
Pelli, D. G. (1997) The VideoToolbox software for visual psychophysics: Transforming numbers into movies. Spatial Vision, 10, 437442.Google Scholar
Perea, M., & Rosa, E. (2002). The effects of associative and semantic priming in the lexical decision task. Psychological Research, 66, 180194.Google Scholar
Pylkkänen, L., & Marantz, A. (2003). Tracking the time course of word recognition with MEG. Trends in Cognitive Sciences, 7, 187189.Google Scholar
Rouder, J. N., Lu, J., Speckman, P., Sun, D., & Jiang, Y. (2005). A hierarchical model for estimating response time distributions. Psychonomic Bulletin & Review, 12, 195223.Google Scholar
Schoonbaert, S., Duyck, W., Brysbaert, M., & Hartsuiker, R. J. (2009). Semantic and translation priming from a first language to a second and back: Making sense of the findings. Memory & Cognition, 37, 569586.CrossRefGoogle ScholarPubMed
Tokowicz, N., Kroll, J. F., de Groot, A. M. B., & van Hell, J. G. (2002). Number-of-translation norms for Dutch-English translation pairs: A new tool for examining language production. Behavior Research Methods, Instruments, & Computers, 34, 435451.Google Scholar
Voga, M., & Grainger, J. (2007). Cognate status and cross-script translation priming. Memory & Cognition, 35, 938952.Google Scholar
Wang, X., & Forster, K. I. (2010). Masked translation priming with semantic categorization: Testing the Sense Model. Bilingualism: Language and Cognition, 13, 327340.CrossRefGoogle Scholar
Wang, X., & Forster, K. I. (2015). Is translation priming asymmetry due to partial awareness of the prime? Bilingualism: Language and Cognition, 18, 657669.Google Scholar
White, S. J., & Staub, A. (2012). The distribution of fixation durations during reading: effects of stimulus quality. Journal of Experimental Psychology: Human Perception and Performance, 38, 603617.Google ScholarPubMed
Witzel, N. O., & Forster, K. I. (2012). How L2 words are stored: The episodic L2 Hypothesis. Journal of Experimental Psychology: Learning, Memory, and Cognition, 38, 16081621.Google Scholar
Wurm, L. H., & Fisicaro, S. A. (2014). What residualizing predictors in regression analyses does (and what it does not do). Journal of Memory and Language, 72, 3748.CrossRefGoogle Scholar
Xia, V., & Andrews, S. (2015). Masked translation priming asymmetry in Chinese–English bilinguals: Making sense of the Sense Model. The Quarterly Journal of Experimental Psychology, 68, 294325.Google Scholar