Cross-language Neighborhood Effects in Learners Indicative of an Integrated Lexicon

Meade, Gabriela; Midgley, Katherine J.; Dijkstra, Ton; Holcomb, Phillip J.

doi:10.1162/jocn_a_01184

Cited by 39 publications

(28 citation statements)

References 53 publications

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“…Participants reported having no history of neurological dysfunction or language disorders, and were not taking any medications that would affect brain function. Data from these same participants in other tasks have been reported elsewhere ( Meade et al, 2018 ). In addition to the three participants excluded from the original report, data from two additional participants were excluded here.…”

Section: Methodsmentioning

confidence: 99%

“…The average Levenshtein distance (i.e., number of insertions, deletions, and substitutions) between the L2 words and their L1 translations was 5.12 ( SD : 1.20). A full description of the L2 words can be found in Meade et al (2018) .…”

Section: Methodsmentioning

confidence: 99%

“…Participants were instructed that they would be learning words from a new language. In order to reinforce that these were words from another language, the experiment began with a language decision ERP pretest (i.e., press one button for English words and another button for words from another language; see Meade et al, 2018 ). Learning exercises were then administered over three consecutive days beginning the day of the pretest.…”

Section: Methodsmentioning

confidence: 99%

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An ERP Investigation of L2–L1 Translation Priming in Adult Learners

2018

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A longstanding debate centers around how beginning adult bilinguals process words in their second language (L2). Do they access the meaning of the L2 words directly or do they first activate the native language (L1) translation equivalents in order to access meaning? To address this question, we used ERPs to investigate how newly learned L2 words influence processing of their L1 translation equivalents. We taught participants the meanings of 80 novel L2 (pseudo)words by presenting them with pictures of familiar objects. After 3 days of learning, participants were tested in a backward translation priming paradigm with a short (140 ms) stimulus onset asynchrony. L1 targets preceded by their L2 translations elicited faster responses and smaller amplitude negativities than the same L1 targets preceded by unrelated L2 words. The bulk of the ERP translation priming effect occurred within the N400 window (350–550 ms), suggesting that the new L2 words were automatically activating their semantic representations. A weaker priming effect in the preceding window (200–350 ms) was found at anterior sites, providing some evidence that the forms of the L1 translation equivalents had also been activated. These results have implications for models of L2 processing at the earliest stages of learning.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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An ERP Investigation of L2–L1 Translation Priming in Adult Learners

2018

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“…During bilingual language processing, words from the nontarget language are activated (e.g., Costa, Caramazza, & Sebastián-Gallés, 2000;Hermans, Bongaerts, De Bot, & Schreuder, 1998;Meade, Midgley, Dijkstra, & Holcomb, 2018) and sometimes even selected by mistake (e.g., Declerck, Lemhöfer, & Grainger, 2017;Gollan, Sandoval, & Salmon, 2011;Poulisse & Bongaerts, 1994). To minimize cross-language interference, and increase the chances that words of the target language are selected, a language control process is implemented.…”

Section: Introductionmentioning

confidence: 99%

What about proactive language control?

Declerck

2019

Psychon Bull Rev

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While several reviews provide an in-depth discussion on reactive language control, which is the language control process that is initiated when the non-target language disrupts the selection of target language words, few have touched on proactive language control, which is the language control process implemented as an anticipation of any non-target language interference disrupting the selection of target language words. In the current review, three prominent markers of proactive language control are discussed (i.e., the reversed language dominance effect, language-mixing costs, and the blocked language-order effect). Based on these three markers, it appears that proactive language control can be implemented to mainly restrict interference from the first language during bilingual language production, but is typically absent during bilingual language comprehension. The literature also implies that proactive language control might be partly domain general. With respect to the underlying mechanism of proactive language control, there are some indications that proactive language control relies on inhibition, but no unequivocal evidence has been provided so far.

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“…is established quite early in second language learners (e.g., Meade, Midgley, Dijkstra, & Holcomb, 2018).…”

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confidence: 99%

On keeping cool: The role of inhibition in bilingual word processing

2018

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One of the cool aspects of the original implementation of the BIA model (van Heuven, Dijkstra & Grainger, 1998) was the discovery that inhibitory connections between language nodes and lexical representations was a necessary feature for the model to be able to simulate the target data set at that time. This demonstrates the importance of computational modeling, a key point of the present target article, since inhibitory connections were postulated to occur only between representations at the same level in the conceptual model (Grainger & Dijkstra, 1992). Top-down inhibition was subsequently dropped in the BIA+ model (Dijkstra & van Heuven, 2002), and the Multilink model of the present target article (Dijkstra, Wahl, Buytenhuijs, van Halem, Al-jibouri, de Korte & Rekké, 2018) goes one step further by removing all kinds of inhibitory connections, both between and within levels. Instead, the authors of the model propose that bilingual language processing relies on bidirectional excitatory connections between representations at different levels. This is curious given that even more evidence has accumulated in favor of inhibition since the original implementation of the BIA model, both between neighboring lexical representations (i.e., lateral inhibition) and from language membership representations (e.g., language nodes and tags) down to lexical representations. In this commentary, we focus on whether the exclusion of these two inhibitory processes is warranted, and how the inclusion of these processes might benefit future developments of the model.

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Cross-language Neighborhood Effects in Learners Indicative of an Integrated Lexicon

Cited by 39 publications

References 53 publications

An ERP Investigation of L2–L1 Translation Priming in Adult Learners

An ERP Investigation of L2–L1 Translation Priming in Adult Learners

What about proactive language control?

On keeping cool: The role of inhibition in bilingual word processing

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