Inhibitory control predicts language switching performance in trilingual speech production

Linck, Jared A.; Schwieter, John W.; Sunderman, Gretchen

doi:10.1017/s136672891100054x

Cited by 161 publications

(240 citation statements)

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“…This has generally been explained with a larger L1 activation than L2 activation. Whereas such a pattern has also been observed in several studies using mixed language blocks (e.g., de Bruin et al, 2014;Linck et al, 2012;Macizo et al, 2012), there are also studies that observed worse L1 performance than L2 performance in mixed language blocks (e.g., Christoffels et al, 2007;Costa & Santesteban, 2004;Gollan & Ferreira, 2009;Verhoef et al, 2009Verhoef et al, , 2010. Interestingly, this is only the case in production studies, while comprehension studies do not show this pattern (similar to asymmetrical switch costs).…”

Section: When L2 Outperforms L1mentioning

confidence: 58%

“…Green, 1998), one would expect faster naming of L1 words than L2 words when asymmetrical switch costs are observed. Some studies have shown exactly this pattern of faster overall L1 than L2 naming and asymmetrical switch costs (e.g., Linck et al, 2012;Macizo et al, 2012). However, there have also been studies that found faster overall L1 than L2 naming and symmetrical switch costs (e.g., Declerck, Koch, & Philipp, 2012;see also de Bruin et al, 2014).…”

Section: Asymmetrical Switch Costs As a Marker For Inhibitionmentioning

confidence: 88%

“…For example, Linck et al (2012) and Liu, Rossi, Zhou, and Chen (2014) have shown that asymmetrical switch costs are, at least partially, related to inhibition, as measured by the Simon task (Simon, 1969). Yet, there are also arguments against using asymmetrical switch costs as a marker for inhibition.…”

Section: Asymmetrical Switch Costs As a Marker For Inhibitionmentioning

confidence: 99%

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A review of control processes and their locus in language switching

2015

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Language switching has been one of the main tasks to investigate language control, a process that restricts bilingual language processing to the target language. In the current review, we discuss the How (i.e., mechanisms) and Where (i.e., locus of these mechanisms) of language control in language switching. As regards the mechanisms of language control, we describe several empirical markers of language switching and their relation to inhibition, as a potentially important mechanism of language control. From this overview it becomes apparent that some, but not all, markers indicate the occurrence of inhibition during language switching and, thus, language control. In a second part, we turn to the potential locus of language control and the role of different processing stages (concept level, lemma level, phonology, orthography, and outside language processing). Previous studies provide evidence for the employment of several of these processing stages during language control so that either a complex control mechanism involving different processing stages and/or multiple loci of language control have to be assumed. Based on the discussed results, several established and new theoretical avenues are considered.

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Section: When L2 Outperforms L1mentioning

confidence: 58%

Section: Asymmetrical Switch Costs As a Marker For Inhibitionmentioning

confidence: 88%

Section: Asymmetrical Switch Costs As a Marker For Inhibitionmentioning

confidence: 99%

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A review of control processes and their locus in language switching

2015

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“…With the exception of one participant, they all started learning English by the age of eleven and they were late bilinguals, in the sense of coming into sustained contact with native speakers only in adolescence. Expected for such a type of bilinguals is the transfer of L1 features into their L2 (Green 1998;Linck et al 2012), which, on the level of sound, results in foreign-accentedness. Interestingly, recent studies have revealed that phonetic cross-linguistic influence (including L1-to-L2 interference) can momentarily increase when a bilingual performs in the bilingual language mode (Grosjean 2008), that is, when both their languages are engaged simultaneously (for references see Sections 1.2 and 1.3).…”

Section: Introductionmentioning

confidence: 99%

Patterns of Short-Term Phonetic Interference in Bilingual Speech

Šimáčková

Podlipský

2018

Languages

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Previous research indicates that alternating between a bilingual's languages during speech production can lead to short-term increases in cross-language phonetic interaction. However, discrepancies exist between the reported L1-L2 effects in terms of direction and magnitude, and sometimes the effects are not found at all. The present study focused on L1 interference in L2, examining Voice Onset Time (VOT) of English voiceless stops produced by L1-dominant Czech-English bilinguals-interpreter trainees highly proficient in L2-English. We tested two hypotheses: (1) switching between languages induces an immediate increase in L1 interference during code-switching; and (2) due to global language co-activation, an increase in L1-to-L2 interference occurs when bilinguals interpret (translate) a message from L1 into L2 even if they do not produce L1 speech. Fourteen bilinguals uttered L2-English sentences under three conditions: L2-only, code-switching into L2, and interpreting into L2. Against expectation, the results showed that English VOT in the bilingual tasks tended to be longer and less Czech-like compared to the English-only task. This contradicts an earlier finding of L2 VOT converging temporarily towards L1 VOT values for comparable bilingual tasks performed by speakers from the same bilingual population. Participant-level inspection of our data suggests that besides language-background differences, individual language-switching strategies contribute to discrepancies between studies.

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“…The main line of research on this topic focused on individual differences in ability to hold an item in working memory, an ability that has been linked to success at text comprehension (Haarmann et al 2003), ambiguity resolution (e. g. Miyake et al 1994), low versus high attachment preference (Swets et al 2007), and foreign language learning (e. g. Baddeley et al 1998). Other lines of research focused on individual differences in inhibition, linking it to success at language acquisition (Darcy et al 2014), degree of competitor activation across and within languages (Festman et al 2010;Gollan et al 2011;Linck et al 2011;Lev-Ari and Keysar 2014;Peperkamp 2013, 2014), and success at inhibiting discourseirrelevant information in either literal (e. g. Gernsbacher and Robertson 1995;Gernsbacher et al 1990 ) or figurative language (e. g. Chiappe and Chiappe 2007;Kintsch 2001). Working memory has also been shown to influence the ability to integrate different types and sources of information online (Dagerman et al 2006;Federmeier and Kutas 2005;Just and Carpenter 1992;Madden and Zwaan 2006;Pearlmutter and McDonald 1995;Traxler et al 2005).…”

mentioning

confidence: 99%

Studying individual differences in the social environment to better understand language learning and processing

Lev‐Ari

2016

Linguistics Vanguard

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People learn language from their social environment. Therefore, individual differences in the input that their social environment provides could influence their linguistic performance. Nevertheless, investigation of the role of individual differences in input on performance has been mostly restricted to first and second language acquisition. In this paper I argue that individual differences in input can influence linguistic performance even in adult native speakers. Specifically, differences in input can affect performance by influencing people's knowledgebase, by modulating their processing manner, and by shaping expectations. Therefore, studying the role that individual differences in input play can improve our understanding of how language is learned, processed and represented.Keywords: individual differences, social networks, PsychLingvarOne of the main goals of psycholinguistic research is to understand how we make sense of incoming input and manage to transform it into meaningful utterances. On the face of it, this is a task that most of us seem to succeed at, yet a closer look reveals great variation in the degree of success at different aspects of the task, from speech perception to the comprehension of pragmatic intentions. So far, the study of individual differences in language processing has mostly focused on differences due to variation in cognitive skills. Much less attention has been devoted to individual differences in the social environment, and in particular, to differences in the properties of the input it provides, especially among adult native speakers. In this paper, I argue that the characteristics of the input that people receive play an important role in shaping their linguistic performance. I will focus on three manners by which input can do so: by influencing the knowledgebase that feeds the analysis of incoming language, by influencing the manner of processing, such as the mechanisms that are relied on and the cues that are attended to during language processing, and by shaping expectations, which, in turn, influence performance. From noise to structured differencesThe realization that individual differences in performance can be informative about language processing and representation and are not merely noise that needs to be reduced has only gained popularity in Psycholinguistics over the last couple of decades. For many decades, experimental studies in psycholinguistics, as well as in other fields, focused on the commonalities, on how people in general perform certain tasks, and how the average participant is influenced by certain manipulations. Individual differences in performance were treated as noise. After all, by definition, participants' score on any task is composed of their "true" score and the measurement error, and so differences might simply be noise. If the experiment is conducted well, the measurement errors should cancel each other, and the general trend would be discovered. It is only in the 90s that the systematicity in this "noise" has started to be explo...

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Inhibitory control predicts language switching performance in trilingual speech production

Cited by 161 publications

References 34 publications

A review of control processes and their locus in language switching

A review of control processes and their locus in language switching

Patterns of Short-Term Phonetic Interference in Bilingual Speech

Studying individual differences in the social environment to better understand language learning and processing

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