Bilingualism as a gradient measure modulates functional connectivity of language and control networks

Sulpizio, Simone; Maschio, Nicola Del; Mauro, Gianpaolo Del; Fedeli, Davide

doi:10.1016/j.neuroimage.2019.116306

Cited by 126 publications

(147 citation statements)

References 67 publications

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“…Allowing multiple bilingual groups in a factor mixture model could potentially mirror groups that already exist in the literature (e.g., simultaneous, sequential, etc. ), and subsequently capture the heterogeneity within those groups (Clark et al, 2013;Sulpizio et al, 2020). While theory can drive the number of categories and the measures that are included in a final bilingualism score, it should be noted that the number of groups and the number of factors contributing to the continuous score are typically determined through an iterative modeling process.…”

Section: Factor Mixture Modelmentioning

confidence: 99%

Why not both? Rethinking categorical and continuous approaches to bilingualism

Kremin¹,

Byers‐Heinlein²

2020

Preprint

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Bilingualism is a complex construct, and it can be difficult to define and model. This paper proposes that the field of bilingualism can draw from other fields of psychology, by integrating advanced psychometric models that incorporate both categorical and continuous properties. These models can unify the widespread use of bilingual and monolingual groups that exist in the literature with recent proposals that bilingualism should be viewed as a continuous variable. In the paper, we highlight two models of potential interest: the factor mixture model and the grade-of-membership model. These models simultaneously allow for the formation of different categories of speakers and for variation to exist within these categories. Researchers can then conduct their analyses on either the categorical or continuous information, or a combination of the two, depending on which is most appropriate to address their research question. Conceptualizing bilingualism within the context of these more flexible models will help to advance theory and lead to a fuller and deeper understanding of bilingualism.

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Section: Factor Mixture Modelmentioning

confidence: 99%

Why not both? Rethinking categorical and continuous approaches to bilingualism

Kremin¹,

Byers‐Heinlein²

2020

Preprint

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“…The calculation revealed that the effect sizes for dFC and dynamic topological properties were quite high (Cohen's d > 1.2) in this study. In addition, recent studies (Gullifer et al, 2018;DeLuca et al, 2019;Sulpizio et al, 2020) are fast moving toward considering AoA-L2 as a continuous variable in correlational analysis with brain function and structure. In future studies, we should include more detailed behavior measurements (De Bruin, 2019) and recruit more subjects to undergo MRI scanning.…”

Section: Limitationsmentioning

confidence: 99%

“…The graph theory has been widely used to measure the topological properties of brain networks (Wang et al, 2010;Bullmore and Bassett, 2011;Karwowski et al, 2019). For example, Sulpizio et al (2020) applied the graph theory to explore the neural activation within the language and control networks in bilinguals. In this study, we selected four parameters, clustering coefficient (C w ), characteristic path length (L w ), global efficiency (E glob ), and local efficiency (E loc ), to characterize the dynamic topological properties of the language network.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Language Network in Early and Late Cantonese–Mandarin Bilinguals

Liu

Chen

et al. 2020

Front. Psychol.

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The brain representation of language in bilinguals is sculptured by several factors, such as age of acquisition (AoA) and proficiency level (PL) in second language. Although the effect of AoA-L2 on brain function and structure has been studied, little attention is devoted to dynamic properties of the language network and their differences between early and late bilinguals. In this study, we acquired resting-state fMRI data from early and late Cantonese (L1)-Mandarin (L2) bilinguals with high PLs of verbal fluency in both languages. We then analyzed dynamic functional connectivity (dFC) by using the sliding-windows approach, estimated the dFC states by using the k-means clustering algorithm, and calculated the dynamic topological properties of the language network for the early and late bilinguals. We detected four dFC states, State 1, State 2, State 3, and State 4, which may be related to phonetic processing, semantic processing, language control, and syntactic processing, respectively. Compared to the late bilinguals, the early bilinguals showed higher dFC between the inferior frontal area and the temporal area in State 1 and State 2, while higher dFC between the cerebellum and other regions in State 3. The early bilinguals showed a higher clustering coefficient and local and global efficiency in State 1 and State 3, but lower characteristic path length in State 1, than the late bilinguals. Together, these results suggested that AoA-L2 affects temporal neural activation and dynamic topological properties of the language network. These findings provide new information to understand the effect of experience of L2 acquisition on language network in bilinguals.

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“…Neuroimaging evidence supporting this assumption demonstrates that there is indeed an overlap in brain networks involved in language selection and non-verbal task switching (Abutalebi and Green, 2007;Luk et al, 2011;De Baene et al, 2015). However, in recent studies such an overlap is further specified as being valid for bilinguals only (Anderson et al, 2018;Wu et al, 2019;Stasenko et al, 2020;Sulpizio et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Explaining Individual Differences in Executive Functions Performance in Multilinguals: The Impact of Code-Switching and Alternating Between Multicultural Identity Styles

et al. 2020

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This study sheds new light on the relative impact of switching between languages and switching between cultures on Executive Functions (EFs) in bilinguals. Several studies have suggested that bilingualism has a measurable impact on executive functioning, presumably due to bilinguals' constant practice in dealing with two languages, or two cultures. Yet, the evidence on the relative contribution of culture and bilingualism to EFs is not well understood, because disentangling language, culture and immigration status is very difficult. The novelty of our approach was to keep the language pair and immigration status constant, whilst the cultural identity of participants was systematically varied, and measured at the individual level (not just at group level). Two groups of Turkish-English bilinguals, all adult immigrants to the United Kingdom, took part in the study, but one group (n = 29) originated from mainland Turkey and the other (n = 28) from Cyprus. We found that the bilinguals experienced smaller Conflict Effects on a Flanker task measuring inhibition, by comparison with monolingual British participants (n = 30). The key variable explaining EF performance variance at the individual level turned out to be bilinguals' Multicultural Identity Style. In particular those who indicated that they attempted to alternate between different British and Turkish (Cypriot) identity styles were found to have shorter RTs on incongruent trials of the Flanker task. The two multicultural identity variables, Alternating and Hybrid Identity Styles, together explained 32% in RTs over and above Education, Working Memory and Nonverbal reasoning (overall explained variance 49%). Thus, the data provide strong evidence for the impact of culture on EFs. We suggest that, as a result of their daily practice in recognizing cultural cues which highlight the need to switch to a different cultural frame, multicultural bilinguals develop a heightened context-sensitivity, and this gives them an advantage over monolinguals in a Flankers task. Our approach, which draws on models from cross-cultural psychology, bilingualism and executive functioning, illustrates the importance of theory building in which sociolinguistic and cultural variables are integrated into models of EFs.

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Bilingualism as a gradient measure modulates functional connectivity of language and control networks

Cited by 126 publications

References 67 publications

Why not both? Rethinking categorical and continuous approaches to bilingualism

Why not both? Rethinking categorical and continuous approaches to bilingualism

Dynamic Language Network in Early and Late Cantonese–Mandarin Bilinguals

Explaining Individual Differences in Executive Functions Performance in Multilinguals: The Impact of Code-Switching and Alternating Between Multicultural Identity Styles

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