Brain network reconfiguration for language and domain-general cognitive control in bilinguals

Wu, Junjie; Yang, Jing; Chen, Mo; Li, Shuhua; Zhang, Zhaoqi; Kang, Chunyan; Ding, Guiguang; Guo, Taomei

doi:10.1016/j.neuroimage.2019.06.022

Cited by 52 publications

(49 citation statements)

References 115 publications

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“…On the other hand, the MDS seems necessary for language, at least in case of difficult task and memory requirements (Campbell and Tyler, 2018), and it seems to be engaged in language learning (Sliwinska et al, 2017). A particular network overlapping with the MDS has been outlined for language control in bilingual speakers, comprising dorsal and ventral parts of the frontal lobe, parietal cortex, subcortical areas and cerebellar regions (Wu et al, 2019).…”

Section: The Multiple Demand Systemmentioning

confidence: 99%

The Margins of the Language Network in the Brain

2020

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This review paper summarizes the various brain modules that are involved in speech and language communication in addition to a left-dominant "core" language network that, for the present purpose, has been restricted to elementary formal-linguistic and more or less disembodied functions such as abstract phonology, syntax, and very basic lexical functions. This left-dominant perisylvian language network comprises parts of inferior frontal gyrus, premotor cortex, and upper temporal lobe, and a temporoparietal interface. After introducing this network, first, the various roles of neighboring and functionally connected brain regions are discussed. As a second approach, entire additional networks were considered rather than single regions, mainly motivated by resting-state studies indicating more or less stable connectivity patterns within these networks. Thirdly, some examples are provided for language tasks with functional demands exceeding the operating domain of the core language network. The rationale behind this approach is to present some outline of how the brain produces and perceives language, accounting, first, for a bulk of clinical studies showing typical forms of aphasia in case of left-hemispheric lesions in the core language network and second, for widespread activation patterns beyond this network in various experimental studies with language tasks. Roughly, the brain resources that complement the core language system in a task-specific way can be described as a number of brain structures and networks that are related to (1) motor representations, (2) sensory-related representations, (3) non-verbal memory structures, (4) affective/emotional processing, (5) social cognition and theory of mind, (6) meaning in context, and (7) cognitive control. After taking into account all these aspects, first, it seems clear that natural language communication cannot really work without additional systems. Second, it also becomes evident that during language acquisition the core language network has to be built up from outside, that is, from various neuronal activations that are related to sensory input, motor imitation, nursing, pre-linguistic sound communication, and pre-linguistic pragmatics. Furthermore, it might be worth considering that also in cases of aphasia the language network might be restored by being trained from outside.

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Section: The Multiple Demand Systemmentioning

confidence: 99%

The Margins of the Language Network in the Brain

2020

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“…Dynamic organization of the functional network resulted in a well-organized way to ensure more efficient cooperation between brain regions during the brain resting state and different cognitive tasks (Raichle et al, 2001;Fox and Raichle, 2007;Sporns, 2010). A recent study (Wu et al, 2019) found more activity in subcortical areas and a connection from frontal to subcortical areas when bilinguals performed a language switching task compared to a nonverbal switching task. These results suggested a reconfigurable brain network for language and domain-general cognitive control in bilinguals.…”

Section: Dynamic Language Networkmentioning

confidence: 93%

“…Early bilinguals are more likely to use a common neural mechanism to process L1 and L2 (Klein et al, 2006;Garbin et al, 2011), while late bilinguals with low PL-L2 may recruit more activation of cognitive control regions when processing L2 (Saur et al, 2009;Berken et al, 2015). Language processing is supported by a set of brain regions located in the language network (Price, 2010;Tie et al, 2014;Seo et al, 2018), in which the information transfers as a dynamic instead of static signal (Friederici and Gierhan, 2013;Fedorenko and Thompson-Schill, 2014;Wu et al, 2019). The dynamic property of the language network is mainly reflected in regional activation of the language network changing over time when subject processing language or even in brain resting state (Fedorenko and Thompson-Schill, 2014;Chai et al, 2016).…”

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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Brain network reconfiguration for language and domain-general cognitive control in bilinguals

Cited by 52 publications

References 115 publications

The Margins of the Language Network in the Brain

The Margins of the Language Network in the Brain

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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