多くの言語を話す人々にとって、母国語には特別な何かがある(For people who speak many languages, there’s something special about their native tongue)

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2024-03-10 マサチューセッツ工科大学(MIT)

多言語を話す人々の脳には、母国語を処理する特別な方法があることが、研究で明らかになりました。多言語話者の脳では、どの言語を聞いても同じ言語領域が活性化します。しかし、母国語を聞くと、他の言語に比べて活性化が著しく低下します。これは、脳が初めて習得した言語を処理する際には努力が最小限で済むためとされています。この研究は、「Cerebral Cortex」誌に掲載されました。

<関連情報>

精密fMRIによるポリグロットとハイパーポリグロットの言語ネットワークの機能的特徴づけ Functional characterization of the language network of polyglots and hyperpolyglots with precision fMRI

Saima Malik-Moraleda, Olessia Jouravlev, Maya Taliaferro, Zachary Mineroff, Theodore Cucu, Kyle Mahowald, Idan A Blank, Evelina Fedorenko
Cerebral Cortex  Published:11 March 2024
DOI:https://doi.org/10.1093/cercor/bhae049

Responses to different languages in the polyglots’ language network. (a) Activation overlap for the four familiar languages (L1–L4). For each language, we selected 10% of voxels in the LH that were most responsive to the Language > Quilted-control contrast (based on the contrast values). The activations are shown within the boundaries of the language parcels (see Methods). Colors correspond to the number of languages (between 1 and 4) for which the voxel was in the set of top 10% of most responsive voxels (Three-digit numbers in black boxes correspond to the unique ID of the participant and can be cross-referenced with the data on OSF: https://osf.io/3he75/.). For similar overlap maps for all participants, see Fig. S1; for the activation maps for individual languages within sample participants, see Fig. S2. (b) Response in the language network (averaged across the five fROIs) to the conditions of the multi-language listening experiment relative to the fixation baseline (for the responses of the individual fROIs, see Fig. S3a; for the responses broken down by experiment version (Bible, Alice in Wonderland), see Figs S3b and S5c). The language fROIs are defined by the Sentences > Nonwords contrast in the English localizer (see Methods; see Fig. S4 for evidence that the results are similar when the L1 > quilted contrast from the critical task is used as the localizer). The conditions include the participant’s native language (L1), three languages that the participant is somewhat proficient in (L2, L3, and L4; proficiency is highest for L2, lower for L3, and lower for L4, as described in Methods), four unfamiliar languages (two languages that are related to the languages that the participant is relatively proficient in, two languages that the participant is completely unfamiliar with), and the perceptually matched control condition (quilts; see Methods). Dots correspond to individual participants, and error bars represent standard errors of the mean by participant.

Abstract

How do polyglots—individuals who speak five or more languages—process their languages, and what can this population tell us about the language system? Using fMRI, we identified the language network in each of 34 polyglots (including 16 hyperpolyglots with knowledge of 10+ languages) and examined its response to the native language, non-native languages of varying proficiency, and unfamiliar languages. All language conditions engaged all areas of the language network relative to a control condition. Languages that participants rated as higher proficiency elicited stronger responses, except for the native language, which elicited a similar or lower response than a non-native language of similar proficiency. Furthermore, unfamiliar languages that were typologically related to the participants’ high-to-moderate-proficiency languages elicited a stronger response than unfamiliar unrelated languages. The results suggest that the language network’s response magnitude scales with the degree of engagement of linguistic computations (e.g. related to lexical access and syntactic-structure building). We also replicated a prior finding of weaker responses to native language in polyglots than non-polyglot bilinguals. These results contribute to our understanding of how multiple languages coexist within a single brain and provide new evidence that the language network responds more strongly to stimuli that more fully engage linguistic computations.

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医療・健康
機能的磁気共鳴画像法(fMRI)多言語脳言語ネットワーク
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