Aviva Lerman , Alina Bihovsky , Natalia Meir , Michal Ben-Shachar , Mira Goral
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引用次数: 0
Abstract
Language mixing (LM) is common among individuals who speak two or more languages. LM in healthy multilingual individuals has been studied extensively, often by applying the Matrix Language Frame (MLF) and the 4M model, both developed by Myers-Scotton and colleagues. Our study examined LM in multilingual people with aphasia (PWA), to determine: (1) frequency of LM in the first-acquired language (L1) and later-acquired languages (L2/L3); (2) whether the 4M model accounts for LM patterns; and (3) how language-specific characteristics affect LM.
Narratives produced by 18 multilingual PWA (English-Hebrew; English-Spanish, English-Hebrew-Spanish and Russian-Hebrew speakers) with and without agrammatism were analyzed using the 4M model. More LM was observed in L2 contexts compared to L1 in participants with agrammatism, yet in participants without agrammatism no differences were found between L1 and L2. The patterns of LM in target and non-target languages were similar across L1 and L2: content morphemes were more likely to be embedded into the matrix language, aligning with previous research on healthy multilingual controls. Differences were found between the types of LM across the four studied languages.
Our findings indicate that multilingual PWA mix languages in a typical manner, similar to neurotypical multilingual individuals, aligning with the predictions of the 4M model. Furthermore, in multilingual PWA, as in healthy multilingual people, differences in LM across languages are related to the morphological richness of the matrix language and the congruency of the languages involved in LM. Clinically, based on our results, LM can be encouraged as a communication aid.
期刊介绍:
An interdisciplinary journal, Brain and Language publishes articles that elucidate the complex relationships among language, brain, and behavior. The journal covers the large variety of modern techniques in cognitive neuroscience, including functional and structural brain imaging, electrophysiology, cellular and molecular neurobiology, genetics, lesion-based approaches, and computational modeling. All articles must relate to human language and be relevant to the understanding of its neurobiological and neurocognitive bases. Published articles in the journal are expected to have significant theoretical novelty and/or practical implications, and use perspectives and methods from psychology, linguistics, and neuroscience along with brain data and brain measures.