Poster B45, Sunday, March 25, 8:00-10:00 am, Exhibit Hall C
Effects of polyglotism on functioning of the language, MD, and DMN networks.
Olessia Jouravlev1,2, Zachary Mineroff1, Evelina Fedorenko1,3,4; 1Massachusetts Institute of Technology, 2Carleton University, 3Harvard Medical School, 4Massachusetts General Hospital
Research on neurocognitive mechanisms of exceptional language processing is lacking. We report the first fMRI investigation of seventeen polyglots (M(languages)=11.6; range(languages)=5-55). In Study 1, we explored whether the language network of polyglots was different from that of non-polyglots. The language network was defined individually using the Sentences>Nonwords contrast of the language localizer task (Fedorenko et al., 2010). The polyglots showed both less extensive activation and a smaller Sentences>Nonwords effect than non-polyglots. No group differences were observed in two control brain networks (Multiple Demand and DMN), arguing against ubiquitous group differences in information processing. This finding suggests that language processing is more efficient in individuals speaking multiple languages compared to monolinguals. In Study 2, we examined how different languages (i.e., native language (L1), non-native languages (L2-L4), cognates languages (L5-L6), and unfamiliar languages (L7-L8)) are represented in the polyglots’ brains. Participants listened to intact passages in different languages and to a control scrambled-speech condition. The Intact>Scrambled contrasts for the different languages activated highly overlapping areas within the language network. The Intact>Scrambled effect was reliable in all languages (ps<0.03), but its size generally scaled with proficiency, decreasing from L2 to L8, except for the response to L1, which was relatively low. Thus, the ability to extract high-level linguistic information from the speech signal leads to stronger responses in the language regions. However, one’s native language constituted an exception: the response was lower than to familiar non-native languages, perhaps reflecting greater efficiency.
Topic Area: LANGUAGE: Other