Saima Malik-Moraleda

What constitutes a language? Natural languages share some features with other domains: from math, to music, to gesture. However, the brain mechanisms that process linguistic input are highly specialized, showing little or no response to diverse non-linguistic tasks. Here, we examine constructed languages (conlangs) to ask whether they draw on the same neural mechanisms as natural languages, or whether they instead pattern with domains like math and logic. Using individual-subject fMRI analyses, we show that understanding conlangs recruits the same brain areas as natural language comprehension. This result holds for Esperanto (n=19 speakers)— created to resemble natural languages—and fictional conlangs (Klingon (n=10), Na’vi (n=9), High Valyrian (n=3), and Dothraki (n=3)),  created to differ from natural languages, and suggests that conlangs and natural languages share critical features and that the notable differences between conlangs and natural language are not consequential for the cognitive and neural mechanisms that they engage.

A small fraction of the world population master five or more languages. How do such polyglots represent and process their different languages, and more generally, what can this unique population tell us about the language system? We identified the language network in each of 25 polyglots (including 16 hyperpolyglots with knowledge of 10+ languages) and examined its response to the native language, languages of varying proficiency, and unfamiliar languages. We found that all languages elicit a response reliably above the perceptually matched control condition in all areas of the language network. The response magnitude across languages generally scaled with comprehension level: aside from the native language, which elicited a relatively low response, languages that were more comprehensible to the participant elicited stronger responses. This pattern held for both familiar (studied) languages, and unfamiliar languages (cognate languages of high-proficiency languages elicited a stronger response than non-cognate languages). We also replicated a prior finding of weaker responses during native language processing in polyglots compared to non-polyglots. These results contribute to our understanding of how multiple languages co-exist within a single brain and provide new evidence that the language-selective network responds more strongly to stimuli from which more linguistic meaning can be extracted.

To understand the architecture of human language, it is critical to examine diverse languages; yet most cognitive neuroscience research has focused on a handful of primarily Indo-European languages. Here, we report an investigation of the fronto-temporo-parietal language network across 45 languages and establish the robustness to cross-linguistic variation of its topography and key functional properties, including left-lateralization, strong functional integration among its brain regions, and functional selectivity for language processing.

A standard assumption in the bilingual language processing literature is that the ease of access of a word in a language is determined by the speaker’s overall proficiency in the language. Alternatively, it could be that proficiency varies across semantic categories of the bilingual’s two languages. Here, we investigated lexical access in color terms in Tsimane’-Spanish bilinguals. Given that color terms are generally more frequent in Spanish than Tsimane’, participants may have better lexical access for color words in Spanish despite being overall more proficient in Tsimane’. Twenty-two Tsimane’-Spanish bilinguals took part in a picture naming task where participants labeled colors and animals. Participants were equally fast and accurate at naming animals in Tsimane’ and Spanish. However, participants were faster and more accurate at naming colors in Spanish than Tsimane’ except for the three color words that are most frequent (jaibes = white, tsincus = black, jaines = red) in Tsimane’, for which they were equally fast in both Tsimane’ and Spanish. These results suggest that category-specific proficiency is a better predictor for lexical access than overall proficiency.

Words and the concepts they represent vary across languages. Here we ask if mother-tongue concepts are altered by learning a second language. What happens when speakers of Tsimane’, a language with few consensus color terms, learn Bolivian-Spanish, a language with more terms? Three possibilities arise: concepts in Tsimane’ remain unaffected, or they are remapped, either by Tsimane’ terms taking on new meanings or by borrowing Bolivian-Spanish terms. We found that bilingual speakers remap Tsimane’ concepts. They do not import Bolivian-Spanish terms into Tsimane’ and they show no evidence in Tsimane’ for the acquisition of the Bolivian-Spanish subdivision of blue (celeste and azul). Instead they acquire more precise use of all Tsimane’ terms, for example restructuring concepts of monolingual synonyms shandyes and yụshñus to reflect the Bolivian-Spanish distinction of verde (~green) and azul (~blue). These results show that learning a second language can change the concepts in the first language.