Will Dunham at Reuters writes about new research from Prof. Evelina Fedorenko and others, which found that polyglots “who spoke between five and 54 languages” used less brain activity when processing their native language. "We think this is because when you process a language that you know well, you can engage the full suite of linguistic operations - the operations that the language system in your brain supports," says Fedorenko.
MIT researchers have used machine learning to uncover the different kinds of sentences that most likely to activate the brain’s key language processing centers, reports Kyle Wiggers and Devin Coldewey for TechCrunch. The model, “was able to predict for novel sentences whether they would be taxing on human cognition or not,” they explain.
Researchers from MIT and Harvard have found that an adult’s ability to “parse the early attempts of children to talk may also help the children learn how to speak properly faster,” reports Jess Thomson for Newsweek. “These adult listening abilities might help children communicate very early and highlight that speech is a good way to share information with others," says postdoctoral associate Stephan Meylan. "That said, there is a lot of diversity in how adults and children interact across the world, both within and across different social and cultural contexts. This means that there are very likely many pathways to understanding language."
Prof. Jacob Andreas explored the concept of language guided program synthesis at CSAIL’s Imagination in Action event, reports research affiliate John Werner for Forbes. “Language is a tool,” said Andreas during his talk. “Not just for training models, but actually interpreting them and sometimes improving them directly, again, in domains, not just involving languages (or) inputs, but also these kinds of visual domains as well.”
Prof. Ev Fedorenko has been studying the differences in “the neural architecture of speakers who speak languages with different properties,” reports Sofia Quaglia for Wired. “Her studies suggest that the core features of language systems in the brain seem similar across the board,” explains Quaglia.
MIT researchers have found that lawyers prefer, and better understand, simplified texts, rather than legalese, reports Jesse Greenspan for Scientific American. “The researchers presented 105 U.S. attorneys with contract excerpts written in both “legalese” and plain English and tested their comprehension and recall for each,” explains Greenspan. “While the attorneys outperformed laypeople overall, they still found the legalese contracts harder to grasp than those written in plain English.”
Researchers at MIT have found that lawyers “have an easier time remembering legal documents written in simple English over those filled with so-called legalese,” reports Ed Cara for Gizmodo. “On average, for instance, lawyers scored 45% on a test that asked them to recall documents written in legalese, compared to the average 38% scored by nonlawyers,” explains Cara. “But the lawyers’ score also increased to over 50% when they were given the simplified version.”
Prof. Edward Flemming speaks with Boston.com reporter Ross Cristantiello about the origins of the Boston accent. Flemming says the “'softening' and eventual dropping of “R” sounds appears to have spread from the south of England through ports up and down the eastern coast of America, influencing the accents found in cities like Charleston and New York City.”
Researchers from MIT and elsewhere have studied the mind of polyglots and uncovered how language-specific regions of the brain respond to different and familiar languages, reports Natalia Mesa for Science. The researchers found that “the activity in the brain’s language network fluctuated based on how well participants understood a language. The more familiar the language, the larger the response,” writes Mesa. “There was one exception to the rule: when participants heard their native tongue, their language networks were actually quieter than when they heard other familiar languages.”
Researchers from the MIT-IBM Watson AI Lab and the Harvard Natural Language Processing Group developed the Giant Language model Test Room (GLTR), an algorithm that attempts to detect if text was written by a bot, reports Megan Morrone for Fast Company. “Using the ‘it takes one to know one’ method, if the GLTR algorithm can predict the next word in a sentence, then it will assume that sentence has been written by a bot,” explains Morrone.
Prof. Evelina Fedorenko speaks with Atlantic reporter Matteo Wong about her research exploring how “the brain behaves when an individual speaks different languages.” Fedorenko explains that “it seems like languages provide us with mappings between forms and meanings.”
Scientists at MIT have found that specific neurons in the human brain light up whenever we see images of food, reports Dr. Mallika Marshall for CBS Boston. “The researchers now want to explore how people’s responses to certain foods might differ depending on their personal preferences, likes and dislikes and past experiences,” Marshall.
Writing for The New York Times, Prof. Michel DeGraff details how the education system in Haiti discriminates against Kreyòl, forcing children to speak and learn in French, “a legacy of the French colonial design for Haiti’s impoverishment, which continues, centuries later, to drain us as a nation.” DeGraff adds: “Unshackling Haitian minds and society from centuries of linguistic discrimination is the first step to help Haiti overcome the disastrous consequences of its colonial and neocolonial history.”
Researchers at MIT have discovered that pictures of food appear to stimulate strong reactions among specific sets of neurons in the human brain, a trait that could have evolved due to the importance of food for humans, reports Sascha Pare for The Guardian. “The researchers posit these neurons have gone undetected because they are spread across the other specialized cluster for faces, places, bodies and words, rather than concentrated in one region,” writes Pare.
Prof. Evelina Fedorenko is studying a woman whose brain does not have a left temporal lobe in an effort to understand how the brain regions thought to play a role in language learning and comprehension develop. “Because EG’s left temporal lobe is missing, Fedorenko’s team had a chance to answer an interesting question: are the temporal regions a prerequisite for setting up the frontal language areas?” writes Grace Browne for Wired.