Similar Activity in the Brain's Language Network, No Matter What Language You Speak - Neuroscience News

Summary: In a study of speakers of 45 languages, researchers found similar patterns of brain activity and language selectivity.

Source: MIT

For decades, neuroscientists have created well-defined maps of the brain’s “language network,” or regions of the brain specialized for processing language. Found primarily in the left hemisphere, this tissue includes areas within Broca’s area, as well as in other parts of the frontal and temporal lobes.

However, most of these mapping studies were conducted on English speakers while they were listening to or reading English texts. MIT neuroscientists have now conducted brain imaging studies of speakers of 45 different languages. The results show that the language network of speakers appears to be essentially the same as that of native English speakers.

This finding, though not surprising, establishes that the location and key properties of language networks appear to be universal. This work also lays the groundwork for the future study of linguistic elements that would be difficult or impossible to learn in English speakers because English does not have such features.

“This study is very basic, extending some of the findings from English to multiple languages,” said Evelina Fedorenko, Frederick A. and Carole J. Middleton Career Development Associate Professor of Neuroscience at MIT and a member of the McGovern Institute for MIT Brain Research.

“The hope is that now that we see that basic traits appear to be common across languages, we can ask about potential differences between languages ​​and language families in how they are applied in the brain, and we can study phenomena that don’t actually occur. is in English.”

Fedorenko is the senior author of the study, which appears today at Natural Neuroscience. Saima Malik-Moraleda, a PhD student in the Speech and Hearing Bioscience and Technology program at Harvard University, and Dima Ayyash, a former research assistant, are the lead authors of the paper.

Language network mapping

The exact location and shape of language areas differs between individuals, so to find language networks, researchers asked each person to perform a language task while scanning their brains with functional magnetic resonance imaging (fMRI). Listening to or reading sentences in one’s mother tongue must activate the language network.

To differentiate this network from other brain regions, researchers also asked participants to perform tasks they shouldn’t activate, such as listening to a foreign language or solving a math problem.

A few years ago, Fedorenko started designing this “localizer” task for speakers of languages ​​other than English. While most language network studies have used English speakers as subjects, English does not include many of the features commonly seen in other languages. For example, in English, word order tends to be fixed, while in other languages ​​it is more flexible in the way words are arranged. Many of these languages ​​instead use the addition of morphemes, or word segments, to convey additional meaning and relationships between words.

“There is a growing awareness over the years about the need to look at more languages, if you want to make claims about how language works, as opposed to how English works,” Fedorenko said.

“We thought it would be useful to develop tools that would allow people to study language processing strictly in the brain in other parts of the world. There is now access to brain-imaging technology in many countries, but the basic paradigm you need to find language-responsive areas in a person isn’t there.”

For the new study, researchers performed brain imaging of two speakers of 45 different languages, representing 12 different language families. Their goal was to see if the key properties of the language network, such as location, left lateralization, and selectivity, were the same in these participants as in people whose mother tongue was English.

The researchers decided to use “Alice in Wonderland” as the text that everyone would hear, as it is one of the most translated works of fiction in the world. They selected 24 short sections and three long sections, each recorded by a native speaker of the language. Each participant also heard nonsensical passages, which should not activate the language network, and were asked to perform various other cognitive tasks that should not activate them.

The team found that the language networks of the participants in the study were found around the same brain regions, and had the same selectivity as native English speakers.

“The language area is selective,” says Malik-Moraleda. “They shouldn’t respond during other tasks such as the spatial working memory task, and that’s what we found across speakers of the 45 languages ​​we tested.”

In addition, the language regions that are normally co-activated in English speakers, such as the frontal language region and the temporal language region, are also synchronized with speakers of other languages.

The researchers also showed that across all subjects, the small amount of variation they saw between individuals speaking different languages ​​equaled the amount of variation typically seen among native English speakers.

Similarities and differences

While the findings suggest that the overall architecture of language networks is similar across speakers of different languages, that doesn’t mean that there aren’t any differences at all, Fedorenko said. As one example, researchers can now look for differences in language speakers who mostly use morphemes, rather than word order, to help determine the meaning of a sentence.

In brain imaging studies, neuroscientists found similar patterns of brain activation across language areas such as Broca’s area. Credit: Christine Daniloff, MIT

“There are all sorts of interesting questions you can ask about morphological processing that really don’t make sense to ask in English, because there’s so much less morphology,” Fedorenko said.

See also

Another possibility is to study whether speakers of languages ​​who use pitch differences to convey different word meanings will have language networks with stronger links to the auditory brain regions that code for tones.

Currently, Fedorenko’s lab is working on a study in which they compare the ‘temporal receptive fields’ of speakers of six typologically different languages, including Turkish, Mandarin, and Finnish. The temporal receptive field is a measure of how many words a language processing system can handle at one time, and for English, it has been shown to be six to eight words long.

“The language system appears to be working on chunks of just a few words, and we’re trying to see if this limitation applies to all the other languages ​​we’ve tested,” Fedorenko said.

The researchers also worked to create a language localization task and found study participants who represented additional languages ​​out of 45 of the study.

Funding: The research was funded by the National Institutes of Health and research grants from MIT’s Department of Brain and Cognitive Sciences, the McGovern Institute, and the Simons Center for the Social Brain. Malik-Moraleda is funded by a la Caixa Fellowship and Friends of McGovern fellowship.

About this language and neuroscience research news

Author: Anne Trafton
Source: MIT
Contact: Anne Trafton – MIT
Picture: Image credited to Christine Daniloff, MIT

Original Research: Closed access.
“Investigations across 45 languages ​​and 12 language families reveal universal language networks” by Evelina Fedorenko et al. Natural Neuroscience

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Abstract

Investigations across 45 languages ​​and 12 language families reveal universal language networks

To understand the architecture of human language, it is very important to examine a variety of languages; however, most cognitive neuroscience research has focused on only a handful of Indo-European languages.

Here we report an investigation of the fronto-temporo-parietal language network in 45 languages ​​and establish resistance to cross-language variation of topography and its key functional properties, including left lateralization, strong functional integration between brain regions, and functional selectivity for language processing.

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