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People who speak many languages have smaller language networks
The people in this research reported speaking many languages, and their language networks measured smaller than those of monolinguals. That is a puzzling result, since a network with more responsibilities might be expected to be bigger.
One possible explanation is efficiency pressure. Within the languages these people speak, the brain responses to each language overlap heavily. So the network holds all of them in largely the same tissue.
Experience seems to have some influence on how the network is built, though a great deal is still to be discovered about that question.
Why would efficiency shrink a network?
Imaging studies of skill learning often report that a practiced task recruits less brain activity than an unpracticed one. This pattern is sometimes called neural efficiency. A network that handles several languages in largely the same tissue would fit that pattern, since overlapping responses need no separate territory for each language. The size of a network is usually measured as the amount of cortex that responds to language in a localizer scan.
How do brains handle more than one language?
Studies of bilingual speakers show that both languages are active in the brain even when only one is being spoken. Words from the unused language compete weakly with the chosen one, and the brain keeps that competition in check. Imaging work has found that the languages of a bilingual person engage largely overlapping cortical regions. Differences between languages are usually small shifts in how strongly the same regions respond.
How is a network's size even measured?
A common method is a localizer task in which a person reads or hears sentences and then a control such as lists of nonwords. The regions that respond more strongly to the sentences are marked as the language network. Researchers count the voxels, the small volume units of the scan, that pass a threshold. That count gives each person's network a size that can be compared with other people's.
More from Wu Tsai Neurosciences Institute, Stanford
