For years, researchers have been interested in the similarities seen across human languages.

A new study led by a University of Arizona researcher suggests that some of those similarities may be based on the human brain's preference for efficient information processing.

Masha Fedzechkina, an assistant professor of linguistics, is the lead researcher for the study. She and her team designed an artificial language based on Japanese rules of grammar and then played audio samples to teach English-only speakers the new language and two ways to express the same ideas in that language.

When she tested the artificial language on her sample group, they showed an overwhelming preference for short dependency length, the distance between words that depend on each other for interpretation.

According to Fedzechkina, the finding suggests that language construction might be explained by what appears to be the human brain's innate preference for short sentence constructions.

“The question is: ‘how did our learners know to do it when this pattern was not present in the input artificial language and it was not present in their native language?’ In fact, English does the opposite,” Fedzechkina said. “The way we interpret this, is that it has to do with constraints on how our brain processes information.”

The study is published in the journal “Psychological Science.”