Native language leaves distinctive traces in brain connections

Abstract

The worlds languages differ substantially in their sounds, grammatical rules, and expression of semantic relations. While starting from a shared neural substrate, the developing brain must therefore have the plasticity to accommodate to the specific processing needs of each language. However, there is little research on how language-specific differences impacts brain function and structure. Here, we show that speaking typologically different languages leaves unique traces in the brains white matter connections of monolingual speakers of English (fixed word order language), German (with grammatical marking), and Chinese (tonal language). Using machine learning, we classified with high accuracy the mother tongue based on the participants patterns of structural connectivity obtained with probabilistic tractography. More importantly, connectivity differences between groups could be traced back to relevant processing characteristics of each native tongue. Our results show that the life-long use of a certain language leaves distinct traces in a speakers neural network.