Dynamic changes in network activations characterize early learning of a natural language

Those who are initially exposed to an unfamiliar language have difficulty separating running speech into individual words, but over time will recognize both words and the grammatical structure of the language. Behavioral studies have used artificial languages to demonstrate that humans are sensitive to distributional information in language input, and can use this information to discover the structure of that language. This is done without direct instruction and learning occurs over the course of minutes rather than days or months. Moreover, learners may attend to different aspects of the language input as their own learning progresses. Here, we examine processing associated with the early stages of exposure to a natural language, using fMRI. Listeners were exposed to an unfamiliar language (Icelandic) while undergoing four consecutive fMRI scans. The Icelandic stimuli were constrained in ways known to produce rapid learning of aspects of language structure. After approximately 4 min of exposure to the Icelandic stimuli, participants began to differentiate between correct and incorrect sentences at above chance levels, with significant improvement between the first and last scan. An independent component analysis of the imaging data revealed four task-related components, two of which were associated with behavioral performance early in the experiment, and two with performance later in the experiment. This outcome suggests dynamic changes occur in the recruitment of neural resources even within the initial period of exposure to an unfamiliar natural language.