Using stochastic language models (SLM) to map lexical, syntactic, and phonological information processing in the brain.

ABSTRACT: Language comprehension involves the simultaneous processing of information at the phonological, syntactic, and lexical level. We track these three distinct streams of information in the brain by using stochastic measures derived from computational language models to detect neural correlates of phoneme, part-of-speech, and word processing in an fMRI experiment. Probabilistic language models have proven to be useful tools for studying how language is processed as a sequence of symbols unfolding in time. Conditional probabilities between sequences of words are at the basis of probabilistic measures such as surprisal and perplexity which have been successfully used as predictors of several behavioural and neural correlates of sentence processing. Here we computed perplexity from sequences of w

SUBMITTER: Lopopolo A 

PROVIDER: S-EPMC5436813 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature