Linguistic networks associated with lexical, semantic and syntactic predictability in reading: A fixation-related fMRI study

Abstract

The ability to make predictions is thought to facilitate language processing. During language comprehension such predictions appear to occur at multiple levels of linguistic representations (i.e. semantic, syntactic and lexical). The neural mechanisms that define the network sensitive to linguistic predictability have yet to be adequately defined. The purpose of the present study was to explore the neural network underlying predictability during the normal reading of connected text. Predictability values for different linguistic information were obtained from a pre-existing text corpus. Forty-one subjects underwent simultaneous eye-tracking and fMRI scans while reading these select paragraphs. Lexical, semantic, and syntactic predictability measures were then correlated with functional activation associated with fixation onset on the individual words. Activation patterns showed both positive and negative correlations to lexical, semantic, and syntactic predictabilities. Conjunction analysis revealed regions specific to or shared between each type of predictability. The regions associated with the different predictability measures were largely separate. Results suggest that most linguistic predictions are graded in nature, activating components of the existing language system. A number of regions were also found to be uniquely associated with full lexical predictability, most notably the anterior temporal lobe and the inferior posterior temporal cortex.