The role of a critical left fronto-temporal network with its right-hemispheric homologue in syntactic learning based on word category information

Abstract

Word category information (WCI) is proposed to be fundamental for syntactic learning and processing. However, it remains largely unclear how left-hemispheric key regions for language, including BA 44 in the inferior frontal gyrus (IFG) and superior temporal gyrus (STG), interact with their right-hemispheric homologues to support the WCI-based syntactic learning. To address this question, this study employed a unified structural equation modeling (uSEM) approach to explore both the intra- and inter-hemispheric effective connectivity among these areas, to specify the neural underpinnings of handling WCI for syntactic learning. Modeling results identified a distinctive intra-left hemispheric connection from left BA 44 to left STG, a more integrated intra-right hemispheric network, and a particular frontal right-to-left hemispheric connectivity pattern for WCI-based syntactic learning. Further analyses revealed a selective positive correlation between task performance and the lagged effect in left BA 44. These results converge on a critical left fronto-temporal language network with left BA 44 and its connectivity to left STG for WCI-based syntactic learning, which is also facilitated in a domain-general fashion by the right homologues. Together, these results provide novel insights into crucial neural network(s) for syntactic learning on the basis of WCI.