Poster D47, Monday, March 26, 8:00-10:00 am, Exhibit Hall C
Language-specific and domain-general regions jointly predict individual differences in sentence comprehension: Evidence from a network approach
Qiuhai Yue1, Randi C. Martin1, Simon Fischer-Baum1, Michael W. Deem1; 1Rice University
Some researchers have claimed that the neural substrate for high-level language processes does not involve regions which are engaged in a wide range of domain-general non-linguistic processes (e.g., working memory, cognitive control), with domain-general regions only activated by complicated sentence structures (e.g., strong garden paths, object relatives) rarely encountered in natural conversation. The current study addressed these claims by examining whether individual differences in comprehension of unambiguous sentences with commonly encountered structures was better predicted by interconnectivity of a network comprised of both language-specific and domain-general nodes or interconnectivity within the language network. We used graph theoretic tool to estimate modularity for each of 42 subjects based on the correlation matrix for functional connectivity between nodes during resting-state fMRI. A sentence comprehension task administered to the same participants outside the scanner manipulated the degree of semantic and syntactic interference. Consistent with our previous findings relating lower modularity (i.e., relatively strong between-module connections) with better complex task performance, correlational analysis between behavior and brain network modularity indicated that better performance in comprehending more difficult sentences was associated with lower modularity derived from the network combining language and domain-general regions, but had no relationship with the modularity of the language network per se. Our findings support the claim that domain-general regions play a role as sentence complexity increases. The results provide a strong challenge to theories claiming the independence of the language network.
Topic Area: LANGUAGE: Other