Neural Correlates of Lexical Interaction in Adult Second Language Learners

Open Access
Grant, Angela Marie
Graduate Program:
Master of Science
Document Type:
Master Thesis
Date of Defense:
November 01, 2013
Committee Members:
  • Ping Li, Thesis Advisor
  • second language
  • acquisition
  • fMRI
  • homograph
  • working memory
  • inhibitory control
This study uses functional magnetic resonance imaging (fMRI) to address two main issues in second language (L2) research: how semantic access in the L2 interacts with L1 semantic access, and how these processes may be influenced by individual differences in non-linguistic domains. Models of bilingual processing such as the inhibitory control (IC) model and the revised hierarchical model (RHM) suggest that (a) bilinguals must consistently use IC in comprehension and production, and (b) highly proficient learners access concepts directly while less proficient learners access concepts through the L1, respectively. The neural implication of these models is that less proficient bilinguals, compared with highly proficient bilinguals, will require more effort to inhibit their L1 in order to successfully retrieve words in the L2. Based on these models, we expected that lower proficiency learners would more strongly activate IC areas than areas associated with semantic retrieval when processing their L2 compared with their L1. Higher proficiency learners, by contrast, would utilize networks focused on semantic/conceptual retrieval rather than inhibitory control. Additionally, we expected individual differences in the non-linguistic domains of working memory (WM) and IC to moderate these proficiency-based differences, such that high WM/high IC participants would use show less activation in control areas than their proficiency-matched peers. To examine this, participants complete measures of proficiency, WM, and IC that were regressed on BOLD responses to a lexical decision task. Our results largely supported our predictions, and are discussed in light of the IC and RHM models, as well as brain-based models of L2 processing.