EEG investigation of morphologically complex word processing in a second language

ECS 2022/2023
(PI Yoonsang Song, Co-I Youngah Do, Ouyang Guang and Nan Jiang)
Early Career Scheme (ECS), University Grants Council (UGC), Hong Kong
Amount: 652,812 HKD

Abstract
This electroencephalography (EEG) research explores whether there are notable qualitative and fundamental differences between first language (L1) and second language (L2) processing of bi- and multi-morphemic words. The current literature shows that the answer to this question remains far from settled, and thus, the PI proposes to conduct a series of experiments to address this gap. Specifically, this proposed research project focuses on the L2 development of the internal morphological structure of derived words (e.g., [un-[[kind]-ness]]), asking the question of whether L2 learners can eventually develop such morphological structure. Previous studies on the L2 representation of derived words are scarce, as derivational morphology has been largely overlooked by most of the L2 research community, with much more attention being paid to inflectional morphology. Furthermore, the results of these studies are even apparently inconsistent. Last but not least, neurophysiological aspects of the L2 representation of derived words still remain largely unexplored, as most of the studies only relied on behavioral methods. The current literature shows that in real-time lexical comprehension, native speakers construct structurally detailed representations for words that consist of more than one morpheme. In a series of experiments, this proposed study tests whether L2 learners, at least highly proficient ones, are able to build such representations like native speakers, or their representations lack detailed structural information, and thus, their processing relies more heavily on non-structural (e.g., semantic, orthographic) information than native speakers’. The current study exploits the advantages of EEG, which has been found highly effective in finding distinctive neuronal signatures for structural processing, such as morphological decomposition and unification. Using both of the two most reliable EEG analysis techniques, namely, the ERP and time-frequency analysis, this study first explores the neuronal signatures of structure-driven word processing in native speakers’ EEG data. Once these signatures are established, the study will investigate whether L2 word processing manifests these signatures as clearly as L1 processing. The results of this research will enhance our understanding of the nature of L2 morphological processing and representations, making valuable contributions to L2 processing and acquisition theories. Our language processing data are also expected to provide beneficial insights into second language education in the long run, as they shed light on the question of why L2 learners struggle with certain domains of language.