English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Monitoring of language selection errors in switching: Not all about conflict

MPS-Authors
/persons/resource/persons226941

Zheng,  Xiaochen
Donders Institute for Brain, Cognition and Behaviour, External Organizations;
International Max Planck Research School for Language Sciences, MPI for Psycholinguistics, Max Planck Society;

External Resource

data
(Supplementary material)

Fulltext (public)
Supplementary Material (public)

journal.pone.0200397.s001.docx
(Supplementary material), 18KB

journal.pone.0200397.s002.docx
(Supplementary material), 18KB

journal.pone.0200397.s003.docx
(Supplementary material), 17KB

Citation

Zheng, X., Roelofs, A., Farquhar, J., & Lemhöfer, K. (2018). Monitoring of language selection errors in switching: Not all about conflict. PLoS One, 13(11): e0200397. doi:10.1371/journal.pone.0200397.


Cite as: http://hdl.handle.net/21.11116/0000-0002-9646-6
Abstract
Although bilingual speakers are very good at selectively using one language rather than another, sometimes language selection errors occur. To investigate how bilinguals monitor their speech errors and control their languages in use, we recorded event-related potentials (ERPs) in unbalanced Dutch-English bilingual speakers in a cued language-switching task. We tested the conflict-based monitoring model of Nozari and colleagues by investigating the error-related negativity (ERN) and comparing the effects of the two switching directions (i.e., to the first language, L1 vs. to the second language, L2). Results show that the speakers made more language selection errors when switching from their L2 to the L1 than vice versa. In the EEG, we observed a robust ERN effect following language selection errors compared to correct responses, reflecting monitoring of speech errors. Most interestingly, the ERN effect was enlarged when the speakers were switching to their L2 (less conflict) compared to switching to the L1 (more conflict). Our findings do not support the conflict-based monitoring model. We discuss an alternative account in terms of error prediction and reinforcement learning.