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Error-related negativity (ERN) and ‘hot’ executive function in bilingual and monolingual preschoolers

Published online by Cambridge University Press:  20 January 2020

Srishti Nayak Open the ORCID record for Srishti Nayak [Opens in a new window]  and
Amanda R. Tarullo
Srishti Nayak*
Affiliation:
Princeton University, Princeton Writing Program Boston University, Department of Psychological & Brain Sciences
Amanda R. Tarullo
Affiliation:
Boston University, Department of Psychological & Brain Sciences
*
Address for correspondence: Srishti Nayak E-mail: [email protected]
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Abstract

Early regular experience with dual-language management is thought to shape executive function (EF) circuitry during development. However, previous investigations of bilingual children's EF have largely focused on behavioral measures, or on cognitive aspects of EF. The first part of this study compared monolingual and bilingual preschoolers’ performance on more purely cognitive and more affective versions of a card-sort task, and the second part investigated Error-related negativity (ERN) event-related potential (ERP) waveforms to understand error-awareness mechanisms underlying task performance. Behavioral results showed bilingual advantages in reaction times but not accuracy, and interaction effects of language background, level of challenge, and affective/motivational salience on reaction times. Electrophysiological results revealed smaller ERN peak amplitudes in bilinguals compared to monolinguals in frontal and frontocentral midline regions. Results highlight that bilingualism may shape motivational mechanisms and neural learning mechanisms such as error-detection, such that bilinguals may be less focused on their errors.

Keywords

bilingualismexecutive function (EF)cognitive developmentelectroencephalography (EEG)error-related negativity (ERN)
Type
Research Article
Information
Bilingualism: Language and Cognition , Volume 23 , Special Issue 4: Interpreting: A window into bilingual processing , August 2020 , pp. 897 - 908
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Copyright
Copyright © Cambridge University Press 2020

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