4.7 Article

The interplay between domain-general and domain-specific mechanisms during the time-course of verbal associative learning: An event-related potential study

Journal

NEUROIMAGE
Volume 242, Issue -, Pages -

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2021.118443

Keywords

Verbal associative learning; Memory; EEG; N400; Vocabulary acquisition

Funding

  1. Brain Train Research Center of Excel-lence at the Abo Akademi University
  2. Ministerio de Economia, Industria y Competitividad [PSI2015-69132-P, PGC2018-099859-B-I00]
  3. Academyof Finland [260276, 323251]
  4. French government [ANR-16-CONV-0002]
  5. Excellence Initiative of Aix-Marseille University (A*MIDEX)

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The study explores the temporal brain dynamics of explicit verbal associative learning between unfamiliar items in humans. It found that N400 amplitude modulations reflect the emergence of novel lexical traces even without semantic information, suggesting a balance between domain-general and language-specific mechanisms in specific word learning steps.
Humans continuously learn new information. Here, we examined the temporal brain dynamics of explicit verbal associative learning between unfamiliar items. In the first experiment, 25 adults learned object-pseudoword associations during a 5-day training program allowing us to track the N400 dynamics across learning blocks within and across days. Successful learning was accompanied by an initial frontal N400 that decreased in amplitude across blocks during the first day and shifted to parietal sites during the last training day. In Experiment 2, we replicated our findings with 38 new participants randomly assigned to a consistent learning or an inconsistent learning group. The N400 amplitude modulations that we found, both within and between learning sessions, are taken to reflect the emergence of novel lexical traces even when learning concerns items for which no semantic information is provided. The shift in N400 topography suggests that different N400 neural generators may contribute to specific word learning steps through a balance between domain-general and language-specific mechanisms.

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