Elmer, StefanBesson, MireilleRodríguez Fornells, Antoni2022-12-162022-12-162022-12-011872-7697https://hdl.handle.net/2445/191645Human beings continuously make use of learned associations to generate predictions about future occurrences in the environment. Such memory-related predictive processes provide a scaffold for learning in that mental rep-resentations of foreseeable events can be adjusted or strengthened based on a specific outcome. Learning the meaning of novel words through picture-word associations constitutes a prime example of associative learning because pictures preceding words can trigger word prediction through the pre-activation of the related mne-monic representations. In the present electroencephalography (EEG) study, we used event-related potentials (ERPs) to compare neural indices of word pre-activation between a word learning condition with maximal prediction likelihood and a non-learning control condition with low prediction. Results revealed that prediction -related N400 amplitudes in response to pictures decreased over time at central electrodes as a function of word learning, whereas late positive component (LPC) amplitudes increased. Notably, N400 but not LPC changes were also predictive of word learning performance, suggesting that the N400 component constitutes a sensitive marker of word pre-activation during associative word learning.11 p.application/pdfengcc by (c) Elmer, Stefan et al., 2022http://creativecommons.org/licenses/by/3.0/es/AprenentatgeElectrofisiologiaLearningElectrophysiologyinfo:eu-repo/semantics/article2022-12-07info:eu-repo/semantics/openAccess36167179