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dc.contributor.authorBermúdez Margaretto, Beatriz
dc.contributor.authorBeltrán Guerrero, David 
dc.contributor.authorCuetos, Fernando
dc.contributor.authorDomínguez Martínez, Alberto 
dc.contributor.otherPsicología Cognitiva, Social y Organizacional
dc.date.accessioned2024-01-19T21:05:08Z
dc.date.available2024-01-19T21:05:08Z
dc.date.issued2018
dc.identifier.urihttp://riull.ull.es/xmlui/handle/915/35475
dc.description.abstractThe contribution of two different training contexts to online, gradual lexical acquisition was investigated by event-related potentials (ERPs) elicited by new, word-like stimuli. Pseudowords were repeatedly preceded by a picture representing a well-known object (semantic-associative training context) or by a hash mark (non-associative training context). The two training styles revealed differential effects of repetition in both behavioral and ERPs data. Repetition of pseudowords not associated with any stimulus gradually enhanced the late positive component (LPC) as well as speeded lexical categorization of these stimuli, suggesting the formation of episodic memory traces. However, repetition under the semantic-associative context caused higher reduction in N400 component and categorization latencies. This result suggests the facilitation in the lexico-semantic processing of pseudowords as a consequence of their progressive associations to picture-concepts, going beyond the visual memory trace that is generated under the non-associative context.en
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.relation.ispartofseriesFrontiers in Human Neuroscience, Volume 12 - 2018
dc.rightsLicencia Creative Commons (Reconocimiento-No comercial-Sin obras derivadas 4.0 Internacional)
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.es_ES
dc.titleBrain signatures of new (pseudo-) words: Visual repetition in associative and non-associative contexts
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.3389/fnhum.2018.00354
dc.subject.keywordcluster-based permutation analysis
dc.subject.keywordLPC
dc.subject.keywordN400
dc.subject.keywordreading
dc.subject.keywordregression-based ERPs


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