Evidence map›Paper›PMID 33267883›Full record

ArticleBehavioral and brain functions : BBF2020

Rapid acquisition of novel written word-forms: ERP evidence.

Beatriz Bermúdez-Margaretto, Yury Shtyrov, David Beltrán, Fernando Cuetos, Alberto Domínguez

Abstract read
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Article in Behavioral and brain functions : BBF, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Beatriz Bermúdez-MargarettoCentre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russian Federation. bermudezmargaretto@gmail.com.ORCID http://orcid.org/0000-0002-3687-3634
Yury ShtyrovCentre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russian Federation.
David BeltránInstituto Universitario de Neurociencia (IUNE) and Facultad de Psicología, Universidad de La Laguna, Tenerife, Spain.
Fernando CuetosFacultad de Psicología, Universidad de Oviedo, Oviedo, Spain.
Alberto DomínguezInstituto Universitario de Neurociencia (IUNE) and Facultad de Psicología, Universidad de La Laguna, Tenerife, Spain.

Funding

Russian Academy Excellence Project '5-100'
6 · The paper itself

Abstract

backgroundNovel word acquisition is generally believed to be a rapid process, essential for ensuring a flexible and efficient communication system; at least in spoken language, learners are able to construct memory traces for new linguistic stimuli after just a few exposures. However, such rapid word learning has not been systematically found in visual domain, with different confounding factors obscuring the orthographic learning of novel words. This study explored the changes in human brain activity occurring online, during a brief training with novel written word-forms using a silent reading task

resultsSingle-trial, cluster-based random permutation analysis revealed that training caused an extremely fast (after just one repetition) and stable facilitation in novel word processing, reflected in the modulation of P200 and N400 components, possibly indicating rapid dynamics at early and late stages of the lexical processing. Furthermore, neural source estimation of these effects revealed the recruitment of brain areas involved in orthographic and lexico-semantic processing, respectively.

conclusionsThese results suggest the formation of neural memory traces for novel written word-forms after a minimal exposure to them even in the absence of a semantic reference, resembling the rapid learning processes known to occur in spoken language.

Indexed as

ReadingAdolescentAdultBrainCluster AnalysisElectroencephalographyEvoked PotentialsFemaleHumansLearningMaleMemoryMental ProcessesSemanticsVerbal LearningYoung AdultCluster-based random permutation analysisERP methodologyN400P200Word learning

Identifiers

PMID33267883
PMCPMC7713216

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.