Literature DB >> 33513707

Perceptual Connectivity Influences Toddlers' Attention to Known Objects and Subsequent Label Processing.

Ryan E Peters1, Justin B Kueser2, Arielle Borovsky2.   

Abstract

While recent research suggests that toddlers tend to learn word meanings with many "perceptual" features that are accessible to the toddler's sensory perception, it is not clear whether and how building a lexicon with perceptual connectivity supports attention to and recognition of word meanings. We explore this question in 24-30-month-olds (N = 60) in relation to other individual differences, including age, vocabulary size, and tendencies to maintain focused attention. Participants' looking to item pairs with high vs. low perceptual connectivity-defined as the number of words in a child's lexicon sharing perceptual features with the item-was measured before and after target item labeling. Results revealed pre-labeling attention to known items is biased to both high- and low-connectivity items: first to high, and second, but more robustly, to low-connectivity items. Subsequent object-label processing was also facilitated for high-connectivity items, particularly for children with temperamental tendencies to maintain focused attention. This work provides the first empirical evidence that patterns of shared perceptual features within children's known vocabularies influence both visual and lexical processing, highlighting the potential for a newfound set of developmental dependencies based on the perceptual/sensory structure of early vocabularies.

Entities:  

Keywords:  attentional biases; language development; lexicosemantic development; perceptual knowledge; semantic networks; shared features; visual object processing; word processing

Year:  2021        PMID: 33513707      PMCID: PMC7912090          DOI: 10.3390/brainsci11020163

Source DB:  PubMed          Journal:  Brain Sci        ISSN: 2076-3425


  58 in total

1.  Measurement of fine-grained aspects of toddler temperament: the early childhood behavior questionnaire.

Authors:  Samuel P Putnam; Maria A Gartstein; Mary K Rothbart
Journal:  Infant Behav Dev       Date:  2006-03-02

2.  On the nature and scope of featural representations of word meaning.

Authors:  K McRae; V R de Sa; M S Seidenberg
Journal:  J Exp Psychol Gen       Date:  1997-06

3.  Twenty-Five Years Using the Intermodal Preferential Looking Paradigm to Study Language Acquisition: What Have We Learned?

Authors:  Roberta Michnick Golinkoff; Weiyi Ma; Lulu Song; Kathy Hirsh-Pasek
Journal:  Perspect Psychol Sci       Date:  2013-05

4.  Development of lexical-semantic language system: N400 priming effect for spoken words in 18- and 24-month old children.

Authors:  Pia Rämä; Louah Sirri; Josette Serres
Journal:  Brain Lang       Date:  2013-02-26       Impact factor: 2.381

5.  Attention and word learning in toddlers who are late talkers.

Authors:  Michelle Macroy-Higgins; Elizabeth A Montemarano
Journal:  J Child Lang       Date:  2016-09

Review 6.  Temperament, speech and language: an overview.

Authors:  Edward G Conture; Ellen M Kelly; Tedra A Walden
Journal:  J Commun Disord       Date:  2012-11-19       Impact factor: 2.288

7.  The Associative Structure of Language: Contextual Diversity in Early Word Learning.

Authors:  Thomas T Hills; Josita Maouene; Brian Riordan; Linda B Smith
Journal:  J Mem Lang       Date:  2010-10-01       Impact factor: 3.059

8.  Developmental differences in the effects of phonological, lexical and semantic variables on word learning by infants.

Authors:  Holly L Storkel
Journal:  J Child Lang       Date:  2008-09-02

9.  Categorical structure among shared features in networks of early-learned nouns.

Authors:  Thomas T Hills; Mounir Maouene; Josita Maouene; Adam Sheya; Linda Smith
Journal:  Cognition       Date:  2009-07-02

10.  Vocabulary size and structure affects real-time lexical recognition in 18-month-olds.

Authors:  Arielle Borovsky; Ryan E Peters
Journal:  PLoS One       Date:  2019-07-11       Impact factor: 3.240

View more
  1 in total

1.  Moving towards accurate and early prediction of language delay with network science and machine learning approaches.

Authors:  Arielle Borovsky; Donna Thal; Laurence B Leonard
Journal:  Sci Rep       Date:  2021-04-14       Impact factor: 4.379

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.