A Simple Computational Model of Semantic Priming in 18‐Month‐Olds

We propose a simple computational model that describes potential mechanisms underlying the organization and development of the lexical-semantic system in 18-month-old infants. We focus on two independent aspects: (i) on potential mechanisms underlying the development of taxonomic and associative priming, and (ii) on potential mechanisms underlying the effect of Inter Stimulus Interval on these priming effects. Our model explains taxonomic priming between words by semantic feature overlap, whereas associative priming between words is explained by Hebbian links between semantic representations derived from co-occurrence relations between words (or their referents). From a developmental perspective, any delay in the emergence of taxonomic priming compared to associative priming during infancy seems paradoxical since feature overlap per se need not be learned. We address this paradox in the model by showing that feature overlap itself is an emergent process. The model successfully replicates infant data related to Inter Stimulus Interval effects in priming experiments and makes testable predictions.

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Publication Details

Journal
Cognitive Science
Published
2024-10-01
DOI
https://doi.org/10.1111/cogs.13499
Primary Topic
Child and Animal Learning Development
Type
article
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article

A Simple Computational Model of Semantic Priming in 18‐Month‐Olds

Valentina Gliozzi
Cognitive Science
Child and Animal Learning Development
article

A Simple Computational Model of Semantic Priming in 18‐Month‐Olds

Valentina Gliozzi
article en

Abstract

We propose a simple computational model that describes potential mechanisms underlying the organization and development of the lexical-semantic system in 18-month-old infants. We focus on two independent aspects: (i) on potential mechanisms underlying the development of taxonomic and associative priming, and (ii) on potential mechanisms underlying the effect of Inter Stimulus Interval on these priming effects. Our model explains taxonomic priming between words by semantic feature overlap, whereas associative priming between words is explained by Hebbian links between semantic representations derived from co-occurrence relations between words (or their referents). From a developmental perspective, any delay in the emergence of taxonomic priming compared to associative priming during infancy seems paradoxical since feature overlap per se need not be learned. We address this paradox in the model by showing that feature overlap itself is an emergent process. The model successfully replicates infant data related to Inter Stimulus Interval effects in priming experiments and makes testable predictions.

Cognitive ScienceVol. 48(10)
University of Turin (IT)
Openalex Percentile: Top 78%
Child and Animal Learning Development
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A Simple Computational Model of Semantic Priming in 18‐Month‐Olds — Valentina Gliozzi · Cognitive Science (2024) | TGRS Research Map | TGRS