A Simple Computational Model of Semantic Priming in 18-Month-Olds.

Cogn Sci

Department of Computer Science and Center for Logic, Language and Cognition (LLC), University of Turin.

Published: October 2024

AI Article Synopsis

  • - The proposed computational model aims to explain how infants around 18 months develop their understanding of language by looking at two main aspects: taxonomic priming (grouping similar words) and associative priming (linking words that frequently occur together).
  • - Taxonomic priming is linked to semantic feature overlap, while associative priming is explained through Hebbian links based on word co-occurrence.
  • - The model addresses why taxonomic priming appears later than associative priming, suggesting that feature overlap emerges as infants learn, and it successfully replicates data from experiments examining how the timing between words affects these priming effects.

Article 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.

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Source
http://dx.doi.org/10.1111/cogs.13499DOI Listing

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