A neurocomputational account of taxonomic responding and fast mapping in early word learning.

  title={A neurocomputational account of taxonomic responding and fast mapping in early word learning.},
  author={Julien Mayor and Kim Plunkett},
  journal={Psychological review},
  volume={117 1},
We present a neurocomputational model with self-organizing maps that accounts for the emergence of taxonomic responding and fast mapping in early word learning, as well as a rapid increase in the rate of acquisition of words observed in late infancy. The quality and efficiency of generalization of word-object associations is directly related to the quality of prelexical, categorical representations in the model. We show how synaptogenesis supports coherent generalization of word-object… 

Word learning emerges from the interaction of online referent selection and slow associative learning.

An alternative in which referent selection is an online process and independent of long-term learning is presented, which suggests that association learning buttressed by dynamic competition can account for much of the literature and suggests more sophisticated ways of describing the interaction between situation- and developmental-time processes.

An investigation of fast and slow mapping

Children learn words astonishingly skilfully. Even infants can reliably “fast map” novel category labels to their referents without feedback or supervision (Carey & Bartlett, 1978; Houston-Price,

Pushing the envelope of associative learning: Internal representations and dynamic competition transform association into development

The authors present a model that embeds association learning in a richer system, which includes both internal representations to and real-time competition that enable it to select the referent of novel and familiar words.

In Learning Nouns and Adjectives Remembering Matters: A Cortical Model

Results of the model can explain what has emerged in a series of developmental research studies in early language acquisition, and can account for the different developmental patterns followed by children in acquiring nouns and adjectives, by perceptually driven associational learning processes at the synaptic level.

Modeling Cross-Modal Interactions in Early Word Learning

This model of word learning based on interacting self-organizing maps that represent the auditory and visual modalities, respectively, argues that the learning mechanism introduced in this model could play a role in the facilitation of infants' categorization through verbal labeling.

Interactions in the development of skilled word learning in neural networks and toddlers

A computational model is used to investigate how the shape bias influences novel noun generalization to other types of items, and to guide a behavioral study of this effect in children, providing a novel view of biased word learning over time.

Computational Exploration of Lexical Development in Down Syndrome

A neural network model is presented that instantiates notions from neurophysiological studies to account for the disparities between lexical comprehension and production in DS and shows that an atypical LTP/LTD balance affects comprehension andproduction differently in an associative model of lexical development.

Decoding the Formation of New Semantics: MVPA Investigation of Rapid Neocortical Plasticity during Associative Encoding through Fast Mapping

It is proposed that fast mapping promotes incidental rapid integration of new associations into existing neocortical semantic networks by activating related, nonoverlapping conceptual knowledge, while hippocampal involvement is less predictive of this kind of learning.



The Emergence of Words: Attentional Learning in Form and Meaning

An associative exemplar-based model is presented that accounts for the improvement at word learning without a change in mechanism, and explains these improvements in terms of increased attention to relevant aspects of form and meaning, which reduces memory interference.

Dynamic Self-Organization and Early Lexical Development in Children

This study presents a self-organizing connectionist model of early lexical development called DevLex-II, based on the earlier DevLex model, which can simulate a variety of empirical patterns in children's acquisition of words.

Early lexical development in a self-organizing neural network

Structure and deterioration of semantic memory: a neuropsychological and computational investigation.

The authors present a parallel distributed processing implementation of this theory, in which semantic representations emerge from mechanisms that acquire the mappings between visual representations of objects and their verbal descriptions, to understand the structure of impaired performance in patients with selective and progressive impairments of conceptual knowledge.

The role of shape similarity in toddlers' lexical extensions

The taxonomic assumption, or noun-category bias, is thought to facilitate word learning by focusing children’ s attention on taxonomic categories as likely candidates for word meanings. Three

From the lexicon to expectations about kinds: a role for associative learning.

Nine simulations and behavioral experiments tested the hypothesis that generalized expectations about how solid and nonsolid things are named arise from the correlations characterizing early learned noun categories, and formed generalized expectations that match children's performances in the novel noun generalization task in the very different languages of English and Japanese.

Weaving a Lexicon

The studies in Weaving a Lexicon make a significant contribution to the growing field of lexical acquisition by considering the multidimensional way in which infants and children acquire the lexicon

Semantic Cognition: A Parallel Distributed Processing Approach

The authors propose that performance in semantic tasks arises through the propagation of graded signals in a system of interconnected processing units, and show how a simple computational model proposed by Rumelhart exhibits a progressive differentiation of conceptual knowledge, paralleling aspects of cognitive development seen in the work of Frank Keil and Jean Mandler.

Rapid Word Learning in 13- and 18-Month-Olds.

A number of theorists have argued that the productive naming explosion results from advances in abilities that underlie language learning (e.g., the realization that words are symbols, changes in

Lexical Neighborhoods and the Word-Form Representations of 14-Month-Olds

Evidence is presented indicating that, in fact, the lexical representations of 14- and 15-month-olds are encoded in fine detail, even when this detail is not functionally necessary for distinguishing similar words in the infant's vocabulary.