Eliana Colunga

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

In the novel noun generalization task, 2 1/2-year-old children display generalized expectations about how solid and nonsolid things are named, extending names for never-before-encountered solids by shape and for never-before-encountered nonsolids by material. This distinction between solids and nonsolids has been interpreted in terms of an ontological distinction between objects and substances. Nine simulations and behavioral experiments tested the hypothesis that these expectations arise from the correlations characterizing early learned noun categories. In the simulation studies, connectionist networks were trained on noun vocabularies modeled after those of children. These networks formed generalized expectations about solids and nonsolids that match childrens performances in the novel noun generalization task in the very different languages of English and Japanese. The simulations also generate new predictions supported by new experiments with children. Implications are discussed in terms of childrens development of distinctions between kinds of categories and in terms of the nature of this knowledge.

Knowledge as Process: Contextually-Cued Attention and Early Word Learning

Learning depends on attention. The processes that cue attention in the moment dynamically integrate learned regularities and immediate contextual cues. This paper reviews the extensive literature on cued attention and attentional learning in the adult literature and proposes that these fundamental processes are likely significant mechanisms of change in cognitive development. The value of this idea is illustrated using phenomena in children novel word learning.

Knowledge Embedded in Process: The Self-Organization of Skilled Noun Learning.

Young childrens skilled generalization of newly learned nouns to new instances has become the battleground for two very different approaches to cognition. This debate is a proxy for a larger dispute in cognitive science and cognitive development: cognition as rule-like amodal propositions, on the one hand, or as embodied, modal, and dynamic processes on the other. After a brief consideration of this theoretical backdrop, we turn to the specific task set before us: an overview of the Attentional Learning Account (ALA) of childrens novel noun generalizations, the constrained set of experimental results to be explained, and our explanation of them. We conclude with a consideration of what all of this implies for a theory of cognitive development.

More than a matter of getting 'unstuck': flexible thinkers use more abstract representations than perseverators

Why do people perseverate, repeating prior behaviours that are no longer appropriate? Many accounts point to isolated deficits in processes such as inhibition or attention. We instead posit a fundamental difference in rule representations: flexible switchers use active representations that rely on later-developing prefrontal cortical areas and are more abstract, whereas perseverators use latent representations that rely on earlier-developing posterior cortical and subcortical areas and are more stimulus-specific. Thus, although switchers and perseverators should apply the rules they use to familiar stimuli equally reliably, perseverators should show unique limitations in generalizing their rules to novel stimuli, a process that requires abstract representations. Two behavioural experiments confirmed this counterintuitive prediction early in development. Three-year-old children sorted cards by one rule, were asked to switch to another rule, and then were asked simply to continue their behaviour, with novel cards. Perseverators applied the rule they were using (the first rule) just as reliably as switchers applied the rule they were using (the second rule) with familiar cards; however, only switchers generalized their rule to novel cards. This finding supports an early link between active representations that support switching and abstract representations that support generalization. We interpret this synergy in terms of prefrontal cortical development.

Bilingual and Monolingual Children Attend to Different Cues When Learning New Words

The way in which children learn language can vary depending on their language environment. Previous work suggests that bilingual children may be more sensitive to pragmatic cues from a speaker when learning new words than monolingual children are. On the other hand, monolingual children may rely more heavily on object properties than bilingual children do. In this study we manipulate these two sources of information within the same paradigm, using eye gaze as a pragmatic cue and similarity along different dimensions as an object cue. In the crucial condition, object and pragmatic cues were inconsistent with each other. Our results showed that in this ambiguous condition monolingual children attend more to object property cues whereas bilingual children attend more to pragmatic cues. Control conditions showed that monolingual children were sensitive to eye gaze and bilingual children were sensitive to similarity by shape; it was only when the cues were inconsistent that children’s preference for one or the other cue was apparent. Our results suggest that children learn to weigh different cues depending on their relative informativeness in their environment.

Language Networks as Models of Cognition: Understanding Cognition through Language

Language is inherently cognitive and distinctly human. Separating the object of language from the human mind that processes and creates language fails to capture the full language system. Linguistics traditionally has focused on the study of language as a static representation, removed from the human mind. Network analysis has traditionally been focused on the properties and structure that emerge from network representations. Both disciplines could gain from looking at language as a cognitive process. In contrast, psycholinguistic research has focused on the process of language without committing to a representation. However, by considering language networks as approximations of the cognitive system we can take the strength of each of these approaches to study human performance and cognition as related to language. This paper reviews research showcasing the contributions of network science to the study of language. Specifically, we focus on the interplay of cognition and language as captured by a network representation. To this end, we review different types of language network representations before considering the influence of global level network features. We continue by considering human performance in relation to network structure and conclude with theoretical network models that offer potential and testable explanations of cognitive and linguistic phenomena.

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

Development is about change over time. Computational models have provided insights into the developmental changes seen in different cognitive phenomena, including within the domain of word learning. The present paper uses a computational model in tandem with a behavioral study to make and test predictions about the interdependencies between the emergences of different word learning biases. The 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. The results provide a novel view of biased word learning over time, and suggest that emerging biases interact with each other and influence how networks and children attend to different kinds of information over time.

The Cambridge Handbook of Psycholinguistics: Developing Categories and Concepts

The literature on concept development is highly contentious because there is a lot at stake. The processes that give rise to categories are at the very core of how we understand human cognition. In broad strokes, the debate is about whether categories reflect internal representations that are highly stable symbolic proposition-like and manipulated via logical operators or, whether they are probabilistic, context-dependent, and derived from bundles of correlated features and ordinary processes of perceiving and The literature appears to cycle through these two classes of accounts, advancing with each pass through but never quite leaving these two general points of view. Many of the contentious issues in the developmental literature on concepts and categories are variants of this debate. Accordingly, this review begins with a brief history of theories of categories. This is as history of back-and-forth transitions between a focus on more the more stable and the more probabilistic aspects of categories and it is a debate that is not resolved. However, by either view, categories result from internal representations that capture the structure in the world. Accordingly, the review of the developmental literature is organized with respect to recent advances in understanding outside-the-mind factors that organize and recruit the cognitive processes that create categories: the statistical regularities in the learning environment, the cognitive tasks and the nested time scales of the internal processes they recruit, and the body which is the interface between the external world and cognition. Back – and – forth theories.

Words can slow down category learning

Words have been shown to influence many cognitive tasks, including category learning. Most demonstrations of these effects have focused on instances in which words facilitate performance. One possibility is that words augment representations, predicting an across the-board benefit of words during category learning. We propose that words shift attention to dimensions that have been historically predictive in similar contexts. Under this account, there should be cases in which words are detrimental to performance. The results from two experiments show that words impair learning of object categories under some conditions. Experiment 1 shows that words hurt performance when learning to categorize by texture. Experiment 2 shows that words also hurt when learning to categorize by brightness, leading to selectively attending to shape when both shape and hue could be used to correctly categorize stimuli. We suggest that both the positive and negative effects of words have developmental origins in the history of word usage while learning categories. [corrected]

Beyond modeling abstractions: learning nouns over developmental time in atypical populations and individuals.

Connectionist models that capture developmental change over time have much to offer in the field of language development research. Several models in the literature have made good contact with developmental data, effectively captured behavioral tasks, and accurately represented linguistic input available to young children. However, fewer models of language development have truly captured the process of developmental change over time. In this review paper, we discuss several prominent connectionist models of early word learning, focusing on semantic development, as well as our recent work modeling the emergence of word learning biases in different populations. We also discuss the potential of these kinds of models to capture children’s language development at the individual level. We argue that a modeling approach that truly captures change over time has the potential to inform theory, guide research, and lead to innovations in early language intervention.