How do children learn the meaning of words like "pretty" and "tall," which are not only gradable and context dependent (Kennedy & McNally 2005), but encode speaker subjectivity? Despite their complex semantics (Stephenson 2007; Lasersohn 2009; Bylinina 2014), these and other adjectives like them, are some of the most…

Acquiring the correct meanings of words expressing quantities ("seven, most") and qualities ("red, spotty") present a challenge to learners. Understanding how children succeed at this requires understanding, not only of what kinds of data are available to them, but also the biases and expectations they bring to the learning…

Purpose: In this study, the authors used neural network modeling to investigate the possible mechanistic basis of developmental language delay and to test the viability of the hypothesis that persisting delay and resolving delay lie on a mechanistic continuum with normal development. Method: The authors used a population modeling approach to study…

According to the age-of-acquisition hypothesis, words acquired early in life are processed faster and more accurately than words acquired later. Connectionist models have begun to explore the influence of the age/order of acquisition of items (and also their frequency of encounter). This study attempts to reconcile two different methodological and…

This article addresses issues in embodied sentence processing from a "cognitive neural systems" approach that combines analysis of the behavior in question, analysis of the known neurophysiological bases of this behavior, and the synthesis of a neuro-computational model of embodied sentence processing that can be applied to and tested in the…

Statistical learning mechanisms play an important role in theories of language acquisition and processing. Recurrent neural network models have provided important insights into how these mechanisms might operate. We examined whether such networks capture two key findings in human statistical learning. In Simulation 1, a simple recurrent network…

A central issue in cognitive neuroscience today concerns how distributed neural networks in the brain that are used in language learning and processing can be involved in non-linguistic cognitive sequence learning. This issue is informed by a wealth of functional neurophysiology studies of sentence comprehension, along with a number of recent…

In this paper we discuss a computational cognitive model of children's poor performance on pronoun interpretation (the so-called Delay of Principle B Effect, or DPBE). This cognitive model is based on a theoretical account that attributes the DPBE to children's inability as hearers to also take into account the speaker's perspective. The cognitive…

Prior research has established an executive function advantage among bilinguals as compared to monolingual peers. These non-linguistic cognitive advantages are largely assumed to result from the experience of managing two linguistic systems. However, the possibility remains that the relationship between bilingualism and executive function is…

Many theories of language production and perception assume that in the normal course of processing a word, additional non-target words (lexical neighbors) become active. The properties of these neighbors can provide insight into the structure of representations and processing mechanisms in the language processing system. To infer the properties of…

Recent work addressing the phenomenon of perceptual simulation offers new and exciting avenues of investigating how to model knowledge representation. From the perspective of language, the simulation approach has given rise to new impetus to work on models of language understanding (e.g., Zwaan, 2004, and references therein), and provides a way of…

The forms of words as they appear in text and speech are central to theories and models of lexical processing. Nonetheless, current methods for simulating their learning and representation fail to approach the scale and heterogeneity of real wordform lexicons. A connectionist architecture termed the "sequence encoder" is used to learn…

Examines the implications of connectionist models of cognition for second-language theory, in which all knowledge is embodied in a network of simple processing units joined by connections that are strengthened or weakened in response to regularities in input patterns. A connectionist framework is proposed within which hypotheses about…

The Wernicke-Lichtheim-Geschwind (WLG) theory of the neurobiological basis of language is of great historical importance, and it continues to exert a substantial influence on most contemporary theories of language in spite of its widely recognized limitations. Here, we suggest that neurobiologically grounded computational models based on the WLG…

Variations in the amount and nature of early language to which children are exposed have been linked to their subsequent ability (e.g. Huttenlocher, Haight, Bryk, Seltzer & Lyons, 1991; Hart & Risley, 1995). In three computational simulations, we explore how differences in linguistic experience can explain differences in word learning ability due…