In this thesis, I use a combination of simulations and empirical data to demonstrate that a small set of structural and functional principles - the basic tenets of predictive coding theory - succinctly accounts for a very wide range of properties in the language processing system. Predictive coding approximates hierarchical Bayesian inference via…

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…

In this article, I explore how connectionism might expand its role in second language acquisition (SLA) theory by showing how some symbolic models of bilingual and second language lexical memory can be reduced to a biologically realistic (i.e., neurally plausible) connectionist model. This integration or hybridization of the two models follows the…

Goldberg's (1995) recognition that, in addition to various word-level constructions, sentences also instantiate meaningful argument structure constructions enables a non-polysemy-based analysis of various verb 'alternations' (Levin 1993). In such an analysis, meaning variations associated with the use of the same verb in different argument…

A central topic in cognitive neuroscience concerns the representation of concepts and the specific neural mechanisms that mediate conceptual knowledge. Recently proposed modal theories assert that concepts are grounded on the integration of multimodal, distributed representations. The aim of the present work is to complement the available…

This dissertation develops analytical tools which enable rigorous evaluation of competing syllabic parses on the basis of temporal patterns in speech production data. The data come from the articulographic tracking of fleshpoints on target speech organs, e.g., tongue, lips, jaw, in experiments with native speakers of American English and Moroccan…

It is argued that pessimistic assessments of the adequacy of artificial neural networks (ANNs) for natural language processing (NLP) on the grounds that they have a finite state architecture are unjustified, and that their adequacy in this regard is an empirical issue. First, arguments that counter standard objections to finite state NLP on the…

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…

Focuses on Elman's (1990) statistical analyses of the hidden unit activation patterns in his simple recurrent network on sentence prediction, first to highlight the feasibility of such analyses and then to show how connectionist explanations contribute to the development of effective explanatory theories. Argues for the evolutionary nature of…

This paper describes and illustrates a simulation model for the processing of grammatical elements in a sentence, focusing on one aspect of sentence comprehension: the assignment of the constituent elements of a sentence to the correct thematic case roles. The model addresses questions about sentence processing from a perspective very different…