Structural priming in language production is a tendency to recreate a recently uttered syntactic structure in different words. This tendency can be seen independent of specific lexical items, thematic roles, or word sequences. Two alternative proposals about the mechanism behind structural priming include (a) short-term activation from a memory representation of a priming structure and (b) longer term adaptation within the cognitive mechanisms for creating sentences, as a form of procedural learning. Two experiments evaluated these hypotheses, focusing on the persistence of structural priming. Both experiments yielded priming that endured beyond adjacent sentences, persisting over 2 intervening sentences in Experiment 1 and over 10 in Experiment 2. Although memory may have short-term consequences for some components of this kind of priming, the persisting effects are more compatible with a learning account than a transient memory account. Speakers repeat themselves. Sometimes their repetitions are intentional, made for emphasis or other stylistic and social purposes (Giles & Powesland, 1975; Tannen, 1987), and sometimes they are accidental. They may involve almost

In everyday tasks, selecting actions in the proper sequence requires a continuously updated representation of temporal context. Many existing models address this problem by positing a hierarchy of processing units, mirroring the roughly hierarchical structure of naturalistic tasks themselves. Such an approach has led to a number of difficulties, including a reliance on overly rigid sequencing mechanisms, an inability to account for context sensitivity in behavior, and a failure to address learning. We consider here an alternative framework, according to which the representation of temporal context is facilitated by recurrent connections within a network mapping from environmental inputs to actions. Applying this approach to a specific, and in many ways prototypical, everyday task (coffee-making), we examine its ability to account for several central characteristics of normal and impaired human performance. The model we consider learns to deal flexibly with a complex set of sequencing constraints, encoding contextual information at multiple time-scales within a single, distributed internal representation. Mildly degrading this context representation leads

The most predominant language processing theories have, for some time, been based largely on structured knowledge and relatively simple rules. These symbolic models intentionally segregate syntactic information processing from statistical information as well as semantic, pragmatic, and discourse influences, thereby minimizing the importance of these potential constraints in learning and processing language. While such models have the advantage of being relatively simple and explicit, they are inadequate to account for learning and validated ambiguity resolution phenomena. In recent years, interactive constraint-based theories of sentence processing have gained increasing support, as a growing body of empirical evidence demonstrates early influences of various factors on comprehension performance. Connectionist networks are one form of model that naturally reflect many properties of constraint-based theories, and thus provide a form in which those theories may be instantiated. Unfortunately, most of the connectionist language models implemented until now have involved severe limitations, restricting the phenomena they could address. Comprehension and production models have, by and large, been limited to simple sentences with small vocabularies (cf. St. John & McClelland, 1990). Most models that have addressed the problem of complex, multi-clausal sentence processing have been prediction networks (cf. Elman, 1991; Christiansen & Chater, 1999a). Although a useful component of a language processing system, prediction does not get at the heart of language: the interface between syntax and semantics.

Psycholinguistic research has shown that the influence of abstract syntactic knowledge on performance is shaped by particular sentences that have been experienced. To explore this idea, the authors applied a connectionist model of sentence production to the development and use of abstract syntax. The model makes use of (a) error-based learning to acquire and adapt sequencing mechanisms and (b) meaning–form mappings to derive syntactic representations. The model is able to account for most of what is known about structural priming in adult speakers, as well as key findings in preferential looking and elicited production studies of language acquisition. The model suggests how abstract knowledge and concrete experience are balanced in the development and use of syntax.

The ability to combine words into novel sentences has been used to argue that humans have symbolic language production abilities. Critiques of connectionist models of language often center on the inability of these models to generalize symbolically (Fodor & Pylyshyn, 1988; Marcus, 1998). To address these issues, a connectionist model of sentence production was developed. The model had variables (role-concept bindings) that were inspired by spatial representations (Landau & Jackendoff, 1993). In order to take advantage of these variables, a novel dual-pathway architecture with event semantics is proposed and shown to be better at symbolic generalization than several variants. This architecture has one pathway for mapping message content to words and a separate pathway that enforces sequencing constraints. Analysis of the model’s hidden units demonstrated that the model learned different types of information in each pathway, and that the model’s compositional behavior arose from the combination of these two pathways. The model’s ability to balance symbolic and statistical behavior in syntax acquisition and to model aphasic double dissociations provided independent support for the dual-pathway architecture.

The emphasis in the connectionist sentence-processing literature on distributed representation and emergence of grammar from such systems seems to have prevented connectionists and symbolists alike from recognizing the often close relations between their respective systems. This paper argues that simply recurrent network (SRN) models proposed by Jordan (1990) and Elman (1990) are more directly related to stochastic Part-of-Speech (POS) Taggers than to parsers or grammars as such, while recursive auto-associative memory (RAAM) of the kind pioneered by Pollack and incorporated in many hybrid connectionist parsers since may be useful for grammar induction from a network-based conceptual structure as well as for structure-building. These observations suggest some interesting new directions for connectionist sentence processing research, including more efficient devices for representing finite state machines, and acquisition devices based on a distinctively connectionist grounded conceptual...

This article analyzes the relationship between skill learning and repetition priming, 2 implicit memory phenomena. A number of reports have suggested that skill learning and repetition priming can be dissociated from each other and are therefore based on different mechanisms. The authors present a theoretical analysis showing that previous results cannot be regarded as evidence of a processing dissociation between skill learning and repetition priming. The authors also present a single-mechanism computational model that simulates a specific experimental task and exhibits both skill learning and repetition priming, as well as a number of apparent dissociations between these measures. These theoretical and computational analyses provide complementary evidence that skill learning and repetition priming are aspects of a single underlying mechanism that has the characteristics of procedural memory. One of the most significant developments in the study of human memory over the last two decades has been the discovery of a dissociation between two different kinds of memory systems. An early indication of this dissociation came from studies of amnesia in patients with excision or lesions of the hippocampus (Scoville & Milner, 1957). These patients were dramatically impaired in their

Speakers tend to reproduce syntactic structures that they have recently comprehended or produced. This structural or syntactic priming occurs despite differences in the particular conceptual or event roles expressed in prime and target sentences (Bock & Loebell, 1990). In two sentence recall studies, we used the tendency of speakers to paraphrase the finite complements of object-raising verbs as infinitive complements (e.g., “John believed that Mary was nice ” as “John believed Mary to be nice”) to test whether an additional conceptual role would affect priming. Prime constructions with identical constituent orders as objectraising infinitives but an additional conceptual role (“John persuaded Mary to be nice”) resulted in fewer paraphrases. Contrasts with other constructions suggest that the critical difference between primes was this extra conceptual role. Thus, subtle differences in conceptual structures can affect how speakers grammatically encode message elements. The meaning of an utterance constrains the form of its expression. For instance, a speaker who wishes to talk about one thing affecting another thing is more likely to create a sentence with two noun phrases than a sentence with only one noun phrase. Given information about what a speaker intends to express and context of the utterance, there is a limited set of constructions that the speaker can felicitously use. Yet, despite the many systematic meaning-form correlations present in languages, the mappings between them are not always one-to-one (for discussion, see

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INTRODUCTION Understanding speech production requires a synthesis of perspectives found in physiology, motor control, cognitive science, and linguistics. Here we focus on presenting work in the areas of motor control, dynamical systems and neural networks, and linguistics which we feel is critical in understanding functional architecture and characteristics of the speech production system. Centuries of research in linguistics have provided considerable evidence that there are fundamental cognitive units that structure language. Spoken word forms are not unstructured wholes but rather are composed from a limited inventory of phonological units which have no independent meaning but can be (relatively freely) combined and organized in the construction of word forms. While languages differ in their selection of phonological units, within a given language there is a relatively small fixed set. Unlike certain other domains of human movement in which the existence of