We present statistical analyses of the large-scale structure of three types of semantic networks: word associations, WordNet, and Roget's thesaurus. We show that they have a small-world structure, characterized by sparse connectivity, short average path-lengths between words, and strong local clustering. In addition, the distributions of the number of connections follow power laws that indicate a scale-free pattern of connectivity, with most nodes having relatively few connections joined together through a small number of hubs with many connections. These regularities have also been found in certain other complex natural networks, such as the world wide web, but they are not consistent with many conventional models of semantic organization, based on inheritance hierarchies, arbitrarily structured networks, or high-dimensional vector spaces. We propose that these structures reflect the mechanisms by which semantic networks grow. We describe a simple model for semantic growth, in which each new word or concept is connected to an existing network by differentiating the connectivity pattern of an existing node. This model generates appropriate small-world statistics and power-law connectivity distributions, and also suggests one possible mechanistic basis for the effects of learning history variables (age-ofacquisition, usage frequency) on behavioral performance in semantic processing tasks.

Many theorists assume that the cognitive system is composed of a collection of encapsulated processing components or modules, each dedicated to performing a particular cognitive function. On this view, selective impairments of cognitive tasks following brain damage, as evidenced by double dissociations, are naturally interpreted in terms of the loss of particular processing components. By contrast, the current investigation examines in detail a double dissociation between concrete and abstract word reading after damage to a connectionist network that pronounces words via meaning and yet has no separable components (Plaut & Shallice, 1993). The functional specialization in the network that gives rise to the double dissociation is not transparently related to the network's structure, as modular theories assume. Furthermore, a consideration of the distribution of effects across quantitatively equivalent individual lesions in the network raises specific concerns about the interpretation of...

Processing language requires the retrieval of concepts from memory in response to an ongoing stream of information. This retrieval is facilitated if one can infer the gist of a sentence, conversation, or document computational problem underlying the extraction and use of gist, formulating this problem as a rational statistical inference. This leads to a novel approach to semantic representation in which word meanings are represented in terms of a set of probabilistic topics. The topic model performs well in predicting word association and the effects of semantic association and ambiguity on a variety of language-processing and memory tasks. It also provides a foundation for developing more richly structured statistical models of language, as the generative process assumed in the topic model can easily be extended to incorporate other kinds of semantic and syntactic structure.

The patterns of semantic errors in speaking and writing are used to constrain claims about the structure of lexical access mechanisms in speech and written language production. It is argued that it is not necessary to postulate a modality-neutral level of lexical representation (lemma) that is intermediate between lexical-semantic representations and modality-specific lexical representations. A dual-stage access model is proposed in which the first stage involves the selection of semantically and syntactically specified, modality-specific lexical forms, and the second stage involves the selection of specific phonological (orthographic) content for the selected lexemes.

DISLEX is an artificial neural network model of the mental lexicon. It was built to test computationally whether the lexicon could consist of separate feature maps for the different lexical modalities and the lexical semantics, connected with ordered pathways. In the model, the orthographic, phonological, and semantic feature maps and the associations between them are formed in an unsupervised process, based on cooccurrence of the lexical symbol and its meaning. After the model is organized, various damage to the lexical system can be simulated, resulting in dyslexic and category-specific aphasic impairments similar to those observed in human patients. 1 Introduction The human lexical system is believed to be highly modular, consisting of a central semantic component and separate symbol memories for the different input and output modalities (Caramazza 1988; McCarthy and Warrington 1990). Such an architecture is intuitively compelling since the modalities give rise to different repres...

this article may be sent to David Plaut, Mellon Institute 115-- CNBC, Carnegie Mellon University, 4400 Fifth Avenue, Pittsburgh PA 15213--2683; email: plaut@cmu.edu

Memory evolved to supply useful, timely information to the organism’s decision-making systems. Therefore, decision rules, multiple memory systems, and the search engines that link them should have coevolved to mesh in a coadapted, functionally interlocking way. This adaptationist perspective suggested the scope hypothesis: When a generalization is retrieved from semantic memory, episodic memories that are inconsistent with it should be retrieved in tandem to place boundary conditions on the scope of the generalization. Using a priming paradigm and a decision task involving person memory, the authors tested and confirmed this hypothesis. The results support the view that priming is an evolved adaptation. They further show that dissociations between memory systems are not—and should not be—absolute: Independence exists for some tasks but not others. Memory is a gift of nature, the ability of living organisms to retain and to utilize acquired information or knowledge.... Owners of biological memory systems are capable of behaving more appropriately at a later time because of their experiences at an earlier time, a feat not possible for organisms without memory. (Tulving, 1995a, p. 751) If there is one proposition on which all psychologists seem to

of objects

Investigations of patients with semantic category-specific deficits have revealed a wide range of performance and variability in categories that are impaired or spared; this variability presents a challenge to accounts of category specificity. Accounts based only on impairment to semantic features of a particular type (e.g., visual), as well as accounts based only on featural properties (e.g., feature intercorrelations), are insufficient to explain the variability of patients' performance. A first goal of the paper is to discuss how a hybrid account incorporating both a level of organization according to feature-types (a level of nonlinguistic conceptual representations) and a level of organization dictated by featural properties may provide a more comprehensive account of the cases reported in the literature. The second and most novel goal of the study reported here is to derive from our hybrid account a series of novel predictions concerning the representation and impairment of a different domain of knowledge: knowledge of actions and events, a domain of knowledge that has received remarkably little attention to date. Keywords: category-specificity, nouns, verbs, semantics, simulation The breakdown of semantic knowledge: Insights from a statistical model of meaning representation. The study of patients in whom semantic knowledge has been disrupted has led to a number of important inferences concerning the underlying architecture of the semantic system (Warrington, 1975). Particularly relevant are cases in which focal brain damage creates categoryspecific deficits (i.e., selective impairment of semantic knowledge along category boundaries). At present there are a substantial number of cases on record (approximately 89, according to Rogers & Plaut, 2002). Specificity in...

This essay attempts to develop a psychologically informed semantics of perception reports, whose predictions match with the linguistic data. As suggested by the quotation from Miller and Johnson-Laird, we take a hallmark of perception to be its fallible nature; the resulting semantics thus necessarily differs from situation semantics. On the psychological side, our main inspiration is Marr's (1982) theory of vision, which can easily accomodate fallible perception. In Marr's theory, vision is a multi-layered process. The different layers have filters of different gradation, wkich makes vision at each of them approximate. On the logical side, our task is therefore twofold to fomalise the layers and the ways in which they may refine each other, and to develop logical means to let description vary with such degrees of refinement.