Elsevier

Cognitive Psychology

Volume 48, Issue 4, June 2004, Pages 422-488
Cognitive Psychology

Representing the meanings of object and action words: The featural and unitary semantic space hypothesis

https://doi.org/10.1016/j.cogpsych.2003.09.001Get rights and content

Abstract

This paper presents the Featural and Unitary Semantic Space (FUSS) hypothesis of the meanings of object and action words. The hypothesis, implemented in a statistical model, is based on the following assumptions: First, it is assumed that the meanings of words are grounded in conceptual featural representations, some of which are organized according to modality. Second, it is assumed that conceptual featural representations are bound into lexico-semantic representations that provide an interface between conceptual knowledge and other linguistic information (syntax and phonology). Finally, the FUSS model employs the same principles and tools for objects and actions, modeling both domains in a single semantic space. We assess the plausibility of the model by showing that it can capture generalizations presented in the literature, in particular those related to category-related deficits, and show that it can predict semantic effects in behavioral experiments for object and action words better than other models such as Latent Semantic Analysis (Landauer & Dumais, 1997) and similarity metrics derived from Wordnet (Miller & Fellbaum, 1991).

Introduction

To grasp the meaning of a thing, an event, or a situation is to see it in its relations to other things; to note how it operates or functions, what consequences follow from it, what causes it, what uses it can be put to. In contrast, what we have called the brute thing, the thing without meaning to us, is something whose relations are not grasped” (John Dewey, 1910; quoted in Miller & Johnson-Laird, 1975, p. 212)

In the above passage Dewey simply and clearly points to two fundamental questions in the investigation of meaning. First, how are meanings related? Second, how is each meaning structured? These two separate but highly related questions have traditionally been central in cognitive psychology, linguistics, psycholinguistics, and neuroscience.

With respect to meaning relations, the intuitive impression that some meanings are more similar than others is compelling. The role of similarity in meaning is well documented in a variety of behavioral tasks and has a major role in theories of semantic representation developed within linguistics, cognitive psychology, and neuroscience. In the linguistic literature, for example, some researchers argue that words are organized into semantic fields: content domains (in which different elements are lexicalized in a language) structured on the basis of fine-grained contrasts and properties of similarity among their exemplars that govern the relations among the different words. These principles are relational (e.g., contrast) and the meanings of words within and between fields are defined solely with reference to other words (Kittay, 1987). Meaning similarity also plays a major theoretical role in a number of psychological theories of semantic memory (e.g., Collins & Loftus, 1975; Collins & Quillian, 1969; Medin, Goldstone, & Gentner, 1993; Miller & Johnson-Laird, 1975; Tversky, 1977).

Effects of meaning similarity are well-documented in linguistic tasks. For example, in spontaneous speech, mistakenly substituting one word with another word similar in meaning is one of the most common types of slip of the tongue (Garrett, 1992a). In naming experiments, the presentation of a word similar in meaning to a target picture immediately prior to the target has interference effects (e.g., Schriefers, Meyer, & Levelt, 1990). In word recognition experiments, semantically related primes speed up target recognition (McRae & Boisvert, 1998). The fact that more similar entities are clustered together and are separate from other less similar entities is also evident in the neuropsychological literature: semantic knowledge can break down selectively along category boundaries, broad boundaries such as selective deficit (or sparing) of living and non-living things; but also more fine-grained distinctions such as specific impairments (or sparing) of body-parts; fruits and vegetables among others (see Forde & Humphreys, 2002, for updated reviews).

With respect to the issue of how each meaning is represented, central to a number of theories of semantic organization is some sort of featural decomposition (see, e.g., Collins & Quillian, 1969; Jackendoff, 1990; Minsky, 1975; Norman & Rumelhart, 1975; Saffran & Sholl, 1999; Shallice, 1993; Smith & Medin, 1981, for overviews). Properties of featural representations such as correlation among features, features shared among different exemplars, and features distinctive of given exemplars have been used to account for meaning similarity effects (Malt & Smith, 1984; McRae, de Sa, & Seidenberg, 1997; Smith et al. (1988, Smith et al. (1974). Featural correlations and feature types (i.e., whether features refer to visual, acoustic, motoric, etc. properties of a concept) have also been used to explain category-related impairments of semantic knowledge (Caramazza, Hillis, Rapp, & Romani, 1990; Devlin, Gonnerman, Andersen, & Seidenberg, 1998; Tyler, Moss, Durrant-Peatfield, & Levy, 2000; Warrington & Shallice, 1984). Whether treated in terms of featural systems or other mechanisms, these regularities of normal and impaired meaning processing provide a major part of the empirical challenge to the development and elaboration of psychological theories of meaning representation.

In this paper, we present the Featural and Unitary Semantic Space (FUSS) hypothesis of the representations of words referring to objects and actions.1 FUSS integrates a number of previous claims and research strands encompassing neuroscience, cognitive psychology, and psycholinguistics into a working hypothesis of how the meanings of words are represented, which we have operationalized into a statistical model. Word meanings must be grounded in conceptual knowledge; however, at the same time the two levels cannot be equated (Murphy, 2002). For this reason we explicitly specify the type of conceptual representations we assume to exist, and we also explicitly specify the manner in which conceptual representations are linked to the meanings of words. Moreover, our hypothesis is constrained by neuropsychological and neuroanatomical evidence, in addition to having psychological plausibility. Given these premises, FUSS is formulated based on the following assumptions: First, featural representations are essential components of conceptual structure, and at least some of these featural representations (those for concrete concepts) can be described as modality-specific. Second, these featural representations are bound into lexico-semantic representations whose organization is dictated by featural properties (such as shared and correlated features). These first two assumptions lead us to a third assumption, namely, that the same general computational principles can be used to encode the representations for words in different content domains (here: objects and actions). Thus, in FUSS, the semantic system, organized according to the same principles for the object and action domains, comprises two levels of representation: conceptual structures (of which modality-specific features are an essential part) and lexico-semantic representations (derived from the conceptual features and organized on the basis of featural properties). Each of these architectural assumptions has existing exemplars in cognitive psychology, linguistics or neuroscience. Very few attempts, however, have been made to integrate them (a notable exception being Jackendoff, 2002). In contrast to other proposals, we integrate these assumptions across domains of object and action knowledge into a quantitative model based on feature norms.

The paper is organized into two main sections. In the first section, we discuss the underlying assumptions, motivating them on the basis of previous work. We present an implementation based on these assumptions and we detail analyses of the properties of the implemented model that relate back to the assumptions. In the second section, we present a series of behavioral experiments that test the ability of the implemented model to predict semantic similarity effects for both objects and actions. In this section, we directly compare the predictive power of our hypothesis to the predictive power of two existing models: Latent Semantic Analysis (LSA, Landauer & Dumais, 1997) and similarity measures derived from Wordnet (Miller & Fellbaum, 1991), models that are based on different principles but both of which allow us to derive quantitative predictions for both objects and actions.

Section snippets

Conceptual representations: Features and feature types

Featural conceptual representations are assumed by a number of authors (see, e.g., Collins & Quillian, 1969; Jackendoff (1990, Jackendoff (2002; Minsky, 1975; Norman & Rumelhart, 1975; Saffran & Sholl, 1999; Shallice, 1993; Smith & Medin, 1981), although few researchers have attempted to assess whether conceptual structures can be exhaustively decomposed into a set of primitive features (see Fodor, Fodor, & Garrett, 1975; Fodor, Garrett, Walker, & Parkes, 1980; Jackendoff (1983, Jackendoff (2002

Testing semantic similarity

Now that we have presented the hypothesis, motivating it on the basis of previous work, we turn to present a series of six experiments that focus on the lexico-semantic level and assess the predictive power of FUSS semantic similarity measures in the object and action domains. Thus, these experiments directly test the assumption that the lexico-semantic space for objects and actions can be modeled following the same principles.

The six experiments we report address the following specific

Conclusions

Words’ meanings must be grounded in the conceptual representation of things, events, etc.; hence, findings concerning conceptual organization must constrain theories of lexical semantics. Furthermore, words’ meanings are represented in the brain; hence, findings concerning the neural underpinning of semantic memory must constrain our theorizing.

FUSS is a hypothesis of the representation of the meanings of words in different content domains based on the assumptions that featural representations

Acknowledgements

The work reported here was supported by a Human Frontier Science Program Grant (RG148/2000) to Gabriella Vigliocco and Merrill Garrett, and by a James McDonnell Foundation Pilot Award (21002048) to Gabriella Vigliocco. We thank Stefano Cappa, Markus Damian, Peter Indefrey, Ken McRae, Simona Siri and Dan Tranel for their very helpful comments on previous versions of the manuscript.

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