Distinctiveness and Correlation in Conceptual Structure: Behavioral and Computational Studies.

Abstract

Patients with category-specific deficits have motivated a range of hypotheses about the structure of the conceptual system. One class of models claims that apparent category dissociations emerge from the internal structure of concepts rather than fractionation of the system into separate substores. This account claims that distinctive properties of concepts in the living domain are vulnerable because of their weak correlation with other features. Given the assumption that mutual activation among correlated properties produces faster activation in the normal system, the authors predicted a disadvantage for the distinctive features of living things for unimpaired adults. Results of a speeded feature verification study supported this prediction, as did a computational simulation in which networks mapped from orthography to semantics.

Distinctive features hold a privileged status in the computation of word meaning: Implications for theories of semantic memory.

“…First, we use the model to provide predictions for Experiments 1 and 2. It is important to note that the predictions both differ from those of Randall et al (2004), and, to foreshadow our results, fit with the strongest behavioral evidence regarding the time course of computation of distinctive semantic features available to date. Second, we analyze the internal weight structure of the model to provide insight into one plausible mechanism through which the human data can be interpreted.…”

“…This has motivated researchers to test whether the influence of these privileged connections can be seen in semantic tasks in normal participants. Randall, Moss, Rodd, Greer, and Tyler (2004) conducted an experiment to test "the central prediction of the conceptual structure account-that there will be a consistent disadvantage in processing the distinctive properties of living things relative to other kinds of features" (p. 394). They used a speeded feature verification task in which participants were asked to indicate as quickly and accurately as possible whether features were true of concepts.…”

Towards Unrestricted, Large-Scale Acquisition of Feature-Based Conceptual Representations from Corpus Data

“…Most recent theories of conceptual representation in cognitive psychology take a componential approach to semantic representation, and assume a distributed, feature-based model of conceptual knowledge (e.g. Farah and McClelland 1991;Masson 1995;Cree et al 1999;McRae et al 1997;Pexman et al 2002;Randall et al 2004;Tyler et al 2000). According to such theories, conceptual knowledge is distributed across a network of interconnected feature units (such as has_eyes , has_ears , has_stripes ) with concepts' meanings being represented as patterns of activation across these units.…”

“…As connectionist models of cognition have grown more sophisticated (and computational power has increased) researchers have implemented models of conceptual representation which use empirically-derived real world conceptual knowledge (McRae et al 1997;Cree et al 2006;Grondin et al 2009;Randall et al 2004). For these models, the feature nodes together with the concept patterns represented on them are intended to reflect the actual conceptual knowledge of people, as derived empirically from property norming studies.…”

“…They have been explored and tested with a variety of behavioural tasks, including similarity priming (McRae et al 1997;Masson 1995), object naming (Pexman et al 2002), feature verification (Cree et al 2006;Randall et al 2004), word recognition (Pexman et al 2002), and categorization (Pexman et al 2003).…”