ON THE NATURE AND SCOPE OF FEATURAL REPRESENTATIONS OF WORD MEANING

Behavioral experiments and a connectionist model were used to explore the use of featural representations in the computation of word meaning . The research focused on the role of correlations among features, and differences between speeded and untimed tasks with respect to the use of featural information. The results indicate that featural represent ations are used in the initial computation of word meaning (as in an a ttractor network), patterns of feature correlations differ between art ifacts and living things, and the degree to which features are interco rrelated plays an important role in the organization of semantic memor y. The studies also suggest that it may be possible to predict semanti c priming effects from independently motivated featural theories of se mantic relatedness. Implications for related behavioral phenomena such as the semantic impairments associated with Alzheimer's disease (AD) an discussed.