The ability to name pictures or concepts is widely used as a clinical measure of cognitive status and a naming deficit is often one of the first symptoms of dementia. Even healthy older adults are slower and less successful in naming than are younger adults (4). We have shown that healthy older adults are (1) deficient in activation of orthographic and phonemic information necessary to produce a word name, and (2) more dependent on controlled retrieval processes that are both slower and less efficient than automatic processes. Intervention on either score reduces or eliminates naming deficits. The present proposal advances a parallel distributed processing (PDP) model of word retrieval that can accommodate the previous findings on older adults. The language user's knowledge is represented by a network of interconnected nodes organized at the semantic, morphological, and phonological levels, and retrieval is accomplished through patterns of spreading activation across and between network levels. The proposed experiments will allow the parameters of the PDP model to be estimated, and will test their adequacy in predicting naming deficits under various conditions of priming and stimulus exposure. A computerized picture naming paradigm will be used, with identification thresholds established individually for each subject. This will allow unusually precise measurements of the rate of network activation following various prime types. The precision of the new data and the detailed elaboration of the theoretical model offer great promise for clarifying age differences in the cognitive processes underlying naming, and for their possible remediation.