The proposed research focuses on two general issues: (1) how are simple, natural concepts combined to form complex ones, and (2) what processes govern the course of learning novel categories. With regard to (1), our previous work led to a model of how people combine concepts like red and fruit into adjective-noun conjunctions like red fruit. The basic idea is that the noun concept is represented by default values on each of a set of attributes, and that the adjective modifies the value on one of the attributes. This model is among the first to offer a detailed account of how prototype concepts can be combined to form new prototypes. The model has implications for many areas of psychology and our proposed research will test some of these implications and extend the model to new domains. Some studies will evaluate the model's claims about real-time processes during categorization, while others will try to bridge the gap between categorization and psycholinguistics by showing that the categorization processes we have described in our model are involved in language understanding. Still other studies will extend our analyses to conjunctions involving verbs, as well as explore the relation between combining concepts and decision making. The research on category learning considers how experience with exemplars leads to the development of categories. The proposed work will concentrate on distinguishing similarity-based from likelihood-based models of category learning. Some of the experimental tasks simulate the problem of assigning patients to disease categories on the basis of symptom patterns, the task being accomplished either by judging the similarity of new to old exemplars of the categories or by computing the likelihoods of the categories given the symptoms. Correlations between symptoms will be introduced so as to enable differential predictions from similarity and likelihood based models. Our prior research on concepts turned up important implications for psychiatric diagnosis, as well as for personality categories and social stereotypes. We expect the current work to continue to have implications for diagnosis, stereotypes, and aspects of mental illness, particularly since some of the work on combining concepts involves personality concepts, while some of the research on category learning uses diagnosis as the experimental task.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH037208-05
Application #
3376092
Study Section
Psychobiology and Behavior Research Review Committee (BBP)
Project Start
1982-09-28
Project End
1988-08-31
Budget Start
1986-09-01
Budget End
1987-08-31
Support Year
5
Fiscal Year
1986
Total Cost
Indirect Cost
Name
Harvard University
Department
Type
Schools of Arts and Sciences
DUNS #
071723621
City
Cambridge
State
MA
Country
United States
Zip Code
02138
Shafir, E B; Smith, E E; Osherson, D N (1990) Typicality and reasoning fallacies. Mem Cognit 18:229-39
Estes, W K; Campbell, J A; Hatsopoulos, N et al. (1989) Base-rate effects in category learning: a comparison of parallel network and memory storage-retrieval models. J Exp Psychol Learn Mem Cogn 15:556-71
Nosofsky, R M (1987) Attention and learning processes in the identification and categorization of integral stimuli. J Exp Psychol Learn Mem Cogn 13:87-108
Estes, W K (1987) Application of a cognitive-distance model to learning in a simulated travel task. J Exp Psychol Learn Mem Cogn 13:380-6
Estes, W K (1986) Array models for category learning. Cogn Psychol 18:500-49
Osherson, D N; Smith, E E; Shafir, E B (1986) Some origins of belief. Cognition 24:197-224
Nosofsky, R M (1986) Attention, similarity, and the identification-categorization relationship. J Exp Psychol Gen 115:39-61
Estes, W K (1986) Memory storage and retrieval processes in category learning. J Exp Psychol Gen 115:155-74
Nosofsky, R M (1985) Luce's choice model and Thurstone's categorical judgment model compared: Kornbrot's data revisited. Percept Psychophys 37:89-91
Nosofsky, R (1985) Overall similarity and the identification of separable-dimension stimuli: a choice model analysis. Percept Psychophys 38:415-32