Researchers in the cognitive and brain sciences are generally concerned with mental functioning and the workings of the mind. Unfortunately, the cognitive processes that these researchers wish to study, such as attention, learning, and memory retrieval, are not directly observable. Thus, unlike physicists and chemists who have specific instruments to measure observable phenomena, cognitive scientists have no direct scales by which to measure the functions of the brain. This project will develop new measurement tools for the study of mental processes. In particular, the project will develop a scientific method of measurement called multinomial modeling. Multinomial models are relatively simple statistical models that can transform human performance data into measures of cognitive factors. These models have been successful in overcoming measurement problems in other areas of science, such as statistical genetics. In general, this project will create and test a number of multinomial models in crucial areas of human cognition. Scientists will then be able to use these models to explore more effectively many theoretical and practical issues in the areas of cognitive science and neuropsychology. For example, multinomial models may enable us to determine if brain dysfunction, such as in schizophrenia, occurs at the encoding stage of information processing or at some higher level. It may be possible to discover if the memory deficits associated with old age and disease, such as Alzheimer's disease, affect people's ability to store information or just their ability to retrieve it. In addition, these models will be able to pinpoint the precise effects of certain drugs and other disruptive variables on different aspects of cognitive functioning.
