Simulation of Human Memory
{'Code': '04040500', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'BCS', 'LongName': 'Division Of Behavioral and Cognitive Sci'}}
{'SignBlockName': 'Jasmine Young', 'PO_EMAI': 'jyoung@nsf.gov', 'PO_PHON': '7032924833'}
Previous NSF-supported research by Hintzman has shown that a                    simple theory of human memory, based on a few core assumptions,                 can account for a surprising number of empirical phenomena                      uncovered in experiments on human learning and memory.  The basic               assumptions of the theory have been formalized in computer                      programs, which have been tested on learning and memory tasks                   analogous to those given to humans participanting in experiments.                                                                                               Such simulation work is a valuable aid in the development of                    theories of cognition, particularly theories involving factors                  such as parallel processing and variability, whose consequences                 are difficult to anticipate intuitively.  The basic assumptions                 of the Hintzman simulation model, for example, concern processes                underlying the operation of just two fundamental variables,                     repetition and similarity.  However, the model accounts for                     several phenomena that previously had been thought to be unique,                and to require their own ad hoc explanations.                                                                                                                   The research will consist of three types of activity:  (a) The                  simulation model will be expanded in two ways.  First, the                      present model, which has so far been applied primarily to memory                for distinct events and the learning of abstract categories, will               be applied to the domains of associative learning and recall.                   Second, different versions of the model will be developed to                    handle problems for which the present model is inadequate.  These               include retrieval of the meaning of a word from memory, and the                 facilitative effect of prior familiarity on learning.  (b)                      Several experiments will test new predictions made by the model                 concerning the learning of abstract categories, the effects of                  repetition and similarity on recognition of previously                          encountered items, and memory retrieval latencies.  (c)                         Comparisons will be made between the present memory model and                   other models in the literature.  Interest will focus primarily on               determining whether a simple model of the "connectionist" type                  exists whose behavior is essentially the same as that of the                    current model.  This is important because an advantage claimed                  for connectionist models by some is that they are anatomically or               physiologically plausible.                                                                                                                                      The theory has broad implications for learning, memory, and                     cognitive processes.  As such, it could yield practical insights                in the fields of education and training, memory improvement,                    treatment of memory defects, and the reliability of judgments                   based on memory.
{'FirstName': 'Douglas', 'LastName': 'Hintzman', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Douglas L Hintzman', 'EmailAddress': None, 'NSF_ID': '000410982', 'StartDate': '08/15/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of Oregon Eugene', 'CityName': 'EUGENE', 'ZipCode': '974031905', 'PhoneNumber': '5413465131', 'StreetAddress': '1776 E 13TH AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Oregon', 'StateCode': 'OR', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'OR04', 'ORG_UEI_NUM': 'Z3FGN9MF92U2', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF OREGON', 'ORG_PRNT_UEI_NUM': 'Z3FGN9MF92U2'}
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{'Code': '118000', 'Text': 'HUMAN COGNITION & PERCEPTION'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1987&All=true', 'xml': '8711218.xml'}