Center for Research in Computational Neuro-Cognition
{'Code': '08000000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}}
{'SignBlockName': 'Gerald Selzer', 'PO_EMAI': None, 'PO_PHON': None}
This Biological Facilities Center proposal requests funds to                    purchase a Thinking Machines CMlB Connection Machine with l6,384                processing elements and 64 Kbits of memory per element for the                  Center for Research in Computational Neuro-Cognition.  This                     machine is one of the most powerful computers in the world owing                to the extraordinary degree of parallelism it provides--up to                   65,536 concurrent bit operations in the maximal configuration.                  It is useful primarily for executing programs that manipulate                   tens of thousands to millions of small, simple, interacting                     units, exactly the kinds of elements that are found in modeling                 vision systems, associative memories, and other neuro-cognitive                 structures as well as genetic and evolutionary data.                                                                                                            The participants in the Center are committed to a fundamentally                 computational view of cognition, focusing on how humans and other               animals represent and manipulate information.  The Center is                    highly multidisciplinary, including faculty from neuroscience,                  computer science, linguistics, psychology, evolutionary biology,                mathematics, and other departments.  Specific research projects                 for which the connection machine will be used include:  to                      advance a biological computation model of langugage,                            neuromagnetic imaging, to develop a model of recent memory, to                  explore analogical problem solving, to produce an automatic image               identification system using biological principles based on                      Grossberg's theories of brain function, to develop parallel                     structural models of vision, and to simulate ecological and                     evolutionary processes.
{'FirstName': 'Charles', 'LastName': 'Taylor', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Charles E Taylor', 'EmailAddress': 'Taylor@biology.ucla.edu', 'NSF_ID': '000335850', 'StartDate': '09/15/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of California-Los Angeles', 'CityName': 'LOS ANGELES', 'ZipCode': '900244200', 'PhoneNumber': '3107940102', 'StreetAddress': '10889 WILSHIRE BLVD STE 700', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '36', 'CONGRESS_DISTRICT_ORG': 'CA36', 'ORG_UEI_NUM': 'RN64EPNH8JC6', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, LOS ANGELES', 'ORG_PRNT_UEI_NUM': None}
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[{'Code': '1102', 'Text': 'BIOLOGICAL FACILITIES'}, {'Code': '1108', 'Text': 'INSTRUMENTAT & INSTRUMENT DEVP'}, {'Code': '9145', 'Text': 'SPECIAL PROGRAMS-RESERVE'}]
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1987&All=true', 'xml': '8714206.xml'}