Signal Processing for Distributed Network Brain Model
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
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The purpose of this research is to model empirically the distributed            processing network responsible for certain higher brain functions in            humans.  The models to be achieved will have medical relevance (EEG             analysis) and relevance to the design of parallel pattern recognition           and decision systems.  In previously funded research, the group has             used a large array of scalp electrodes to specify the origin of EEG             signals associated with specific functions.  To solve some of the               problems encountered in prior work, a larger array (128 channels) will          be implemented along with an appropriate finite-difference head and             brain model.  These will allow deconvolution of the scalp-recordings to         just above the cortical surface.  Magnetic resonance images will be             used to arrive at the model which will be validated against independent         data sets.
{'FirstName': 'Alan', 'LastName': 'Gevins', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Alan S Gevins', 'EmailAddress': None, 'PI_PHON': '4152274900', 'NSF_ID': '000170052', 'StartDate': '08/15/1986', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'EEG Systems Laboratory', 'CityName': 'San Francisco', 'ZipCode': '941211545', 'PhoneNumber': '4159571600', 'StreetAddress': '1 Rincon Center', 'StreetAddress2': 'Suite 204', 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_ORG': 'CA08', 'ORG_UEI_NUM': None, 'ORG_LGL_BUS_NAME': None, 'ORG_PRNT_UEI_NUM': None}
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{'Code': '5345', 'Text': 'Engineering of Biomed Systems'}
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