Adaptive sensory-Motor Planning By Humans and machines
{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}
{'SignBlockName': 'Howard Moraff'}
The project will develop real-time neural network models for               the adaptive control and planning of complex sensory-motor                      skills.  Such models are equally important for understanding                    human movement planning and the design of flexible characterized                circuits for generating synchronous movements of multi-joint                    motor systems, such as arms and speech articulators, at variable                speeds.  The current research will investigate the design of                    supplementary circuits that are capable of rapidly adapting to                  the unexpected loads and inertias that arise during novel                       movements, and of slowly learning to predict the correct movement               parameters when these novel movements become familiar through                   practice.  In addition, the project will attemp to analyze how                  elementary, or atomic, movements are organized into complex                     movement sequences, and how the controls for these sequences                    become automated through learning.  Also, eye-hand coordination                 will be analyzed by showing how a representation of where the                   eye-head system is looking is associatively transformed into                    where the hand-arm system is commanded to move.  Issues                         concerning the learned timing of actions and self-organization of               a body-centered coordinated system will also be analyzed.
{'FirstName': 'Stephen', 'LastName': 'Grossberg', 'EmailAddress': 'steve@bu.edu', 'StartDate': '05/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Trustees of Boston University', 'CityName': 'BOSTON', 'ZipCode': '022151300', 'PhoneNumber': '6173534365', 'StreetAddress': '881 COMMONWEALTH AVE', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA'}
[{'Code': '6840', 'Text': 'ROBOTICS'}, {'Code': '9120', 'Text': 'CROSS-DIRECTORATE PROGRAMS'}]
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1987&All=true', 'xml': '8716960.xml'}