A Self-Organizing Neural Network for Learning a Body-Centered Invariant Representation of 3-D Target Position

Bullock, DanielGreve, DouglasGrossberg, StephenGuenther, Frank H.2011-11-142011-11-141993-01https://hdl.handle.net/2144/1987This paper describes a self-organizing neural network that rapidly learns a body-centered representation of 3-D target positions. This representation remains invariant under head and eye movements, and is a key component of sensory-motor systems for producing motor equivalent reaches to targets (Bullock, Grossberg, and Guenther, 1993).en-USCopyright 1993 Boston University. Permission to copy without fee all or part of this material is granted provided that: 1. The copies are not made or distributed for direct commercial advantage; 2. the report title, author, document number, and release date appear, and notice is given that copying is by permission of BOSTON UNIVERSITY TRUSTEES. To copy otherwise, or to republish, requires a fee and / or special permission.A Self-Organizing Neural Network for Learning a Body-Centered Invariant Representation of 3-D Target PositionTechnical ReportBoston University Trustees