SELF-ORGANIZING BODY SCHEMA FOR MOTOR PLANNING

This article presents a distributed computational architecture for the motor planning functions of the posterior parietal cortex, which is o rganized as a computational map and combines a paradigm of self-organi zation (for building robust and coherent maps of the different motor s paces) with an attractor dynamics (for run-time integration of task co nstraints). The model, named SO-BoS (self-organizing body-schema), is illustrated with simple simulation results.