Self-Organizing Neural Architectures for Eye Movements, Arm Movements, and Eye-Arm Coordination

Abstract

Many important sensory-motor skills arise as a result of a self-organizing process whereby a biological organism actively moves within a fluctuating environment. The present chapter discusses recent results concerning several key steps in this process: the adaptive transformation of a target position light on the retina into a target position computed in head-centered coordinates; the transformation of a target position computed in head-centered coordinates into a target position command to move an arm to the corresponding location in space; and the conversion of the target position command into a synchronous trajectory of the arm’s many components that executes this command in real-time. These transformations involve several different brain regions, such as posterior parietal cortex, precentral motor cortex, and the basal ganglia. Our concern in this chapter will be primarily with the underlying functional and computational issues. Extended discussions of empirical data and predictions are provided elsewhere [1-4], but some recent supportive data are mentioned, such as data concerning the GROSSBERG AND KUPERSTEIN [4] model of how head-centered target position maps are learned in posterior parietal cortex.