In this paper, we review research that we and our colleagues have done on the cognitive substrates of the planning and control of voluntary movements, especially movements of the hands and arms. We begin with a phenomenon observed in a natural setting and then brought into the laboratory—the
end-state comfort effect. This is a tendency to sacrifice initial comfort in reach-and-grasp tasks for final comfort or stability. The phenomenon can be traced to knowledge of the biomechanical advantages of occupying the middle of the range of motion for a joint. Next, we discuss three computational models that we and our colleagues have developed to address the problem of selecting particular movement patterns when an infinite number of movement patterns allow a task to be achieved. According to the first model—the
optimal selection model—effectors contribute to tasks in proportion to their goodness of fit to task demands. This model is successful in many ways but fails when a task cannot be accomplished by any one of the effectors acting alone. A second model—the
Knowledge model—solves this problem and displays some important competencies, including immediate compensation for reduced mobility of joints. The Knowledge model does not allow for high, equal emphasis on more than one task requirement, however, and requires a number of ad hoc assumptions. These limitations are overcome in a new model which, besides achieving everything that the earlier models could, also allows for effective reaching around obstacles and related abilities, including grasping of objects in realistic ways. The computational mechanisms we have devised may be applicable in domains outside motor control.
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