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In cart-pole balancing, one moves a cart in 1 dimension so as to balance an attached inverted pendulum. We approached perception-action and learning in this task from an ecological perspective. This entailed identifying a space of informational variables that balancers use as they perform the task and demonstrating that they improve by traversing the space to the loci of more useful variables. We presented a novel information space--including fractional derivatives of pendulum angle (e.g., halfway between angle and angular velocity)--as possible information for balancing. Fourteen college students tried to meet a criterion of balancing the pole for 30 s on 3 of 5 successive trials, up to a maximum of 150 attempts. Loci in the fractional derivative space predicted the time series of force production well. Systematic differences were seen in loci as a function of success, and systematic changes in locus were seen with learning. The fractional derivatives were shown to predict pole angles a short time interval into the future, allowing balancers to prospectively control the action and thereby nullify visuomotor delay. In addition to loci in the information space, we analyzed loci in a calibration space, reflecting the gain relating force to information. (Contains 2 tables, 9 figures and 5 footnotes.)

A dynamic touch paradigm in which participants judged the lengths of rods and pipes was used to test the D. M. Jacobs and C. F. Michaels (2007) theory of perceptual learning. The theory portrays perception as the exploitation of a locus on an information manifold and learning as continuous movement across that manifold to a new locus, as guided by information available in feedback. The information manifold was defined as a 1-dimensional space of inertial variables. To encourage maximal learning, a 2-step procedure was used in each of 2 experiments. Each step comprised a pretest to identify the starting locus on the information manifold, a practice phase in which feedback specifying the optimal locus was given, and a posttest in which the ending locus on the manifold was identified. In the 2nd step, a different feedback variable specified a different optimum. In both experiments, participants, who sometimes began at different loci, showed the predicted movement toward the optimum in each phase. Whereas previous applications of the theory posit the existence of information-for-learning without identifying a candidate variable, such a candidate is identified. (Contains 8 footnotes, 6 figures, and 6 tables.)