Trial-to-trial dynamics and learning in generalized, redundant reaching tasks

Trial-to-trial variability in human movement is often overlooked and averaged out, but useful information can be gleaned on the brain’s control of variability. A task can be defined by a function specifying a solution manifold along which all task variable combinations will lead to goal success – the Goal-Equivalent Manifold (GEM). We selected a reaching task with variables reach Distance (D) and reach Time (T). Two GEMs were selected: a constant D/T and constant D×T. Subjects had no knowledge of the goal prior to the experiments and were instructed only to minimize error. Subjects learned the generalized tasks by reducing errors and consolidated learning from one day to the next, generalized learning from the D×T to the D/T GEM, and had interference of learning from the D/T to the D×T GEM. Variability was structured along each GEM significantly more than perpendicular to it. Deviations resulting in errors were corrected significantly more quickly than any other deviation. Our results indicate that subjects can learn generalized reaching tasks, and the brain exploits redundancy in those tasks.