Article,
Statistical decision theory and trade-offs in the control of motor response
Spatial Vision, (2003)
Abstract
We present a novel approach to the modeling of motor responses based
on statistical decision theory. We begin with the hypothesis that
subjects are ideal motion planners who choose movement trajectories
to minimize expected loss. We derive predictions of the hypothesis
for movement in environments where contact with specified regions
carries rewards or penalties. The model predicts shifts in a subject's
aiming point in response to changes in the reward and penalty structure
of the environment and with changes in the subject's uncertainty
in carrying out planned movements. We tested some of these predictions
in an experiment where subjects were rewarded if they succeeded in
touching a target region on a computer screen within a specified
time limit. Near the target was a penalty region which, if touched,
resulted in a penalty. We varied distance between the penalty region
and the target and the cost of hitting the penalty region. Subjects
shift their mean points of contact with the computer screen in response
to changes in penalties and location of the penalty region relative
to the target region in qualitative agreement with the predictions
of the hypothesis. Thus, movement planning takes into account extrinsic
costs and the subject's own motor uncertainty.
