Performance appraisal and recognition system handbook : appendix A.

Mode of access: Internet.

The Federal role in the federal system : the dynamics of growth.

"A-77 - A-87."

Chronic shallow seawater circulation driven by subsurface gas dynamics, at the Southern Hydrate Ridge seep system, Cascadia

Senior thesis written for Oceanography 445

Parametric Optimization of Inductively Driven Liner Compression Driver System

Thesis (Master's)--University of Washington, 2016-06

Position information but not force information is used in adapting to changes in environmental dynamics

This study investigated how movement error is evaluated and used to change feedforward commands following a change in the environmental dynamics. In particular, we addressed the question of whether only position-error information is used or whether information about the force-field direction can also be used for rapid adaptation to changes in the environmental dynamics. Subjects learned to move in a position-dependent force field (PF) with a parabolic profile and the dynamics of a negative spring, which produced lateral force to the left of the target hand path. They adapted very rapidly, dramatically reducing lateral error after a single trial. Several times during training, the strength of the PF was unexpectedly doubled (PF2) for two trials. This again created a large leftward deviation, which was greatly reduced on the second PF2 trial, and an aftereffect when the force field subsequently returned to its original strength. The aftereffect was abolished if the second PF2 trial was replaced by an oppositely directed velocity-dependent force field (VF). During subsequent training in the VF, immediately after having adapted to the PF, subjects applied a force that assisted the force field for similar to 15 trials, indicating that they did not use information about the force-field direction. We concluded that the CNS uses only the position error for updating the internal model of the environmental dynamics and modifying feedforward commands. Although this strategy is not necessarily optimal, it may be the most reliable strategy for iterative improvement in performance.