The clinical utility of an elevated-risk multivariate index assay score in ovarian cancer patients.

Objective: Early involvement of specialists is associated with improved survival in ovarian cancer patients. However, only 33-60% of patients are currently being referred. A more effective strategy to get patients with an elevated risk of ovarian cancer to gynecologic oncologists is needed.

Temporal structure of motor variability is dynamically regulated and predicts motor learning ability.

Individual differences in motor learning ability are widely acknowledged, yet little is known about the factors that underlie them. Here we explore whether movement-to-movement variability in motor output, a ubiquitous if often unwanted characteristic of motor performance, predicts motor learning ability. Surprisingly, we found that higher levels of task-relevant motor variability predicted faster learning both across individuals and across tasks in two different paradigms, one relying on reward-based learning to shape specific arm movement trajectories and the other relying on error-based learning to adapt movements in novel physical environments.

The generalization of visuomotor learning to untrained movements and movement sequences based on movement vector and goal location remapping.

The planning of goal-directed movements is highly adaptable; however, the basic mechanisms underlying this adaptability are not well understood. Even the features of movement that drive adaptation are hotly debated, with some studies suggesting remapping of goal locations and others suggesting remapping of the movement vectors leading to goal locations. However, several previous motor learning studies and the multiplicity of the neural coding underlying visually guided reaching movements stand in contrast to this either/or debate on the modes of motor planning and adaptation.

Adaptation to dynamic environments displays local generalization for voluntary reaching movements.

The shape of the directional generalization function for adaptation to a viscous force-field environment has been controversial. Some studies have suggested wide, essentially global generalization and others have suggested narrow, local generalization. Here, we show definitively that motor adaptation displays narrow generalization with a minimal global component and a peak at the trained movement direction for both single-trial and asymptotic adaptation.