A Single-Rate Context-Dependent Learning Process Underlies Rapid Adaptation to Familiar Object Dynamics

Motor learning has been extensively studied using dynamic (force-field) perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar object dynamics, however, the representations can be engaged based on visual context, and are updated by a single-rate process

Principles of sensorimotor learning.

The exploits of Martina Navratilova and Roger Federer represent the pinnacle of motor learning. However, when considering the range and complexity of the processes that are involved in motor learning, even the mere mortals among us exhibit abilities that are impressive. We exercise these abilities when taking up new activities - whether it is snowboarding or ballroom dancing - but also engage in substantial motor learning on a daily basis as we adapt to changes in our environment, manipulate new objects and refine existing skills. Here we review recent research in human motor learning with an emphasis on the computational mechanisms that are involved

Payer-provider collaboration in accountable care reduced use and improved quality in Maine Medicare Advantage plan.

Patient-centered, accountable care has garnered increased attention with the passage of the Affordable Care Act and new Medicare regulations. This case study examines a care model jointly developed by a provider and a payer that approximates an accountable care organization for a Medicare Advantage population. The collaboration between Aetna and NovaHealth, an independent physician association based in Portland, Maine, focused on shared data, financial incentives, and care management to improve health outcomes for approximately 750 Medicare Advantage members. The patient population in the pilot program had 50 percent fewer hospital days per 1,000 patients, 45 percent fewer admissions, and 56 percent fewer readmissions than statewide unmanaged Medicare populations. NovaHealth\u27s total per member per month costs across all cost categories for its Aetna Medicare Advantage members were 16.5 percent to 33 percent lower than costs for members not in this provider organization. Clinical quality metrics for diabetes, ischemic vascular disease, annual office visits, and postdischarge follow-up for patients in the program were consistently high. The experience of developing and implementing this collaborative care model suggests that several components are key, including robust data sharing and information systems that support it, analytical support, care management and coordination, and joint strategic planning with close provider-payer collaboration