Biomedical subjects
Publications and source records attributed to Paul R Davidson.
Traditional studies of motor learning and prediction have focused on how subjects perform a single task. Recent advances have been made in our understanding of motor learning and prediction by investigating the way we learn variable tasks, which change either predictably or unpredictably over time. Similarly, studies have examined how variability in our own movements affects motor learning.
OBJECTIVE: Delirium, an important event in hospital, is associated with significant mortality and morbidity. Most patients with delirium recover fully; however, when left untreated, delirium may progress to stupor, coma, or death. Delirium is less likely to resolve completely in elderly patients in whom persistent cognitive deficits commonly occur. The extent to which this information is available to family doctors after discharge was investigated. METHOD: A total of 31 patients with delirium who were referred to consultation-liaison psychiatry were assessed using standardized measures. Medical services completed discharge summaries on these patients; a chart review captured the extent to which the diagnosis of delirium and the involvement of psychiatry was recorded in the discharge summaries. RESULTS: In structured discharge summaries, a reference to delirium occurrence was found in 55% of cases. In unstructured discharge summaries, the reporting was much lower (16% of cases). Delirium was more likely to be reported in women than in men, when it was more severe, or when it was the principal reason for admission, rather than when it occurred during an admission for some other reason. CONCLUSIONS: Delirium episodes that occur during a period of hospitalization for treatment of any medical disorder are underreported, even when specifically diagnosed. Structured discharge summaries tend to increase the rate of reporting.
In many recent human motor control models, including feedback-error learning and adaptive model theory (AMT), feedback control is used to correct errors while an inverse model is simultaneously tuned to provide accurate feedforward control. This popular and appealing hypothesis, based on a combination of psychophysical observations and engineering considerations, predicts that once the tuning of the inverse model is complete the role of feedback control is limited to the correction of disturbances. This hypothesis was tested by looking at the open-loop behavior of the human motor system during adaptation. An experiment was carried out involving 20 normal adult subjects who learned a novel visuomotor relationship on a pursuit tracking task with a steering wheel for input. During learning, the response cursor was periodically blanked, removing all feedback about the external system (i.e., about the relationship between hand motion and response cursor motion). Open-loop behavior was not consistent with a progressive transfer from closed- to open-loop control. Our recently developed computational model of the brain--a novel nonlinear implementation of AMT--was able to reproduce the observed closed- and open-loop results. In contrast, other control-systems models exhibited only minimal feedback control following adaptation, leading to incorrect open-loop behavior. This is because our model continues to use feedback to control slow movements after adaptation is complete. This behavior enhances the internal stability of the inverse model. In summary, our computational model is currently the only motor control model able to accurately simulate the closed- and open-loop characteristics of the experimental response trajectories.