Measuring follow-up time in routinely-collected health datasets: Challenges and solutions.

A key requirement for longitudinal studies using routinely-collected health data is to be able to measure what individuals are present in the datasets used, and over what time period. Individuals can enter and leave the covered population of administrative datasets for a variety of reasons, including both life events and characteristics of the datasets themselves. An automated, customizable method of determining individuals' presence was developed for the primary care dataset in Swansea University's SAIL Databank.

An MEG investigation of the neural mechanisms subserving complex visuomotor coordination.

Fifteen human participants performed a manual and ocular tracking task with a continuously and unpredictably moving visual target, while magnetoencephalography (MEG) signals were recorded. Three-dimensional source reconstructions were generated from the MEG signals, using synthetic aperture magnetometry (SAM). The SAM images indicated main effects of alpha band (8-15 Hz) and beta band (15-30 Hz) source power decreases, for manual tracking in the sensorimotor and parietal cortices, and for ocular tracking in the parietal and occipital cortices.

Adaptation to sensory-motor temporal misalignment: instrumental or perceptual learning?

Sensory-motor delays vary over the course of development and under different environmental conditions. Previous research has shown that humans can compensate for the resulting temporal misalignment while performing sensory-motor tasks (e.g.