Motor disorders are a frequent consequence of stroke and much effort is invested in the re-acquisition of motor control. Although patients often regain some of their lost function after therapy, most remain chronically disabled. Functional recovery is achieved largely through reorganization processes in the damaged brain. Neural reorganization depends on the information provided by sensorimotor efferent-afferent feedback loops. It has, however, been shown that the motor system can also be activated "offline" by imagining (motor imagery) or observing movements. The discovery of mirror neurones, which fire not only when an action is executed, but also when one observes another person performing the same action, also show that our action system can be used "online" as well as offline. It is an intriguing question as to whether the information provided by motor imagery or motor observation can lead to functional recovery and plastic changes in patients after stroke. This article reviews the evidence for motor imagery or observation as novel methods in stroke rehabilitation.

SUMMARY The protocols currently used for protein structure determination by NMR depend on the determination of a large number of upper distance limits for proton-proton pairs. Typically, this task is performed manually by an experienced researcher rather than automatically by using a specific computer program. To assess whether it is indeed possible to generate in a fully automated manner NMR structures adequate for deposition in the Protein Data Bank, we gathered ten experimental datasets with unassigned NOESY peak lists for various proteins of unknown structure, computed structures for each of them using different, fully automatic programs, and compared the results to each other and to the manually solved reference structures that were not available at the time the data were provided. This constitutes a stringent “blind” assessment similar to the CASP and CAPRI initiatives. This study demonstrates the feasibility of routine, fully automated protein structure determination by NMR.

In this study subjects had to imagine, observe and perform a series of 25 squat movements while lifting two dumbbells of 12.5 kg each (one with each hand). This movement is effortful and requires substantial activation of peripheral systems. It was asked whether subjects when they imagined that they were performing the movements or when they observed a model performing the squat movements would show increased activity in EMG, heart rate and respiration compared with a control condition where they sat relaxed in a comfortable chair or a condition where they actually performed the squat movements. Two groups of subjects participated in the experiment: experienced squatters and novices. By employing these two groups we were able to study the differential effect of earlier experience with the target movement on peripheral activation. The results showed that with the exception of respiration no significant peripheral activation could be measured related to motor imagery. Although a clear distinction in experience existed between the experienced squatters versus the novices, no relevant imagery-related differences could be obtained between the two groups. The results are discussed in the light of a central explanation of motor imagery.

A coarse-grained (CG) protein model implemented in the ATTRACT protein-protein docking program has been employed to predict protein-protein complex structures in CAPRI Rounds 22-27. For six targets, acceptable or better quality solutions have been submitted corresponding to ~60% of all targets. For one target, promising results on the prediction of the hydration structure at the protein-protein interface have been achieved. New approaches for the rapid flexible refinement have been developed based on a combination of atomistic representation of the bonded geometry and a CG description of nonbonded interactions. Possible further improvements of the docking approach in particular at the scoring and the flexible refinement steps are discussed.