Optimization of Muscle Activity for Task-Level Goals Predicts Complex Changes in Limb Forces across Biomechanical Contexts

Optimality principles have been proposed as a general framework for understanding motor control in animals and humans largely based on their ability to predict general features movement in idealized motor tasks. However, generalizing these concepts past proof-of-principle to understand the neuromechanical transformation from task-level control to detailed execution-level muscle activity and forces during behaviorally-relevant motor tasks has proved difficult. In an unrestrained balance task in cats, we demonstrate that achieving task-level constraints center of mass forces and moments while minimizing control effort predicts detailed patterns of muscle activity and ground reaction forces in an anatomically-realistic musculoskeletal model. Whereas optimization is typically used to resolve redundancy at a single level of the motor hierarchy, we simultaneously resolved redundancy across both muscles and limbs and directly compared predictions to experimental measures across multiple perturbation directions that elicit different intra- and interlimb coordination patterns. Further, although some candidate task-level variables and cost functions generated indistinguishable predictions in a single biomechanical context, we identified a common optimization framework that could predict up to 48 experimental conditions per animal (n = 3) across both perturbation directions and different biomechanical contexts created by altering animals' postural configuration. Predictions were further improved by imposing experimentally-derived muscle synergy constraints, suggesting additional task variables or costs that may be relevant to the neural control of balance. These results suggested that reduced-dimension neural control mechanisms such as muscle synergies can achieve similar kinetics to the optimal solution, but with increased control effort (≈2×) compared to individual muscle control. Our results are consistent with the idea that hierarchical, task-level neural control mechanisms previously associated with voluntary tasks may also be used in automatic brainstem-mediated pathways for balance

The Effect of an Educational Programme to Improve the Skills of General Practitioners in Diagnosing Melanocytic / Pigmented Lesions

Background. Skin cancer is a major public health issue in fair-skinned populations, and general practitioners (GPs) play an important role in the diagnosis and management of this disease. Aims. To evaluate a self-instructional education module with audit and feedback, designed to increase the skills of GPs in diagnosing melanocytic lesions and skin cancer. Methods. This study, conducted in Queensland, Australia, included 16 GPs who participated in an 18-month programme, comprising a 6-month baseline audit of skin excisions, a 6-month educational programme and a 6-month posteducation audit. Results. The overall diagnostic accuracy of malignant lesions was 63.2% (95% CI 60.0–66.3) during baseline and 64.5% (95% CI 61.1–67.7) posteducation. Significant improvements were seen posteducation in the proportion of melanocytic lesions confirmed as malignant (6.1% baseline and 13.5% posteducation, χ2 = 6.6, P = 0.01). GPs with < 15 years of practice recorded significantly lower levels of diagnostic accuracy at baseline compared with those with ≥ 25 years of practice (P = 0.001). There were no differences in diagnostic skill posteducation according to years of practice. Conclusions. The education programme improved the malignant : benign ratio of melanocytic lesions, resulting in a doubling in the number of melanomas diagnosed. We found that GPs with less experience benefited most from the programme, indicating that tailoring of programmes to individual skills and years of practice might be beneficial