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Somersaults with or without twists are the most important elements in sports such as gymnastics or trampolining. Moreover, to perform elements with the highest possible difficulty gymnasts should show good form and execution during the flight phase. In order to ensure perfect body control and a safe landing, gaze behavior has been proven to be crucial for athletes to orientate in the air. As eye movement and head movement are closely coordinated, both must be examined while investigating gaze behavior. The aim of the current study is to analyze athletes' head motion and gaze behavior during somersaults with full twists. 15 skilled trampoline gymnasts performed back straight somersaults with a full twist (back full) on the trampoline. Eye movement and head movement were recorded using a portable eye-tracking device and a motion capture suit. The results indicate that gymnasts use the trampoline bed as a fixation point for orientation and control the back full, whereas the fixation onsets for athletes of a better performance class occur significantly later. A strong coordination between gymnasts' eye movement and head movement could be determined: stabilizing the gaze during the fixation period, the eyes move in combination with the head against the twisted somersault direction to counteract the whole body rotation. Although no significant differences could be found between the performance classes with regard to the maximum axial head rotations and maximum head extensions, there seems to be a trend that less skilled gymnasts need orientation as early as possible resulting in greater head rotation angles but a poorer execution.

In trampolining, gymnasts perform a variety of rotational jumping elements and have to demonstrate perfect control of the body during the flying phase. The performance of a somersault should include an opening phase, i.e. the legs are fully extended pointing vertically at 180° called "kick-out". As previous studies have shown, gaze behavior is essential for the controlling during the flight phase and to prepare for a perfect landing. Gymnasts supposedly use the trampoline bed as orientation and differences in gaze behavior can be expected, depending on how a somersault is performed. The present study investigates the gaze behavior of gymnasts during a back tuck somersault on the trampoline. Eleven experienced trampoline gymnasts performed back tuck somersaults with and without a kick-out while wearing a light weight portable eye-tracking device. All subjects fixated their gaze on a specific point at the trampoline bed and thus used visual information to prepare for landing. During the period of fixation, gymnasts' eyes moved continuously downwards to counteract the backwards head movement. The point of fixation differed between each somersault. Apparently, the fixation position depended on the gymnast's landing position in the bed. Performing a somersault with a kick-out allows gymnasts to orient themselves earlier and thus prepare sooner for landing. Unexpectedly, gymnasts of a higher performance class fixated the bed later compared to less experienced athletes. Supposedly, gymnasts of a better class can allow themselves to fixate later in order to optimize the form and execution of a somersault.

Visually presented biological motion stimuli activate regions in the brain that are also related to musculo-skeletal pain. We therefore hypothesized that chronic pain impairs the perception of visually presented actions that involve body parts that hurt. In the first experiment, chronic back pain (CLBP) patients and healthy controls judged the lifted weight from point-light biological motion displays. An actor either lifted an invisible container (5, 10, or 15 kg) from the floor, or lifted and manipulated it from the right to the left. The latter involved twisting of the lower back and would be very painful for CLBP patients. All participants recognized the displayed actions, but CLBP patients were impaired in judging the difference in handled weights, especially for the trunk rotation. The second experiment involved discrimination between forward and backward walking. Here the patients were just as good as the controls, showing that the main result of the first experiment was indeed specific to the sensory aspects of the task, and not to general impairments or attentional deficits. The results thus indicate that the judgment of sensorimotor aspects of a visually displayed movement is specifically affected by chronic low back pain.

Using recent recurrent network architecture based on the reservoir computing approach, we propose and numerically simulate a model that is focused on the aspects of a flexible motor memory for the storage of elementary movement patterns into the synaptic weights of a neural network, so that the patterns can be retrieved at any time by simple static commands. The resulting motor memory is flexible in that it is capable to continuously modulate the stored patterns. The modulation consists in an approximately linear inter- and extrapolation, generating a large space of possible movements that have not been learned before. A recurrent network of thousand neurons is trained in a manner that corresponds to a realistic exercising scenario, with experimentally measured muscular activations and with kinetic data representing proprioceptive feedback. The network is "self-active" in that it maintains recurrent flow of activation even in the absence of input, a feature that resembles the "resting-state activity" found in the human and animal brain. The model involves the concept of "neural outsourcing" which amounts to the permanent shifting of computational load from higher to lower-level neural structures, which might help to explain why humans are able to execute learned skills in a fluent and flexible manner without the need for attention to the details of the movement.

Model-based calculations indicate that reflex delay and reflex gain are both important for spinal stability. Experimental results demonstrate that chronic low back pain is associated with delayed muscle reflex responses of trunk muscles. The aim of the present study was to analyze the influence of such time-delayed reflexes on the stability using a simple biomechanical model. Additionally, we compared the model-based predictions with experimental data from chronic low back pain patients and healthy controls using surface-electromyography. Linear stability methods were applied to the musculoskeletal model, which was extended with a time-delayed reflex model. Lateral external perturbations were simulated around equilibrium to investigate the effects of reflex delay and gain on the stability of the human lumbar spine. The model simulations predicted that increased reflex delays require a reduction of the reflex gain to avoid spinal instability. The experimental data support this dependence for the investigated abdominal muscles in chronic low back pain patients and healthy control subjects. Reflex time-delay and gain dependence showed that a delayed reflex latency could have relevant influence on spinal stability, if subjects do not adapt their reflex amplitudes. Based on the model and the experimental results, the relationship between muscle reflex response latency and the maximum of the reflex amplitude should be considered for evaluation of (patho) physiological data. We recommend that training procedures should focus on speeding up the delayed reflex response as well as on increasing the amplitude of these reflexes.

Model-based calculations indicate that reflex delay and reflex gain are both important for spinal stability. Experimental results demonstrate that chronic low back pain is associated with delayed muscle reflex responses of trunk muscles. The aim of the present study was to analyze the influence of such time-delayed reflexes on the stability using a simple biomechanical model. Additionally, we compared the model-based predictions with experimental data from chronic low back pain patients and healthy controls using surface-electromyography. Linear stability methods were applied to the musculoskeletal model, which was extended with a time-delayed reflex model. Lateral external perturbations were simulated around equilibrium to investigate the effects of reflex delay and gain on the stability of the human lumbar spine. The model simulations predicted that increased reflex delays require a reduction of the reflex gain to avoid spinal instability. The experimental data support this dependence for the investigated abdominal muscles in chronic low back pain patients and healthy control subjects. Reflex time-delay and gain dependence showed that a delayed reflex latency could have relevant influence on spinal stability, if subjects do not adapt their reflex amplitudes. Based on the model and the experimental results, the relationship between muscle reflex response latency and the maximum of the reflex amplitude should be considered for evaluation of (patho) physiological data. We recommend that training procedures should focus on speeding up the delayed reflex response as well as on increasing the amplitude of these reflexes.

We evaluate an improved method for individually determining neuromuscular properties in vivo. The method is based on Hill's equation used as a force law combined with Newton's equation of motion. To ensure the range of validity of Hill's equation, we first perform detailed investigations on in vitro single muscles. The force-velocity relation determined with the model coincides well with results obtained by standard methods (r= .99) above 20% of the isometric force. In addition, the model-predicted force curves during work loop contractions very well agree with measurements (mean difference: 2-3%). Subsequently, we deduce theoretically under which conditions it is possible to combine several muscles of the human body to model muscles. This leads to a model equation for human leg extension movements containing parameters for the muscle properties and for the activation. To numerically determine these invariant neuromuscular properties we devise an experimental method based on concentric and isometric leg extensions. With this method we determine individual muscle parameters from experiments such that the simulated curves agree well with experiments (r =.99). A reliability test with 12 participants revealed correlations r = .72-.91 for the neuromuscular parameters (p