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Learned biomechanical strategies prepare the human body in kinematics and kinetics terms during interception tasks, such as throwing and catching, in real world. Based on this, we present a real-time physics-based approach that generates natural and physic ...
The ease with which humans coordinate all their limbs is fascinating. Such a simplicity is the result of a complex process of motor coordination, i.e. the ability to resolve the biomechanical redundancy in an efficient and repeatable manner. Coordination e ...
Impaired motor skill acquisition is a feature of older age. Acquisition of new motor skills requires the interplay between different cortical motor areas. Using diffusion tensor imaging we reconstructed cortico-cortical connections between the primary moto ...
Stroke is the leading cause of disability among adults. Motor deficit is the most common impairment after stroke. Especially, deficits in fine motor skills impair numerous activities of daily life. Re-acquisition of motor skills resulting in improved or mo ...
Observing an action performed by another person to learn a new movement is a frequent experience in adult daily life, such as in sports. However, it is an especially common circumstance during the development of motor skills in childhood. Studies on health ...
Animals repeat rewarded behaviors, but the physiological basis of reward-based learning has only been partially elucidated. On one hand, experimental evidence shows that the neuromodulator dopamine carries information about rewards and affects synaptic pla ...
How do animals learn to repeat behaviors that lead to the obtention of food or other “rewarding” objects? As a biologically plausible paradigm for learning in spiking neural networks, spike-timing dependent plasticity (STDP) has been shown to perform well ...
Performance of unimanual movements is associated with bihemispheric activity in the motor cortex in old adults. However, the causal functional role of the ipsilateral MC (iMC) for motor control is still not completely known. Here, the behavioral consequenc ...
Reinforcement learning algorithms have been successfully applied in robotics to learn how to solve tasks based on reward signals obtained during task execution. These reward signals are usually modeled by the programmer or provided by supervision. However, ...
Perceptual learning is reward-based. A recent mathematical analysis showed that any reward-based learning system can learn two tasks only when the mean reward is identical for both tasks [Frémaux, Sprekeler and Gerstner, 2010, The Journal of Neuroscience, ...