Most modern research on the effects of feedback during learning has assumed that feedback is an error correction mechanism. Recent studies of feedback-timing effects have suggested that feedback might also strengthen initially correct responses. In an experiment involving cued recall of trivia facts, we directly tested several theories of feedback-timing effects and also examined the effects of...

Mesencephalic dopaminergic system (MDS) neurons may participate in learning by providing a prediction error signal to their targets, which include ventral striatal, orbital, and medial frontal regions, as well as by showing sensitivity to the degree of uncertainty associated with individual stimuli. We investigated the mechanisms of probabilistic classification learning in humans using function...

Does virtual reality (VR) represent a useful platform for teaching real-world motor skills? In domains such as sport and dance, this question has not yet been fully explored. The aim of this study was to determine the effects of two variations of real-time VR feedback on the learning of a complex dance movement. Novice participants (n 1⁄4 30) attempted to learn the action by both observing a vi...

Signal detection theory (SDT) parameters can describe a learner's ability to discriminate (d') normal from abnormal and the learner's criterion (λ) to under or overcall abnormalities. To examine the serial changes in SDT parameters with serial exposure to radiological cases. 46 participants were recruited for this study: 20 medical students (MED), 6 residents (RES), 12 fellows (FEL), 5 staff pe...

We hereby report on a pump-probe reflectivity experiment conducted on amorphous carbon, using a 780 nm laser as a pump and a 19 nm FEL emission as probe. Measurements were performed at 50 degrees with respect to the surface normal to have an un-pumped reflectivity higher than 0.5%. A sub-10 fs time synchronization error could be obtained exploiting the nearly jitter-free capabilities of FERMI. ...

Recent findings have demonstrated that reward feedback alone can drive motor learning. However, it is not yet clear whether reward feedback alone can lead to learning when a perturbation is introduced abruptly, or how a reward gradient can modulate learning. In this study, we provide reward feedback that decays continuously with increasing error. We asked whether it is possible to learn an abru...

Learning in robotics is one of the practical solutions allowing an autonomous robot to perceive its body and the environment. As discussed in the context of the frame problem [1], the robot’s body and the environment are too complex to be modeled. Even if the kinematics and the dynamics of the body are known, a real sensory input to the body would be different to one derived from the theoretica...

Successful learning hinges on the evaluation of positive and negative feedback. We assessed differential learning from reward and punishment in a monetary reinforcement learning paradigm, together with cardiac concomitants of positive and negative feedback processing. On the behavioral level, learning from reward resulted in more advantageous behavior than learning from punishment, suggesting a...

This paper presents an adaptive iterative learning control scheme that is applicable to a class of nonlinear systems. The control scheme guarantees system stability and boundedness by using the feedback controller coupled with the fuzzy compensator and achieves precise tracking by using the iterative learning rules. In the feedback plus fuzzy compensator unit, the feedback control part stabiliz...