This manuscript reviews historical and recent studies that focus on supplementary sensory
feedback for use in upper limb prostheses. It shows that the inability of many studies to …

It is generally accepted that augmented feedback, provided by a human expert or a technical
display, effectively enhances motor learning. However, discussion of the way to most …

Rationality principles such as optimal feedback control and Bayesian inference underpin a
probabilistic framework that has accounted for a range of empirical phenomena in biological …

A comprehensive look at state-of-the-art ADP theory and real-world applications This book
fills a gap in the literature by providing a theoretical framework for integrating techniques …

In order to generate skilled and efficient actions, the motor system must find solutions to
several problems inherent in sensorimotor control, including nonlinearity, nonstationarity …

During object manipulation tasks, the brain selects and implements action-phase controllers
that use sensory predictions and afferent signals to tailor motor output to the physical …

This paper presents a novel non-model-based, data-driven adaptive optimal controller
design for linear continuous-time systems with completely unknown dynamics. Inspired by …

Noise—random disturbances of signals—poses a fundamental problem for information
processing and affects all aspects of nervous-system function. However, the nature, amount …

We have previously tried to explain perceptual inference and learning under a free-energy
principle that pursues Helmholtz's agenda to understand the brain in terms of energy …

The study of patients to infer normal brain function has a long tradition in neurology and
psychology. More recently, the motor system has been subject to quantitative and …