Delivering specific patterns of electrical activity to the median nerve of the arm triggers reliable sensations of texture, suggesting that it may ultimately be possible to restore complex tactile information to users of prosthetic limbs.

Cervical spinal cord stimulation evokes sensory percepts in the missing hand and arm of people with upper-limb amputation, regardless of amputation level or time post-amputation.

The brain continues to represent individual fingers in primary somatosensory cortex decades after the amputation of a hand, indicating that cortical maps do not require ongoing sensory input from the body.

Hand somatotopy can be preserved in the primary somatosensory cortex of tetraplegic patients, despite the absence of sensorimotor function and periphery-brain communication, but deteriorates over years after injury.

Patterns of coordinated activity in the basal ganglia predict how much force we will use to grip objects, suggesting that individuals with paralysis may ultimately be able to use these signals to control graded responses in robotic devices.

The provided framework based on biological models and clinical literature can aid in the optimization of visual cortical prostheses through computational or behavioral simulation experiments, serving as a flexible tool for computational, clinical, and behavioral neuroscientists working on visual neuroprosthetics.

Task changes, like increased force production or altered posture, decrease the accuracy of brain-machine interfaces predicting intended finger movements, however, understanding how neural activity changes with the altered biomechanics of the task may provide insights for generalizable decoder development.

Bayesian simulator-based inference is used to infer the parameters of complex multicompartment models of retinal neurons from two-photon imaging data.

The human brain encodes coordinated patterns of joint movements – synergies – to increase the efficiency with which it can control complex hand movements.

A murine model for a novel surgical concept demonstrates potential advances of neuroprosthetic interfacing.