A brain-computer interface that evokes tactile sensations improves robotic arm control

By Sharlene N. Flesher, J. Downey, Jeffrey M. Weiss, Christopher L. Hughes, Angelica J. Herrera, E. Tyler-Kabara, M. Boninger, J. Collinger, R. Gaunt. Science, 2021

521 citations recorded by the source corpus.

A boost for brain–computer interfaces The finely controlled movement of our limbs requires two-way neuronal communication between the brain and the body periphery. This includes afferent information from muscles, joints, and skin, as well as visual feedback to plan, initiate, and execute motor output. In tetraplegia, this neural communication is interrupted in both directions at the level of the spinal cord. Brain–computer interfaces have been developed to produce voluntary motor output controlled by directly recording from brain activity. Flesher et al. added an afferent channel to the brain–computer interface to mimic sensory input from the skin of a hand (see the Perspective by Faisal). The improvements achieved by adding the afferent input were substantial in a battery of motor tasks tested in a human subject. Science, abd0380, this issue p. 831; see also abi7262, p. 791 Creating artificial tactile feedback greatly improves the ability of a person with tetraplegia to manipulate objects with a robotic limb. Prosthetic arms controlled by a brain-computer interface can enable people with tetraplegia to perform functional movements. However, vision provides limited feedback because information about grasping objects is best relayed through tactile feedback. We supplemented vision with tactile percepts evoked using a bidirectional brain-computer interface that records neural activity from the motor cortex and generates tactile sensations through intracortical microstimulation of the somatosensory cortex. This enabled a person with tetraplegia to substantially improve performance with a robotic limb; trial times on a clinical upper-limb assessment were reduced by half, from a median time of 20.9 to 10.2 seconds. Faster times were primarily due to less time spent attempting to grasp objects, revealing that mimicking known biological control principles results in task performance that is closer to able-bodied human abilities.

Subfields: Biomedical Engineering, Cellular and Molecular Neuroscience, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/206a34781fa3b976ec1bbf0b9b231bf6a94424f1