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John E. Downey

Researcher at University of Chicago

Publications -  30
Citations -  3286

John E. Downey is an academic researcher from University of Chicago. The author has contributed to research in topics: Somatosensory system & Microstimulation. The author has an hindex of 15, co-authored 25 publications receiving 2533 citations. Previous affiliations of John E. Downey include Johns Hopkins University & University of Pittsburgh.

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High-performance neuroprosthetic control by an individual with tetraplegia

TL;DR: With continued development of neuroprosthetic limbs, individuals with long-term paralysis could recover the natural and intuitive command signals for hand placement, orientation, and reaching, allowing them to perform activities of daily living.
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Intracortical microstimulation of human somatosensory cortex

TL;DR: It is shown that microstimulation within the hand area of the somatosensory cortex of a person with long-term spinal cord injury evokes tactile sensations perceived as originating from locations on the hand and that cortical stimulation sites are organized according to expected somatotopic principles.
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Ten-dimensional anthropomorphic arm control in a human brain?machine interface: difficulties, solutions, and limitations

TL;DR: The results show that individual motor cortical neurons encode many parameters of movement, that object interaction is an important factor when extracting these signals, and that high-dimensional operation of prosthetic devices can be achieved with simple decoding algorithms.
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A brain-computer interface that evokes tactile sensations improves robotic arm control.

TL;DR: In this article, a bidirectional brain-computer interface that records neural activity from the motor cortex and generates tactile sensations through intracortical microstimulation of the somatosensory cortex was used to augment vision with tactile percepts.
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Autonomy infused teleoperation with application to brain computer interface controlled manipulation

TL;DR: The results indicate that shared assistance mitigates perceived user difficulty in using a seven-degree of freedom robotic arm as a prosthetic and enables successful performance on previously infeasible tasks.