Rapid control and feedback rates enhance neuroprosthetic control

Maryam M. Shanechi; Amy L. Orsborn; Helene G. Moorman; Suraj Gowda; Siddharth Dangi; Jose M. Carmena

doi:10.1038/ncomms13825

Nature Communications (Jan 2017)

Rapid control and feedback rates enhance neuroprosthetic control

Maryam M. Shanechi,
Amy L. Orsborn,
Helene G. Moorman,
Suraj Gowda,
Siddharth Dangi,
Jose M. Carmena

Affiliations

Maryam M. Shanechi: Department of Electrical Engineering, Viterbi School of Engineering, University of Southern California
Amy L. Orsborn: UC Berkeley — UCSF Joint Graduate Program in Bioengineering, University of California, Berkeley
Helene G. Moorman: Helen Wills Neuroscience Institute, University of California, Berkeley
Suraj Gowda: Department of Electrical Engineering and Computer Sciences, University of California, Berkeley
Siddharth Dangi: Department of Electrical Engineering and Computer Sciences, University of California, Berkeley
Jose M. Carmena: Department of Electrical Engineering and Computer Sciences, University of California, Berkeley

DOI: https://doi.org/10.1038/ncomms13825
Journal volume & issue: Vol. 8, no. 1
pp. 1 – 10

Abstract

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Brain machine interfaces (BMI) enable sensorimotor control of movement yet the parameters that may affect these pathways are not known. Here the authors show systematically that increasing the rate of control from brain as well as feedback rates to the subject results in better performance on a BMI task in monkeys.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

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