NDLI: Motor cortical decoding performance depends on controlled system order

Content Provider	IEEE Xplore Digital Library
Author	Matlack, C. Haddock, A. Moritz, C.T. Chizeck, H.J.
Copyright Year	2014
Description	Author affiliation: Depts. of Rehabilitation Med. & Physiol. & Biophys., Univ. of Washington, Seattle, WA, USA (Moritz, C.T.) \|\| Dept. of Electr. Eng., Univ. of Washington, Seattle, WA, USA (Matlack, C.; Haddock, A.; Chizeck, H.J.)
Abstract	Recent advances in intracortical brain-machine interfaces (BMIs) for position control have leveraged state estimators to decode intended movements from cortical activity. We revisit the underlying assumptions behind the use of Kalman filters in this context, focusing on the fact that identified cortical coding models capture closed-loop task dynamics. We show that closed-loop models can be partitioned, exposing feedback policies of the brain which are separate from interface and task dynamics. Changing task dynamics may cause the brain to change its control policy, and consequently the closed-loop dynamics. This may degrade performance of decoders upon switching from manual tasks to velocity-controlled BMImediated tasks. We provide experimental results showing that for the same manual cursor task, changing system order affects neural coding of movement. In one experimental condition force determines position directly, and in the other force determines cursor velocity. From this we draw an analogy to subjects transitioning from manual reaching tasks to velocity-controlled BMI tasks. We conclude with suggested principles for improving BMI decoder performance, including matching the controlled system order between manual and brain control, and identifying the brain's controller dynamics rather than complete closed-loop dynamics.
Sponsorship	IEEE Eng. Med. Biol. Soc.
Starting Page	2553
Ending Page	2556
File Size	606043
Page Count	4
File Format	PDF
ISBN	9781424479290
ISSN	1557170X
DOI	10.1109/EMBC.2014.6944143
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Decoding Kalman filters Training Manuals Brain models Kinematics
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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