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A biomimetic adaptive algorithm and low-power architecture for implantable neural decoders

Rapoport, Benjamin I. and Wattanapanitch, Woradorn and Penagos, Hector L. and Musallam, Sam and Andersen, Richard A. and Sarpeshkar, Rahul (2009) A biomimetic adaptive algorithm and low-power architecture for implantable neural decoders. In: 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE , Piscataway, NJ, pp. 4214-4217. ISBN 978-1-4244-3296-7. https://resolver.caltech.edu/CaltechAUTHORS:20190325-154918574

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Abstract

Algorithmically and energetically efficient computational architectures that operate in real time are essential for clinically useful neural prosthetic devices. Such devices decode raw neural data to obtain direct control signals for external devices. They can also perform data compression and vastly reduce the bandwidth and consequently power expended in wireless transmission of raw data from implantable brain-machine interfaces. We describe a biomimetic algorithm and micropower analog circuit architecture for decoding neural cell ensemble signals. The decoding algorithm implements a continuous-time artificial neural network, using a bank of adaptive linear filters with kernels that emulate synaptic dynamics. The filters transform neural signal inputs into control-parameter outputs, and can be tuned automatically in an on-line learning process. We provide experimental validation of our system using neural data from thalamic head-direction cells in an awake behaving rat.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1109/iembs.2009.5333793DOIArticle
ORCID:
AuthorORCID
Andersen, Richard A.0000-0002-7947-0472
Additional Information:© 2009 IEEE. Manuscript received April 2009. This work was funded in part by National Institutes of Health grants R01-NS056140 and R01-EY15545, the McGovern Institute Neurotechnology Program at MIT, and National Eye Institute grant R01-EY13337. Rapoport received support from a CIMIT–MIT Medical Engineering Fellowship.
Funders:
Funding AgencyGrant Number
NIHR01-NS056140
NIHR01-EY15545
Massachusetts Institute of Technology (MIT)UNSPECIFIED
NIHR01-EY13337
National Eye InstituteUNSPECIFIED
Subject Keywords:Brain-machine interface, Neural decoding, Biomimetic, Adaptive algorithms, Analog, Low-power
DOI:10.1109/iembs.2009.5333793
Record Number:CaltechAUTHORS:20190325-154918574
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20190325-154918574
Official Citation:B. I. Rapoport, W. Wattanapanitch, H. L. Penagos, S. Musallam, R. A. Andersen and R. Sarpeshkar, "A biomimetic adaptive algorithm and low-power architecture for implantable neural decoders," 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Minneapolis, MN, 2009, pp. 4214-4217. doi: 10.1109/IEMBS.2009.5333793
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:94131
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:25 Mar 2019 23:29
Last Modified:16 Nov 2021 17:03

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