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Cognitive Signals for Brain-Machine Interfaces in Posterior Parietal Cortex Include Continuous 3D Trajectory Commands

Hauschild, Markus and Mulliken, Grant H. and Fineman, Igor and Loeb, Gerald E. and Andersen, Richard A. (2012) Cognitive Signals for Brain-Machine Interfaces in Posterior Parietal Cortex Include Continuous 3D Trajectory Commands. Proceedings of the National Academy of Sciences of the United States of America, 109 (42). pp. 17075-17080. ISSN 0027-8424. PMCID PMC3479517. doi:10.1073/pnas.1215092109.

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Cortical neural prosthetics extract command signals from the brain with the goal to restore function in paralyzed or amputated patients. Continuous control signals can be extracted from the motor cortical areas, whereas neural activity from posterior parietal cortex (PPC) can be used to decode cognitive variables related to the goals of movement. Because typical activities of daily living comprise both continuous control tasks such as reaching, and tasks benefiting from discrete control such as typing on a keyboard, availability of both signals simultaneously would promise significant increases in performance and versatility. Here, we show that PPC can provide 3D hand trajectory information under natural conditions that would be encountered for prosthetic applications, thus allowing simultaneous extraction of continuous and discrete signals without requiring multisite surgical implants. We found that limb movements can be decoded robustly and with high accuracy from a small population of neural units under free gaze in a complex 3D point-to-point reaching task. Both animals’ brain-control performance improved rapidly with practice, resulting in faster target acquisition and increasing accuracy. These findings disprove the notion that the motor cortical areas are the only candidate areas for continuous prosthetic command signals and, rather, suggests that PPC can provide equally useful trajectory signals in addition to discrete, cognitive variables. Hybrid use of continuous and discrete signals from PPC may enable a new generation of neural prostheses providing superior performance and additional flexibility in addressing individual patient needs.

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URLURL TypeDescription CentralArticle Information
Andersen, Richard A.0000-0002-7947-0472
Additional Information:© 2012 National Academy of Sciences. Freely available online through the PNAS open access option. Contributed by Richard A. Andersen, September 4, 2012 (sent for review June 23, 2012). Published online before print October 1, 2012. We thank I. Kagan for performing the MRI scans, K. Pejsa for animal care, and V. Shcherbatyuk and T. Yao for technical and administrative assistance. This work was supported by the Defense Advanced Research Projects Agency, the National Eye Institute of the National Institutes of Health, the Boswell Foundation and an Alfred E. Mann doctoral fellowship to M.H. Author contributions: M.H., G.H.M., G.E.L., and R.A.A. designed research; M.H. performed research; I.F. performed surgical procedures; M.H. analyzed data; and M.H., G.H.M., and R.A.A. wrote the paper. The authors declare no conflict of interest. This article contains supporting information online at
Funding AgencyGrant Number
Defense Advanced Research Projects Agency (DARPA)UNSPECIFIED
James G. Boswell FoundationUNSPECIFIED
Alfred E. Mann doctoral fellowshipUNSPECIFIED
Subject Keywords:cognitive neural prosthetic; parietal reach region; area 5
Issue or Number:42
PubMed Central ID:PMC3479517
Record Number:CaltechAUTHORS:20121203-131000589
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Official Citation:Decoding reach trajectories from parietal cortex Markus Hauschild, Grant H. Mulliken, Igor Fineman, Gerald E. Loeb, Richard A. Andersen Proceedings of the National Academy of Sciences Oct 2012, 109 (42) 17075-17080; DOI: 10.1073/pnas.1215092109
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:35768
Deposited By: Jason Perez
Deposited On:04 Dec 2012 00:12
Last Modified:09 Nov 2021 23:17

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