Increasing the Performance of Cortically-Controlled Prostheses
Neural prostheses have received considerable attention due to their potential to dramatically improve the quality of life of severely disabled patients. Cortically-controlled prostheses are able to translate neural activity from cerebral cortex into control signals for guiding computer cursors or pr...
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| Veröffentlicht in: | 2006 International Conference of the IEEE Engineering in Medicine and Biology Society 2006, Vol.Supplement, p.6652-6656 |
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| creator | Shenoy, Krishna V. Santhanam, Teresa H. Ryu, Stephen I. Afshar, Afsheen Yu, Byron M. Gilja, Vikash Linderman, Michael D. Kalmar, Rachel S. Cunningham, John P. Kemere, Caleb T. Batista, Aaron P. Churchland, Mark M. Meng, Teresa H. |
| description | Neural prostheses have received considerable attention due to their potential to dramatically improve the quality of life of severely disabled patients. Cortically-controlled prostheses are able to translate neural activity from cerebral cortex into control signals for guiding computer cursors or prosthetic limbs. Non-invasive and invasive electrode techniques can be used to measure neural activity, with the latter promising considerably higher levels of performance and therefore functionality to patients. We review here some of our recent experimental and computational work aimed at establishing a principled design methodology to increase electrodebased cortical prosthesis performance to near theoretical limits. Studies discussed include translating unprecedentedly brief periods of “plan” activity into high information rate (6.5 bits/s) control signals, improving decode algorithms and optimizing visual target locations for further performance increases, and recording from chronically implanted arrays in freely behaving monkeys to characterize neuron stability. Taken together, these results should substantially increase the clinical viability of cortical prostheses. |
| doi_str_mv | 10.1109/IEMBS.2006.260912 |
| format | Article |
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Cortically-controlled prostheses are able to translate neural activity from cerebral cortex into control signals for guiding computer cursors or prosthetic limbs. Non-invasive and invasive electrode techniques can be used to measure neural activity, with the latter promising considerably higher levels of performance and therefore functionality to patients. We review here some of our recent experimental and computational work aimed at establishing a principled design methodology to increase electrodebased cortical prosthesis performance to near theoretical limits. Studies discussed include translating unprecedentedly brief periods of “plan” activity into high information rate (6.5 bits/s) control signals, improving decode algorithms and optimizing visual target locations for further performance increases, and recording from chronically implanted arrays in freely behaving monkeys to characterize neuron stability. 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Cortically-controlled prostheses are able to translate neural activity from cerebral cortex into control signals for guiding computer cursors or prosthetic limbs. Non-invasive and invasive electrode techniques can be used to measure neural activity, with the latter promising considerably higher levels of performance and therefore functionality to patients. We review here some of our recent experimental and computational work aimed at establishing a principled design methodology to increase electrodebased cortical prosthesis performance to near theoretical limits. Studies discussed include translating unprecedentedly brief periods of “plan” activity into high information rate (6.5 bits/s) control signals, improving decode algorithms and optimizing visual target locations for further performance increases, and recording from chronically implanted arrays in freely behaving monkeys to characterize neuron stability. Taken together, these results should substantially increase the clinical viability of cortical prostheses.</description><subject>Algorithms</subject><subject>Animals</subject><subject>Artificial Limbs</subject><subject>Brain-computer interface</subject><subject>brain-machine interface</subject><subject>Central nervous system</subject><subject>Cerebral Cortex - physiology</subject><subject>Communication system control</subject><subject>Decoding</subject><subject>Design methodology</subject><subject>Electrodes</subject><subject>Electrodes, Implanted</subject><subject>Macaca mulatta</subject><subject>Medical treatment</subject><subject>neural prostheses</subject><subject>Neural prosthesis</subject><subject>Neurons</subject><subject>premotor cortex</subject><subject>Prosthesis Design</subject><subject>Prosthetics</subject><subject>USA Councils</subject><subject>User-Computer Interface</subject><issn>1557-170X</issn><isbn>9781424400324</isbn><isbn>1424400325</isbn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2006</creationdate><recordtype>article</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><sourceid>EIF</sourceid><recordid>eNo9z81Kw0AUBeABFVtqH0AEycpd6szc-elsBA1VCxULKrgLk8mNRpJMnUkXffsGWr2buzgfBw4hl4zOGKPmdrl4eXibcUrVjCtqGD8hU6PnTHAhKAUuTsmYSalTpunniExj_KHDgRlifk5GTBtphNZjcrfsXEAb6-4r6b8xWWOofGht5zDxVZL50NfONs0uzXzXB980WCbr4OOAI8YLclbZJuL0-Cfk43Hxnj2nq9enZXa_SmsuNU-xAougJDAorZBzqECxsmLKcCXcsEgbC5ZrEExS5IUthHGsoM4i5wVKmJCbQ-8m-N8txj5v6-iwaWyHfhtzNQdjlNYDvD7CbdFimW9C3dqwy_8WD-DqAGpE_I8FBao4wB5IzmJM</recordid><startdate>2006</startdate><enddate>2006</enddate><creator>Shenoy, Krishna V.</creator><creator>Santhanam, Teresa H.</creator><creator>Ryu, Stephen I.</creator><creator>Afshar, Afsheen</creator><creator>Yu, Byron M.</creator><creator>Gilja, Vikash</creator><creator>Linderman, Michael D.</creator><creator>Kalmar, Rachel S.</creator><creator>Cunningham, John P.</creator><creator>Kemere, Caleb T.</creator><creator>Batista, Aaron P.</creator><creator>Churchland, Mark M.</creator><creator>Meng, Teresa H.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>7X8</scope></search><sort><creationdate>2006</creationdate><title>Increasing the Performance of Cortically-Controlled Prostheses</title><author>Shenoy, Krishna V. ; 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| subjects | Algorithms Animals Artificial Limbs Brain-computer interface brain-machine interface Central nervous system Cerebral Cortex - physiology Communication system control Decoding Design methodology Electrodes Electrodes, Implanted Macaca mulatta Medical treatment neural prostheses Neural prosthesis Neurons premotor cortex Prosthesis Design Prosthetics USA Councils User-Computer Interface |
| title | Increasing the Performance of Cortically-Controlled Prostheses |
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