Cognitive signals for brain–machine interfaces in posterior parietal cortex include continuous 3D trajectory commands
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 cogni...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
National Academy of Sciences (U.S.)
2013
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| Online Access: | http://hdl.handle.net/1721.1/78850 |
| _version_ | 1811083927261020160 |
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| author | Hauschild, Markus Mulliken, Grant Haverstock Fineman, Igor Loeb, Gerald E. Andersen, Richard A. |
| author2 | Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences |
| author_facet | Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences Hauschild, Markus Mulliken, Grant Haverstock Fineman, Igor Loeb, Gerald E. Andersen, Richard A. |
| author_sort | Hauschild, Markus |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T12:41:49Z |
| format | Article |
| id | mit-1721.1/78850 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T12:41:49Z |
| publishDate | 2013 |
| publisher | National Academy of Sciences (U.S.) |
| record_format | dspace |
| spelling | mit-1721.1/788502022-10-01T10:32:55Z Cognitive signals for brain–machine interfaces in posterior parietal cortex include continuous 3D trajectory commands Hauschild, Markus Mulliken, Grant Haverstock Fineman, Igor Loeb, Gerald E. Andersen, Richard A. Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences McGovern Institute for Brain Research at MIT Mulliken, Grant Haverstock 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. 2013-05-09T15:10:20Z 2013-05-09T15:10:20Z 2012-10 2012-06 Article http://purl.org/eprint/type/JournalArticle 0027-8424 1091-6490 http://hdl.handle.net/1721.1/78850 Hauschild, M. et al. “Cognitive Signals for Brain-machine Interfaces in Posterior Parietal Cortex Include Continuous 3D Trajectory Commands.” Proceedings of the National Academy of Sciences 109.42 (2012): 17075–17080. ©2013 National Academy of Sciences en_US http://dx.doi.org/10.1073/pnas.1215092109 Proceedings of the National Academy of Sciences of the United States of America Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf National Academy of Sciences (U.S.) PNAS |
| spellingShingle | Hauschild, Markus Mulliken, Grant Haverstock Fineman, Igor Loeb, Gerald E. Andersen, Richard A. Cognitive signals for brain–machine interfaces in posterior parietal cortex include continuous 3D trajectory commands |
| title | Cognitive signals for brain–machine interfaces in posterior parietal cortex include continuous 3D trajectory commands |
| title_full | Cognitive signals for brain–machine interfaces in posterior parietal cortex include continuous 3D trajectory commands |
| title_fullStr | Cognitive signals for brain–machine interfaces in posterior parietal cortex include continuous 3D trajectory commands |
| title_full_unstemmed | Cognitive signals for brain–machine interfaces in posterior parietal cortex include continuous 3D trajectory commands |
| title_short | Cognitive signals for brain–machine interfaces in posterior parietal cortex include continuous 3D trajectory commands |
| title_sort | cognitive signals for brain machine interfaces in posterior parietal cortex include continuous 3d trajectory commands |
| url | http://hdl.handle.net/1721.1/78850 |
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