Decoding arm speed during reaching
Brain–machine interfaces typically decode arm velocity from motor cortical neurons to move neuroprostheses, but performance of these devices is degraded by erroneous extraction of speed from the neuronal firing patterns. Here, the authors show that this error can be corrected by using a hybrid artif...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2018-12-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-018-07647-3 |
| _version_ | 1818991973096226816 |
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| author | Yoh Inoue Hongwei Mao Steven B. Suway Josue Orellana Andrew B. Schwartz |
| author_facet | Yoh Inoue Hongwei Mao Steven B. Suway Josue Orellana Andrew B. Schwartz |
| author_sort | Yoh Inoue |
| collection | DOAJ |
| description | Brain–machine interfaces typically decode arm velocity from motor cortical neurons to move neuroprostheses, but performance of these devices is degraded by erroneous extraction of speed from the neuronal firing patterns. Here, the authors show that this error can be corrected by using a hybrid artificial neural network approach. |
| first_indexed | 2024-12-20T20:18:46Z |
| format | Article |
| id | doaj.art-f29031c4bcf6498c82d81ef9f86fb397 |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-12-20T20:18:46Z |
| publishDate | 2018-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-f29031c4bcf6498c82d81ef9f86fb3972022-12-21T19:27:38ZengNature PortfolioNature Communications2041-17232018-12-019111410.1038/s41467-018-07647-3Decoding arm speed during reachingYoh Inoue0Hongwei Mao1Steven B. Suway2Josue Orellana3Andrew B. Schwartz4Department of Neurosurgery, Osaka University Graduate School of MedicineSystems Neuroscience Center, University of PittsburghCenter for the Neural Basis of Cognition, Carnegie Mellon University and University of PittsburghCenter for the Neural Basis of Cognition, Carnegie Mellon University and University of PittsburghSystems Neuroscience Center, University of PittsburghBrain–machine interfaces typically decode arm velocity from motor cortical neurons to move neuroprostheses, but performance of these devices is degraded by erroneous extraction of speed from the neuronal firing patterns. Here, the authors show that this error can be corrected by using a hybrid artificial neural network approach.https://doi.org/10.1038/s41467-018-07647-3 |
| spellingShingle | Yoh Inoue Hongwei Mao Steven B. Suway Josue Orellana Andrew B. Schwartz Decoding arm speed during reaching Nature Communications |
| title | Decoding arm speed during reaching |
| title_full | Decoding arm speed during reaching |
| title_fullStr | Decoding arm speed during reaching |
| title_full_unstemmed | Decoding arm speed during reaching |
| title_short | Decoding arm speed during reaching |
| title_sort | decoding arm speed during reaching |
| url | https://doi.org/10.1038/s41467-018-07647-3 |
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