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Making brain–machine interfaces robust to future neural variability
A major hurdle to clinical translation of brain–machine interfaces (BMIs) is that current decoders, which are trained from a small quantity of recent data, become ineffective when neural recording conditions subsequently change. We tested whether a decoder could be made more robust to future neural...
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| Publicado no: | Nat Commun |
|---|---|
| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Nature Publishing Group
2016
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5159828/ https://ncbi.nlm.nih.gov/pubmed/27958268 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/ncomms13749 |
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