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Flexible regulation of representations on a drifting manifold enables long-term stable complex neuroprosthetic control
The nervous system needs to balance the stability of neural representations with plasticity. It is unclear what is the representational stability of simple actions, particularly those that are well-rehearsed in humans, and how it changes in new contexts. Using an electrocorticography brain-computer...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10462094/ https://www.ncbi.nlm.nih.gov/pubmed/37645922 http://dx.doi.org/10.1101/2023.08.11.551770 |
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author | Natraj, Nikhilesh Seko, Sarah Abiri, Reza Yan, Hongyi Graham, Yasmin Tu-Chan, Adelyn Chang, Edward F. Ganguly, Karunesh |
author_facet | Natraj, Nikhilesh Seko, Sarah Abiri, Reza Yan, Hongyi Graham, Yasmin Tu-Chan, Adelyn Chang, Edward F. Ganguly, Karunesh |
author_sort | Natraj, Nikhilesh |
collection | PubMed |
description | The nervous system needs to balance the stability of neural representations with plasticity. It is unclear what is the representational stability of simple actions, particularly those that are well-rehearsed in humans, and how it changes in new contexts. Using an electrocorticography brain-computer interface (BCI), we found that the mesoscale manifold and relative representational distances for a repertoire of simple imagined movements were remarkably stable. Interestingly, however, the manifold’s absolute location demonstrated day-to-day drift. Strikingly, representational statistics, especially variance, could be flexibly regulated to increase discernability during BCI control without somatotopic changes. Discernability strengthened with practice and was specific to the BCI, demonstrating remarkable contextual specificity. Accounting for drift, and leveraging the flexibility of representations, allowed neuroprosthetic control of a robotic arm and hand for over 7 months without recalibration. Our study offers insight into how electrocorticography can both track representational statistics across long periods and allow long-term complex neuroprosthetic control. |
format | Online Article Text |
id | pubmed-10462094 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-104620942023-08-29 Flexible regulation of representations on a drifting manifold enables long-term stable complex neuroprosthetic control Natraj, Nikhilesh Seko, Sarah Abiri, Reza Yan, Hongyi Graham, Yasmin Tu-Chan, Adelyn Chang, Edward F. Ganguly, Karunesh bioRxiv Article The nervous system needs to balance the stability of neural representations with plasticity. It is unclear what is the representational stability of simple actions, particularly those that are well-rehearsed in humans, and how it changes in new contexts. Using an electrocorticography brain-computer interface (BCI), we found that the mesoscale manifold and relative representational distances for a repertoire of simple imagined movements were remarkably stable. Interestingly, however, the manifold’s absolute location demonstrated day-to-day drift. Strikingly, representational statistics, especially variance, could be flexibly regulated to increase discernability during BCI control without somatotopic changes. Discernability strengthened with practice and was specific to the BCI, demonstrating remarkable contextual specificity. Accounting for drift, and leveraging the flexibility of representations, allowed neuroprosthetic control of a robotic arm and hand for over 7 months without recalibration. Our study offers insight into how electrocorticography can both track representational statistics across long periods and allow long-term complex neuroprosthetic control. Cold Spring Harbor Laboratory 2023-08-14 /pmc/articles/PMC10462094/ /pubmed/37645922 http://dx.doi.org/10.1101/2023.08.11.551770 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Natraj, Nikhilesh Seko, Sarah Abiri, Reza Yan, Hongyi Graham, Yasmin Tu-Chan, Adelyn Chang, Edward F. Ganguly, Karunesh Flexible regulation of representations on a drifting manifold enables long-term stable complex neuroprosthetic control |
title | Flexible regulation of representations on a drifting manifold enables long-term stable complex neuroprosthetic control |
title_full | Flexible regulation of representations on a drifting manifold enables long-term stable complex neuroprosthetic control |
title_fullStr | Flexible regulation of representations on a drifting manifold enables long-term stable complex neuroprosthetic control |
title_full_unstemmed | Flexible regulation of representations on a drifting manifold enables long-term stable complex neuroprosthetic control |
title_short | Flexible regulation of representations on a drifting manifold enables long-term stable complex neuroprosthetic control |
title_sort | flexible regulation of representations on a drifting manifold enables long-term stable complex neuroprosthetic control |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10462094/ https://www.ncbi.nlm.nih.gov/pubmed/37645922 http://dx.doi.org/10.1101/2023.08.11.551770 |
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