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Paradigm Shift in Sensorimotor Control Research and Brain Machine Interface Control: The Influence of Context on Sensorimotor Representations
Neural activity in the primary motor cortex (M1) is known to correlate with movement related variables including kinematics and dynamics. Our recent work, which we believe is part of a paradigm shift in sensorimotor research, has shown that in addition to these movement related variables, activity i...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6139327/ https://www.ncbi.nlm.nih.gov/pubmed/30250422 http://dx.doi.org/10.3389/fnins.2018.00579 |
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author | Zhao, Yao Hessburg, John P. Asok Kumar, Jaganth Nivas Francis, Joseph T. |
author_facet | Zhao, Yao Hessburg, John P. Asok Kumar, Jaganth Nivas Francis, Joseph T. |
author_sort | Zhao, Yao |
collection | PubMed |
description | Neural activity in the primary motor cortex (M1) is known to correlate with movement related variables including kinematics and dynamics. Our recent work, which we believe is part of a paradigm shift in sensorimotor research, has shown that in addition to these movement related variables, activity in M1 and the primary somatosensory cortex (S1) are also modulated by context, such as value, during both active movement and movement observation. Here we expand on the investigation of reward modulation in M1, showing that reward level changes the neural tuning function of M1 units to both kinematic as well as dynamic related variables. In addition, we show that this reward-modulated activity is present during brain machine interface (BMI) control. We suggest that by taking into account these context dependencies of M1 modulation, we can produce more robust BMIs. Toward this goal, we demonstrate that we can classify reward expectation from M1 on a movement-by-movement basis under BMI control and use this to gate multiple linear BMI decoders toward improved offline performance. These findings demonstrate that it is possible and meaningful to design a more accurate BMI decoder that takes reward and context into consideration. Our next step in this development will be to incorporate this gating system, or a continuous variant of it, into online BMI performance. |
format | Online Article Text |
id | pubmed-6139327 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-61393272018-09-24 Paradigm Shift in Sensorimotor Control Research and Brain Machine Interface Control: The Influence of Context on Sensorimotor Representations Zhao, Yao Hessburg, John P. Asok Kumar, Jaganth Nivas Francis, Joseph T. Front Neurosci Neuroscience Neural activity in the primary motor cortex (M1) is known to correlate with movement related variables including kinematics and dynamics. Our recent work, which we believe is part of a paradigm shift in sensorimotor research, has shown that in addition to these movement related variables, activity in M1 and the primary somatosensory cortex (S1) are also modulated by context, such as value, during both active movement and movement observation. Here we expand on the investigation of reward modulation in M1, showing that reward level changes the neural tuning function of M1 units to both kinematic as well as dynamic related variables. In addition, we show that this reward-modulated activity is present during brain machine interface (BMI) control. We suggest that by taking into account these context dependencies of M1 modulation, we can produce more robust BMIs. Toward this goal, we demonstrate that we can classify reward expectation from M1 on a movement-by-movement basis under BMI control and use this to gate multiple linear BMI decoders toward improved offline performance. These findings demonstrate that it is possible and meaningful to design a more accurate BMI decoder that takes reward and context into consideration. Our next step in this development will be to incorporate this gating system, or a continuous variant of it, into online BMI performance. Frontiers Media S.A. 2018-09-10 /pmc/articles/PMC6139327/ /pubmed/30250422 http://dx.doi.org/10.3389/fnins.2018.00579 Text en Copyright © 2018 Zhao, Hessburg, Asok Kumar and Francis. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Zhao, Yao Hessburg, John P. Asok Kumar, Jaganth Nivas Francis, Joseph T. Paradigm Shift in Sensorimotor Control Research and Brain Machine Interface Control: The Influence of Context on Sensorimotor Representations |
title | Paradigm Shift in Sensorimotor Control Research and Brain Machine Interface Control: The Influence of Context on Sensorimotor Representations |
title_full | Paradigm Shift in Sensorimotor Control Research and Brain Machine Interface Control: The Influence of Context on Sensorimotor Representations |
title_fullStr | Paradigm Shift in Sensorimotor Control Research and Brain Machine Interface Control: The Influence of Context on Sensorimotor Representations |
title_full_unstemmed | Paradigm Shift in Sensorimotor Control Research and Brain Machine Interface Control: The Influence of Context on Sensorimotor Representations |
title_short | Paradigm Shift in Sensorimotor Control Research and Brain Machine Interface Control: The Influence of Context on Sensorimotor Representations |
title_sort | paradigm shift in sensorimotor control research and brain machine interface control: the influence of context on sensorimotor representations |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6139327/ https://www.ncbi.nlm.nih.gov/pubmed/30250422 http://dx.doi.org/10.3389/fnins.2018.00579 |
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