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Internal models for interpreting neural population activity during sensorimotor control
To successfully guide limb movements, the brain takes in sensory information about the limb, internally tracks the state of the limb, and produces appropriate motor commands. It is widely believed that this process uses an internal model, which describes our prior beliefs about how the limb responds...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4874779/ https://www.ncbi.nlm.nih.gov/pubmed/26646183 http://dx.doi.org/10.7554/eLife.10015 |
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author | Golub, Matthew D Yu, Byron M Chase, Steven M |
author_facet | Golub, Matthew D Yu, Byron M Chase, Steven M |
author_sort | Golub, Matthew D |
collection | PubMed |
description | To successfully guide limb movements, the brain takes in sensory information about the limb, internally tracks the state of the limb, and produces appropriate motor commands. It is widely believed that this process uses an internal model, which describes our prior beliefs about how the limb responds to motor commands. Here, we leveraged a brain-machine interface (BMI) paradigm in rhesus monkeys and novel statistical analyses of neural population activity to gain insight into moment-by-moment internal model computations. We discovered that a mismatch between subjects’ internal models and the actual BMI explains roughly 65% of movement errors, as well as long-standing deficiencies in BMI speed control. We then used the internal models to characterize how the neural population activity changes during BMI learning. More broadly, this work provides an approach for interpreting neural population activity in the context of how prior beliefs guide the transformation of sensory input to motor output. DOI: http://dx.doi.org/10.7554/eLife.10015.001 |
format | Online Article Text |
id | pubmed-4874779 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-48747792016-05-23 Internal models for interpreting neural population activity during sensorimotor control Golub, Matthew D Yu, Byron M Chase, Steven M eLife Neuroscience To successfully guide limb movements, the brain takes in sensory information about the limb, internally tracks the state of the limb, and produces appropriate motor commands. It is widely believed that this process uses an internal model, which describes our prior beliefs about how the limb responds to motor commands. Here, we leveraged a brain-machine interface (BMI) paradigm in rhesus monkeys and novel statistical analyses of neural population activity to gain insight into moment-by-moment internal model computations. We discovered that a mismatch between subjects’ internal models and the actual BMI explains roughly 65% of movement errors, as well as long-standing deficiencies in BMI speed control. We then used the internal models to characterize how the neural population activity changes during BMI learning. More broadly, this work provides an approach for interpreting neural population activity in the context of how prior beliefs guide the transformation of sensory input to motor output. DOI: http://dx.doi.org/10.7554/eLife.10015.001 eLife Sciences Publications, Ltd 2015-12-08 /pmc/articles/PMC4874779/ /pubmed/26646183 http://dx.doi.org/10.7554/eLife.10015 Text en © 2015, Golub et al http://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Neuroscience Golub, Matthew D Yu, Byron M Chase, Steven M Internal models for interpreting neural population activity during sensorimotor control |
title | Internal models for interpreting neural population activity during sensorimotor control |
title_full | Internal models for interpreting neural population activity during sensorimotor control |
title_fullStr | Internal models for interpreting neural population activity during sensorimotor control |
title_full_unstemmed | Internal models for interpreting neural population activity during sensorimotor control |
title_short | Internal models for interpreting neural population activity during sensorimotor control |
title_sort | internal models for interpreting neural population activity during sensorimotor control |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4874779/ https://www.ncbi.nlm.nih.gov/pubmed/26646183 http://dx.doi.org/10.7554/eLife.10015 |
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