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Different sensory information is used for state estimation when stationary or moving
Accurate estimation of limb state is necessary for movement planning and execution. State estimation requires both feedforward and feedback information; here we focus on the latter. Prior literature has shown that integrating visual and proprioceptive feedback improve estimates of static limb positi...
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/PMC10508725/ https://www.ncbi.nlm.nih.gov/pubmed/37732193 http://dx.doi.org/10.1101/2023.09.01.555979 |
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author | Wong, Aaron L Carter, Luke Therrien, Amanda S |
author_facet | Wong, Aaron L Carter, Luke Therrien, Amanda S |
author_sort | Wong, Aaron L |
collection | PubMed |
description | Accurate estimation of limb state is necessary for movement planning and execution. State estimation requires both feedforward and feedback information; here we focus on the latter. Prior literature has shown that integrating visual and proprioceptive feedback improve estimates of static limb position. However, differences in visual and proprioceptive feedback delays suggest that multisensory integration could be disadvantageous when the limb is moving. To investigate multisensory integration in different passive movement contexts, we compared the degree of interference created by discrepant visual or proprioceptive feedback when estimating the position of the limb either statically at the end of the movement or dynamically at movement midpoint. In the static context, we observed idiosyncratic interference: discrepant proprioceptive feedback significantly interfered with reports of the visual target location, leading to a bias of the reported position toward the proprioceptive cue. In the dynamic context, no interference was seen: participants could ignore sensory feedback from one modality and accurately reproduce the motion indicated by the other modality. We modeled feedback-based state estimation by updating the longstanding maximum likelihood estimation model of multisensory integration to account for sensory delays. Consistent with our behavioral results, the model showed that the benefit of multisensory integration was largely lost when the limb was passively moving. Together, these findings suggest that the sensory feedback used to compute a state estimate differs depending on whether the limb is stationary or moving. While the former may tend toward multimodal integration, the latter is more likely to be based on feedback from a single sensory modality. |
format | Online Article Text |
id | pubmed-10508725 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-105087252023-09-20 Different sensory information is used for state estimation when stationary or moving Wong, Aaron L Carter, Luke Therrien, Amanda S bioRxiv Article Accurate estimation of limb state is necessary for movement planning and execution. State estimation requires both feedforward and feedback information; here we focus on the latter. Prior literature has shown that integrating visual and proprioceptive feedback improve estimates of static limb position. However, differences in visual and proprioceptive feedback delays suggest that multisensory integration could be disadvantageous when the limb is moving. To investigate multisensory integration in different passive movement contexts, we compared the degree of interference created by discrepant visual or proprioceptive feedback when estimating the position of the limb either statically at the end of the movement or dynamically at movement midpoint. In the static context, we observed idiosyncratic interference: discrepant proprioceptive feedback significantly interfered with reports of the visual target location, leading to a bias of the reported position toward the proprioceptive cue. In the dynamic context, no interference was seen: participants could ignore sensory feedback from one modality and accurately reproduce the motion indicated by the other modality. We modeled feedback-based state estimation by updating the longstanding maximum likelihood estimation model of multisensory integration to account for sensory delays. Consistent with our behavioral results, the model showed that the benefit of multisensory integration was largely lost when the limb was passively moving. Together, these findings suggest that the sensory feedback used to compute a state estimate differs depending on whether the limb is stationary or moving. While the former may tend toward multimodal integration, the latter is more likely to be based on feedback from a single sensory modality. Cold Spring Harbor Laboratory 2023-09-14 /pmc/articles/PMC10508725/ /pubmed/37732193 http://dx.doi.org/10.1101/2023.09.01.555979 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 Wong, Aaron L Carter, Luke Therrien, Amanda S Different sensory information is used for state estimation when stationary or moving |
title | Different sensory information is used for state estimation when stationary or moving |
title_full | Different sensory information is used for state estimation when stationary or moving |
title_fullStr | Different sensory information is used for state estimation when stationary or moving |
title_full_unstemmed | Different sensory information is used for state estimation when stationary or moving |
title_short | Different sensory information is used for state estimation when stationary or moving |
title_sort | different sensory information is used for state estimation when stationary or moving |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10508725/ https://www.ncbi.nlm.nih.gov/pubmed/37732193 http://dx.doi.org/10.1101/2023.09.01.555979 |
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