A unified internal model theory to resolve the paradox of active versus passive self-motion sensation
Brainstem and cerebellar neurons implement an internal model to accurately estimate self-motion during externally generated (‘passive’) movements. However, these neurons show reduced responses during self-generated (‘active’) movements, indicating that predicted sensory consequences of motor command...
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doaj-4ba63fb0db804d3b8499d07cf4ef02452021-05-05T13:52:37ZengeLife Sciences Publications LtdeLife2050-084X2017-10-01610.7554/eLife.28074A unified internal model theory to resolve the paradox of active versus passive self-motion sensationJean Laurens0https://orcid.org/0000-0002-9101-2802Dora E Angelaki1https://orcid.org/0000-0002-9650-8962Department of Neuroscience, Baylor College of Medicine, Houston, United StatesDepartment of Neuroscience, Baylor College of Medicine, Houston, United StatesBrainstem and cerebellar neurons implement an internal model to accurately estimate self-motion during externally generated (‘passive’) movements. However, these neurons show reduced responses during self-generated (‘active’) movements, indicating that predicted sensory consequences of motor commands cancel sensory signals. Remarkably, the computational processes underlying sensory prediction during active motion and their relationship to internal model computations during passive movements remain unknown. We construct a Kalman filter that incorporates motor commands into a previously established model of optimal passive self-motion estimation. The simulated sensory error and feedback signals match experimentally measured neuronal responses during active and passive head and trunk rotations and translations. We conclude that a single sensory internal model can combine motor commands with vestibular and proprioceptive signals optimally. Thus, although neurons carrying sensory prediction error or feedback signals show attenuated modulation, the sensory cues and internal model are both engaged and critically important for accurate self-motion estimation during active head movements.https://elifesciences.org/articles/28074bayesianvestibularefference copyvestibular nucleuscerebelluminternal model |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jean Laurens Dora E Angelaki |
spellingShingle |
Jean Laurens Dora E Angelaki A unified internal model theory to resolve the paradox of active versus passive self-motion sensation eLife bayesian vestibular efference copy vestibular nucleus cerebellum internal model |
author_facet |
Jean Laurens Dora E Angelaki |
author_sort |
Jean Laurens |
title |
A unified internal model theory to resolve the paradox of active versus passive self-motion sensation |
title_short |
A unified internal model theory to resolve the paradox of active versus passive self-motion sensation |
title_full |
A unified internal model theory to resolve the paradox of active versus passive self-motion sensation |
title_fullStr |
A unified internal model theory to resolve the paradox of active versus passive self-motion sensation |
title_full_unstemmed |
A unified internal model theory to resolve the paradox of active versus passive self-motion sensation |
title_sort |
unified internal model theory to resolve the paradox of active versus passive self-motion sensation |
publisher |
eLife Sciences Publications Ltd |
series |
eLife |
issn |
2050-084X |
publishDate |
2017-10-01 |
description |
Brainstem and cerebellar neurons implement an internal model to accurately estimate self-motion during externally generated (‘passive’) movements. However, these neurons show reduced responses during self-generated (‘active’) movements, indicating that predicted sensory consequences of motor commands cancel sensory signals. Remarkably, the computational processes underlying sensory prediction during active motion and their relationship to internal model computations during passive movements remain unknown. We construct a Kalman filter that incorporates motor commands into a previously established model of optimal passive self-motion estimation. The simulated sensory error and feedback signals match experimentally measured neuronal responses during active and passive head and trunk rotations and translations. We conclude that a single sensory internal model can combine motor commands with vestibular and proprioceptive signals optimally. Thus, although neurons carrying sensory prediction error or feedback signals show attenuated modulation, the sensory cues and internal model are both engaged and critically important for accurate self-motion estimation during active head movements. |
topic |
bayesian vestibular efference copy vestibular nucleus cerebellum internal model |
url |
https://elifesciences.org/articles/28074 |
work_keys_str_mv |
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1721460480135921664 |