Adaptive control of movement deceleration during saccades.
As you read this text, your eyes make saccades that guide your fovea from one word to the next. Accuracy of these movements require the brain to monitor and learn from visual errors. A current model suggests that learning is supported by two different adaptive processes, one fast (high error sensiti...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2021-07-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1009176 |
| _version_ | 1811250831250423808 |
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| author | Simon P Orozco Scott T Albert Reza Shadmehr |
| author_facet | Simon P Orozco Scott T Albert Reza Shadmehr |
| author_sort | Simon P Orozco |
| collection | DOAJ |
| description | As you read this text, your eyes make saccades that guide your fovea from one word to the next. Accuracy of these movements require the brain to monitor and learn from visual errors. A current model suggests that learning is supported by two different adaptive processes, one fast (high error sensitivity, low retention), and the other slow (low error sensitivity, high retention). Here, we searched for signatures of these hypothesized processes and found that following experience of a visual error, there was an adaptive change in the motor commands of the subsequent saccade. Surprisingly, this adaptation was not uniformly expressed throughout the movement. Rather, after experience of a single error, the adaptive response in the subsequent trial was limited to the deceleration period. After repeated exposure to the same error, the acceleration period commands also adapted, and exhibited resistance to forgetting during set-breaks. In contrast, the deceleration period commands adapted more rapidly, but suffered from poor retention during these same breaks. State-space models suggested that acceleration and deceleration periods were supported by a shared adaptive state which re-aimed the saccade, as well as two separate processes which resembled a two-state model: one that learned slowly and contributed primarily via acceleration period commands, and another that learned rapidly but contributed primarily via deceleration period commands. |
| first_indexed | 2024-04-12T16:10:37Z |
| format | Article |
| id | doaj.art-133c38599b464667a4b5a2d47f7fe055 |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-04-12T16:10:37Z |
| publishDate | 2021-07-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-133c38599b464667a4b5a2d47f7fe0552022-12-22T03:25:55ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582021-07-01177e100917610.1371/journal.pcbi.1009176Adaptive control of movement deceleration during saccades.Simon P OrozcoScott T AlbertReza ShadmehrAs you read this text, your eyes make saccades that guide your fovea from one word to the next. Accuracy of these movements require the brain to monitor and learn from visual errors. A current model suggests that learning is supported by two different adaptive processes, one fast (high error sensitivity, low retention), and the other slow (low error sensitivity, high retention). Here, we searched for signatures of these hypothesized processes and found that following experience of a visual error, there was an adaptive change in the motor commands of the subsequent saccade. Surprisingly, this adaptation was not uniformly expressed throughout the movement. Rather, after experience of a single error, the adaptive response in the subsequent trial was limited to the deceleration period. After repeated exposure to the same error, the acceleration period commands also adapted, and exhibited resistance to forgetting during set-breaks. In contrast, the deceleration period commands adapted more rapidly, but suffered from poor retention during these same breaks. State-space models suggested that acceleration and deceleration periods were supported by a shared adaptive state which re-aimed the saccade, as well as two separate processes which resembled a two-state model: one that learned slowly and contributed primarily via acceleration period commands, and another that learned rapidly but contributed primarily via deceleration period commands.https://doi.org/10.1371/journal.pcbi.1009176 |
| spellingShingle | Simon P Orozco Scott T Albert Reza Shadmehr Adaptive control of movement deceleration during saccades. PLoS Computational Biology |
| title | Adaptive control of movement deceleration during saccades. |
| title_full | Adaptive control of movement deceleration during saccades. |
| title_fullStr | Adaptive control of movement deceleration during saccades. |
| title_full_unstemmed | Adaptive control of movement deceleration during saccades. |
| title_short | Adaptive control of movement deceleration during saccades. |
| title_sort | adaptive control of movement deceleration during saccades |
| url | https://doi.org/10.1371/journal.pcbi.1009176 |
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