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Neural representations for multi-context visuomotor adaptation and the impact of common representation on multi-task performance: a multivariate decoding approach.

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Title: Neural representations for multi-context visuomotor adaptation and the impact of common representation on multi-task performance: a multivariate decoding approach.
Authors: Song Y; Department of Bio and Brain Engineering, College of Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea., Shin W; Department of Bio and Brain Engineering, College of Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea.; Program of Brain and Cognitive Engineering, College of Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea., Kim P; Department of Bio and Brain Engineering, College of Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea., Jeong J; Department of Brain and Cognitive Sciences, College of Life Science and Bioengineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea.
Source: Frontiers in human neuroscience [Front Hum Neurosci] 2023 Sep 26; Vol. 17, pp. 1221944. Date of Electronic Publication: 2023 Sep 26 (Print Publication: 2023).
Publication Type: Journal Article
Language: English
Journal Info: Publisher: Frontiers Research Foundation Country of Publication: Switzerland NLM ID: 101477954 Publication Model: eCollection Cited Medium: Print ISSN: 1662-5161 (Print) Linking ISSN: 16625161 NLM ISO Abbreviation: Front Hum Neurosci Subsets: PubMed not MEDLINE
Imprint Name(s): Original Publication: Lausanne, Switzerland : Frontiers Research Foundation, 2008-
Abstract: The human brain's remarkable motor adaptability stems from the formation of context representations and the use of a common context representation (e.g., an invariant task structure across task contexts) derived from structural learning. However, direct evaluation of context representations and structural learning in sensorimotor tasks remains limited. This study aimed to rigorously distinguish neural representations of visual, movement, and context levels crucial for multi-context visuomotor adaptation and investigate the association between representation commonality across task contexts and adaptation performance using multivariate decoding analysis with fMRI data. Here, we focused on three distinct task contexts, two of which share a rotation structure (i.e., visuomotor rotation contexts with -90° and +90° rotations, in which the mouse cursor's movement was rotated 90 degrees counterclockwise and clockwise relative to the hand-movement direction, respectively) and the remaining one does not (i.e., mirror-reversal context where the horizontal movement of the computer mouse was inverted). This study found that visual representations (i.e., visual direction) were decoded in the occipital area, while movement representations (i.e., hand-movement direction) were decoded across various visuomotor-related regions. These findings are consistent with prior research and the widely recognized roles of those areas. Task-context representations (i.e., either -90° rotation, +90° rotation, or mirror-reversal) were also distinguishable in various brain regions. Notably, these regions largely overlapped with those encoding visual and movement representations. This overlap suggests a potential intricate dependency of encoding visual and movement directions on the context information. Moreover, we discovered that higher task performance is associated with task-context representation commonality, as evidenced by negative correlations between task performance and task-context-decoding accuracy in various brain regions, potentially supporting structural learning. Importantly, despite limited similarities between tasks (e.g., rotation and mirror-reversal contexts), such association was still observed, suggesting an efficient mechanism in the brain that extracts commonalities from different task contexts (such as visuomotor rotations or mirror-reversal) at multiple structural levels, from high-level abstractions to lower-level details. In summary, while illuminating the intricate interplay between visuomotor processing and context information, our study highlights the efficiency of learning mechanisms, thereby paving the way for future exploration of the brain's versatile motor ability.
(Copyright © 2023 Song, Shin, Kim and Jeong.)
Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Contributed Indexing: Keywords: context representation; meta-learning; multi-task; multi-voxel pattern analysis (MVPA); sensorimotor adaptation; shared representation; structural learning
Entry Date(s): Date Created: 20231012 Latest Revision: 20231030
Update Code: 20250114
PubMed Central ID: PMC10562562
DOI: 10.3389/fnhum.2023.1221944
PMID: 37822708
Database: MEDLINE
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Frontiers+Research+Foundation%22">Frontiers Research Foundation </searchLink><i>Country of Publication: </i>Switzerland <i>NLM ID: </i>101477954 <i>Publication Model: </i>eCollection <i>Cited Medium: </i>Print <i>ISSN: </i>1662-5161 (Print) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2216625161%22">16625161 </searchLink><i>NLM ISO Abbreviation: </i>Front Hum Neurosci <i>Subsets: </i>PubMed not MEDLINE
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  Data: The human brain's remarkable motor adaptability stems from the formation of context representations and the use of a common context representation (e.g., an invariant task structure across task contexts) derived from structural learning. However, direct evaluation of context representations and structural learning in sensorimotor tasks remains limited. This study aimed to rigorously distinguish neural representations of visual, movement, and context levels crucial for multi-context visuomotor adaptation and investigate the association between representation commonality across task contexts and adaptation performance using multivariate decoding analysis with fMRI data. Here, we focused on three distinct task contexts, two of which share a rotation structure (i.e., visuomotor rotation contexts with -90° and +90° rotations, in which the mouse cursor's movement was rotated 90 degrees counterclockwise and clockwise relative to the hand-movement direction, respectively) and the remaining one does not (i.e., mirror-reversal context where the horizontal movement of the computer mouse was inverted). This study found that visual representations (i.e., visual direction) were decoded in the occipital area, while movement representations (i.e., hand-movement direction) were decoded across various visuomotor-related regions. These findings are consistent with prior research and the widely recognized roles of those areas. Task-context representations (i.e., either -90° rotation, +90° rotation, or mirror-reversal) were also distinguishable in various brain regions. Notably, these regions largely overlapped with those encoding visual and movement representations. This overlap suggests a potential intricate dependency of encoding visual and movement directions on the context information. Moreover, we discovered that higher task performance is associated with task-context representation commonality, as evidenced by negative correlations between task performance and task-context-decoding accuracy in various brain regions, potentially supporting structural learning. Importantly, despite limited similarities between tasks (e.g., rotation and mirror-reversal contexts), such association was still observed, suggesting an efficient mechanism in the brain that extracts commonalities from different task contexts (such as visuomotor rotations or mirror-reversal) at multiple structural levels, from high-level abstractions to lower-level details. In summary, while illuminating the intricate interplay between visuomotor processing and context information, our study highlights the efficiency of learning mechanisms, thereby paving the way for future exploration of the brain's versatile motor ability.<br /> (Copyright © 2023 Song, Shin, Kim and Jeong.)
– Name: Abstract
  Label: Competing Interests
  Group: Ab
  Data: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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  Label: References
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  Data: <i>Keywords: </i>context representation; meta-learning; multi-task; multi-voxel pattern analysis (MVPA); sensorimotor adaptation; shared representation; structural learning
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        Value: 10.3389/fnhum.2023.1221944
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        Text: English
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        StartPage: 1221944
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      – TitleFull: Neural representations for multi-context visuomotor adaptation and the impact of common representation on multi-task performance: a multivariate decoding approach.
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              Text: 2023 Sep 26
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