Compensatory motor network connectivity is associated with motor sequence learning after subcortical stroke
•We evaluated brain connectivity during motor tracking in healthy and stroke participants.•Healthy subjects demonstrated connectivity within a widely disturbed motor network.•A mask of the motor network was created to assess connectivity for the stroke group.•The connectivity within a smaller motor...
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Published in | Behavioural brain research Vol. 286; pp. 136 - 145 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
Netherlands
Elsevier B.V
01.06.2015
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Online Access | Get full text |
ISSN | 0166-4328 1872-7549 1872-7549 |
DOI | 10.1016/j.bbr.2015.02.054 |
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Abstract | •We evaluated brain connectivity during motor tracking in healthy and stroke participants.•Healthy subjects demonstrated connectivity within a widely disturbed motor network.•A mask of the motor network was created to assess connectivity for the stroke group.•The connectivity within a smaller motor network correlated with motor performance in the stroke group.•Motor network connectivity may be a predictor of motor learning and recovery following stroke.
Following stroke, functional networks reorganize and the brain demonstrates widespread alterations in cortical activity. Implicit motor learning is preserved after stroke. However the manner in which brain reorganization occurs, and how it supports behavior within the damaged brain remains unclear. In this functional magnetic resonance imaging (fMRI) study, we evaluated whole brain patterns of functional connectivity during the performance of an implicit tracking task at baseline and retention, following 5 days of practice. Following motor practice, a significant difference in connectivity within a motor network, consisting of bihemispheric activation of the sensory and motor cortices, parietal lobules, cerebellar and occipital lobules, was observed at retention. Healthy subjects demonstrated greater activity within this motor network during sequence learning compared to random practice. The stroke group did not show the same level of functional network integration, presumably due to the heterogeneity of functional reorganization following stroke. In a secondary analysis, a binary mask of the functional network activated from the aforementioned whole brain analyses was created to assess within-network connectivity, decreasing the spatial distribution and large variability of activation that exists within the lesioned brain. The stroke group demonstrated reduced clusters of connectivity within the masked brain regions as compared to the whole brain approach. Connectivity within this smaller motor network correlated with repeated sequence performance on the retention test. Increased functional integration within the motor network may be an important neurophysiological predictor of motor learning-related change in individuals with stroke. |
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AbstractList | Following stroke, functional networks reorganize and the brain demonstrates widespread alterations in cortical activity. Implicit motor learning is preserved after stroke. However the manner in which brain reorganization occurs, and how it supports behavior within the damaged brain remains unclear. In this functional magnetic resonance imaging (fMRI) study, we evaluated whole brain patterns of functional connectivity during the performance of an implicit tracking task at baseline and retention, following 5 days of practice. Following motor practice, a significant difference in connectivity within a motor network, consisting of bihemispheric activation of the sensory and motor cortices, parietal lobules, cerebellar and occipital lobules, was observed at retention. Healthy subjects demonstrated greater activity within this motor network during sequence learning compared to random practice. The stroke group did not show the same level of functional network integration, presumably due to the heterogeneity of functional reorganization following stroke. In a secondary analysis, a binary mask of the functional network activated from the aforementioned whole brain analyses was created to assess within-network connectivity, decreasing the spatial distribution and large variability of activation that exists within the lesioned brain. The stroke group demonstrated reduced clusters of connectivity within the masked brain regions as compared to the whole brain approach. Connectivity within this smaller motor network correlated with repeated sequence performance on the retention test. Increased functional integration within the motor network may be an important neurophysiological predictor of motor learning-related change in individuals with stroke. Following stroke, functional networks reorganize and the brain demonstrates widespread alterations in cortical activity. Implicit motor learning is preserved after stroke. However the manner in which brain reorganization occurs, and how it supports behaviour within the damaged brain remains unclear. In this functional magnetic resonance imaging (fMRI) study, we evaluated whole brain patterns of functional connectivity during the performance of an implicit tracking task at baseline and retention, following 5 days of practice. Following motor practice, a significant difference in connectivity within a motor network, consisting of bihemispheric activation of the sensory and motor cortices, parietal lobules, cerebellar and occipital lobules, was observed at retention. Healthy subjects demonstrated greater activity within this motor network during sequence learning compared to random practice. The stroke group did not show the same level of functional network integration, presumably due to the heterogeneity of functional reorganization following stroke. In a secondary analysis, a binary mask of the functional network activated from the aforementioned whole brain analyses was created to assess within-network connectivity, decreasing the spatial distribution and large variability of activation that exists within the lesioned brain. The stroke group demonstrated reduced clusters of connectivity within the masked brain regions as compared to the whole brain approach. Connectivity within this smaller motor network correlated with repeated sequence performance on the retention test. Increased functional integration within the motor network may be an important neurophysiological predictor of motor learning-related change in individuals with stroke. Following stroke, functional networks reorganize and the brain demonstrates widespread alterations in cortical activity. Implicit motor learning is preserved after stroke. However the manner in which brain reorganization occurs, and how it supports behavior within the damaged brain remains unclear. In this functional magnetic resonance imaging (fMRI) study, we evaluated whole brain patterns of functional connectivity during the performance of an implicit tracking task at baseline and retention, following 5 days of practice. Following motor practice, a significant difference in connectivity within a motor network, consisting of bihemispheric activation of the sensory and motor cortices, parietal lobules, cerebellar and occipital lobules, was observed at retention. Healthy subjects demonstrated greater activity within this motor network during sequence learning compared to random practice. The stroke group did not show the same level of functional network integration, presumably due to the heterogeneity of functional reorganization following stroke. In a secondary analysis, a binary mask of the functional network activated from the aforementioned whole brain analyses was created to assess within-network connectivity, decreasing the spatial distribution and large variability of activation that exists within the lesioned brain. The stroke group demonstrated reduced clusters of connectivity within the masked brain regions as compared to the whole brain approach. Connectivity within this smaller motor network correlated with repeated sequence performance on the retention test. Increased functional integration within the motor network may be an important neurophysiological predictor of motor learning-related change in individuals with stroke.Following stroke, functional networks reorganize and the brain demonstrates widespread alterations in cortical activity. Implicit motor learning is preserved after stroke. However the manner in which brain reorganization occurs, and how it supports behavior within the damaged brain remains unclear. In this functional magnetic resonance imaging (fMRI) study, we evaluated whole brain patterns of functional connectivity during the performance of an implicit tracking task at baseline and retention, following 5 days of practice. Following motor practice, a significant difference in connectivity within a motor network, consisting of bihemispheric activation of the sensory and motor cortices, parietal lobules, cerebellar and occipital lobules, was observed at retention. Healthy subjects demonstrated greater activity within this motor network during sequence learning compared to random practice. The stroke group did not show the same level of functional network integration, presumably due to the heterogeneity of functional reorganization following stroke. In a secondary analysis, a binary mask of the functional network activated from the aforementioned whole brain analyses was created to assess within-network connectivity, decreasing the spatial distribution and large variability of activation that exists within the lesioned brain. The stroke group demonstrated reduced clusters of connectivity within the masked brain regions as compared to the whole brain approach. Connectivity within this smaller motor network correlated with repeated sequence performance on the retention test. Increased functional integration within the motor network may be an important neurophysiological predictor of motor learning-related change in individuals with stroke. •We evaluated brain connectivity during motor tracking in healthy and stroke participants.•Healthy subjects demonstrated connectivity within a widely disturbed motor network.•A mask of the motor network was created to assess connectivity for the stroke group.•The connectivity within a smaller motor network correlated with motor performance in the stroke group.•Motor network connectivity may be a predictor of motor learning and recovery following stroke. Following stroke, functional networks reorganize and the brain demonstrates widespread alterations in cortical activity. Implicit motor learning is preserved after stroke. However the manner in which brain reorganization occurs, and how it supports behavior within the damaged brain remains unclear. In this functional magnetic resonance imaging (fMRI) study, we evaluated whole brain patterns of functional connectivity during the performance of an implicit tracking task at baseline and retention, following 5 days of practice. Following motor practice, a significant difference in connectivity within a motor network, consisting of bihemispheric activation of the sensory and motor cortices, parietal lobules, cerebellar and occipital lobules, was observed at retention. Healthy subjects demonstrated greater activity within this motor network during sequence learning compared to random practice. The stroke group did not show the same level of functional network integration, presumably due to the heterogeneity of functional reorganization following stroke. In a secondary analysis, a binary mask of the functional network activated from the aforementioned whole brain analyses was created to assess within-network connectivity, decreasing the spatial distribution and large variability of activation that exists within the lesioned brain. The stroke group demonstrated reduced clusters of connectivity within the masked brain regions as compared to the whole brain approach. Connectivity within this smaller motor network correlated with repeated sequence performance on the retention test. Increased functional integration within the motor network may be an important neurophysiological predictor of motor learning-related change in individuals with stroke. |
Author | Metzak, Paul D. Wadden, Katie P. Auriat, Angela M. Lakhani, Bimal Woodward, Todd S. Lavigne, Katie M. Boyd, Lara A. |
AuthorAffiliation | c Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada b Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada d BC Mental Health and Addictions Research Institute, Vancouver, BC, Canada a University of British Columbia, Faculty of Medicine, Department of Physical Therapy. 212-2177 Wesbrook Mall. Vancouver, British Columbia. V6T 1Z3. Canada |
AuthorAffiliation_xml | – name: a University of British Columbia, Faculty of Medicine, Department of Physical Therapy. 212-2177 Wesbrook Mall. Vancouver, British Columbia. V6T 1Z3. Canada – name: c Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada – name: d BC Mental Health and Addictions Research Institute, Vancouver, BC, Canada – name: b Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada |
Author_xml | – sequence: 1 givenname: Katie P. orcidid: 0000-0002-1565-7334 surname: Wadden fullname: Wadden, Katie P. organization: University of British Columbia, Faculty of Medicine, Department of Physical Therapy, 212-2177 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada – sequence: 2 givenname: Todd S. surname: Woodward fullname: Woodward, Todd S. organization: Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada – sequence: 3 givenname: Paul D. surname: Metzak fullname: Metzak, Paul D. organization: Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada – sequence: 4 givenname: Katie M. surname: Lavigne fullname: Lavigne, Katie M. organization: Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada – sequence: 5 givenname: Bimal surname: Lakhani fullname: Lakhani, Bimal organization: University of British Columbia, Faculty of Medicine, Department of Physical Therapy, 212-2177 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada – sequence: 6 givenname: Angela M. surname: Auriat fullname: Auriat, Angela M. organization: University of British Columbia, Faculty of Medicine, Department of Physical Therapy, 212-2177 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada – sequence: 7 givenname: Lara A. surname: Boyd fullname: Boyd, Lara A. email: lara.boyd@ubc.ca organization: University of British Columbia, Faculty of Medicine, Department of Physical Therapy, 212-2177 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/25757996$$D View this record in MEDLINE/PubMed |
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Keywords | Functional connectivity Functional magnetic resonance imaging Stroke Constrained principal component analysis Motor sequence learning |
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Snippet | •We evaluated brain connectivity during motor tracking in healthy and stroke participants.•Healthy subjects demonstrated connectivity within a widely disturbed... Following stroke, functional networks reorganize and the brain demonstrates widespread alterations in cortical activity. Implicit motor learning is preserved... |
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SubjectTerms | Brain - physiopathology Brain Mapping Constrained principal component analysis Female Functional connectivity Functional magnetic resonance imaging Humans Learning - physiology Magnetic Resonance Imaging Male Middle Aged Motor sequence learning Motor Skills - physiology Neural Pathways - physiopathology Principal Component Analysis Stroke Stroke - physiopathology Stroke - psychology |
Title | Compensatory motor network connectivity is associated with motor sequence learning after subcortical stroke |
URI | https://dx.doi.org/10.1016/j.bbr.2015.02.054 https://www.ncbi.nlm.nih.gov/pubmed/25757996 https://www.proquest.com/docview/1672087784 https://www.proquest.com/docview/1732817280 https://pubmed.ncbi.nlm.nih.gov/PMC4390540 |
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