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Motor Recovery After Subcortical Stroke Depends on Modulation of Extant Motor Networks

Overview of attention for article published in Frontiers in Neurology, November 2015
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  • Above-average Attention Score compared to outputs of the same age (54th percentile)
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Title
Motor Recovery After Subcortical Stroke Depends on Modulation of Extant Motor Networks
Published in
Frontiers in Neurology, November 2015
DOI 10.3389/fneur.2015.00230
Pubmed ID
Authors

Nikhil Sharma, Jean-Claude Baron

Abstract

Stroke is the leading cause of long-term disability. Functional imaging studies report widespread changes in movement-related cortical networks after stroke. Whether these are a result of stroke-specific cognitive processes or reflect modulation of existing movement-related networks is unknown. Understanding this distinction is critical in establishing more effective restorative therapies after stroke. Using multivariate analysis (tensor-independent component analysis - TICA), we map the neural networks involved during motor imagery (MI) and executed movement (EM) in subcortical stroke patients and age-matched controls. Twenty subcortical stroke patients and 17 age-matched controls were recruited. They were screened for their ability to carry out MI (Chaotic MI Assessment). The fMRI task was a right-hand finger-thumb opposition sequence (auditory-paced 1 Hz; 2, 3, 4, 5, 2…). Two separate runs were acquired (MI and rest and EM and rest; block design). There was no distinction between groups or tasks until the last stage of analysis, which allowed TICA to identify independent components (ICs) that were common or distinct to each group or task with no prior assumptions. TICA defined 28 ICs. ICs representing artifacts were excluded. ICs were only included if the subject scores were significant (for either EM or MI). Seven ICs remained that involved the primary and secondary motor networks. All ICs were shared between the stroke and age-matched controls. Five ICs were common to both tasks and three were exclusive to EM. Two ICs were related to motor recovery and one with time since stroke onset, but all were shared with age-matched controls. No IC was exclusive to stroke patients. We report that the cortical networks in stroke patients that relate to recovery of motor function represent modulation of existing cortical networks present in age-matched controls. The absence of cortical networks specific to stroke patients suggests that motor adaptation and other potential confounders (e.g., effort and additional muscle use) are not responsible for the changes in the cortical networks reported after stroke. This highlights that recovery of motor function after subcortical stroke involves preexisting cortical networks that could help identify more effective restorative therapies.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Singapore 1 2%
Unknown 50 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 15%
Student > Ph. D. Student 7 13%
Student > Bachelor 6 12%
Student > Master 6 12%
Student > Doctoral Student 3 6%
Other 9 17%
Unknown 13 25%
Readers by discipline Count As %
Neuroscience 15 29%
Psychology 5 10%
Medicine and Dentistry 4 8%
Nursing and Health Professions 4 8%
Engineering 3 6%
Other 8 15%
Unknown 13 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 November 2017.
All research outputs
#13,100,019
of 22,833,393 outputs
Outputs from Frontiers in Neurology
#4,983
of 11,712 outputs
Outputs of similar age
#114,509
of 252,470 outputs
Outputs of similar age from Frontiers in Neurology
#31
of 61 outputs
Altmetric has tracked 22,833,393 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,712 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one has gotten more attention than average, scoring higher than 56% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 252,470 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.
We're also able to compare this research output to 61 others from the same source and published within six weeks on either side of this one. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.