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Changes in task-based effective connectivity in language networks following rehabilitation in post-stroke patients with aphasia

Overview of attention for article published in Frontiers in Human Neuroscience, June 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

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9 X users
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Title
Changes in task-based effective connectivity in language networks following rehabilitation in post-stroke patients with aphasia
Published in
Frontiers in Human Neuroscience, June 2015
DOI 10.3389/fnhum.2015.00316
Pubmed ID
Authors

Swathi Kiran, Erin L. Meier, Kushal J. Kapse, Peter A. Glynn

Abstract

In this study, we examined regions in the left and right hemisphere language network that were altered in terms of the underlying neural activation and effective connectivity subsequent to language rehabilitation. Eight persons with chronic post-stroke aphasia and eight normal controls participated in the current study. Patients received a 10 week semantic feature-based rehabilitation program to improve their skills. Therapy was provided on atypical examples of one trained category while two control categories were monitored; the categories were counterbalanced across patients. In each fMRI session, two experimental tasks were conducted: (a) picture naming and (b) semantic feature verification of trained and untrained categories. Analysis of treatment effect sizes revealed that all patients showed greater improvements on the trained category relative to untrained categories. Results from this study show remarkable patterns of consistency despite the inherent variability in lesion size and activation patterns across patients. Across patients, activation that emerged as a function of rehabilitation on the trained category included bilateral IFG, bilateral SFG, LMFG, and LPCG for picture naming; and bilateral IFG, bilateral MFG, LSFG, and bilateral MTG for semantic feature verification. Analysis of effective connectivity using Dynamic Causal Modeling (DCM) indicated that LIFG was the consistently significantly modulated region after rehabilitation across participants. These results indicate that language networks in patients with aphasia resemble normal language control networks and that this similarity is accentuated by rehabilitation.

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X Demographics

The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 123 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 2%
Unknown 121 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 22%
Student > Bachelor 17 14%
Student > Master 13 11%
Researcher 9 7%
Professor > Associate Professor 7 6%
Other 24 20%
Unknown 26 21%
Readers by discipline Count As %
Neuroscience 22 18%
Psychology 19 15%
Medicine and Dentistry 11 9%
Agricultural and Biological Sciences 8 7%
Social Sciences 8 7%
Other 21 17%
Unknown 34 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 04 December 2015.
All research outputs
#4,654,007
of 22,789,566 outputs
Outputs from Frontiers in Human Neuroscience
#2,118
of 7,145 outputs
Outputs of similar age
#59,445
of 266,358 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#53
of 187 outputs
Altmetric has tracked 22,789,566 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,145 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.5. This one has gotten more attention than average, scoring higher than 70% 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 266,358 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 187 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.