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Altered Whole-Brain and Network-Based Functional Connectivity in Parkinson's Disease

Overview of attention for article published in Frontiers in Neurology, June 2018
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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 (79th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

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Title
Altered Whole-Brain and Network-Based Functional Connectivity in Parkinson's Disease
Published in
Frontiers in Neurology, June 2018
DOI 10.3389/fneur.2018.00419
Pubmed ID
Authors

Laura J. de Schipper, Anne Hafkemeijer, Jeroen van der Grond, Johan Marinus, Johanna M. L. Henselmans, Jacobus J. van Hilten

Abstract

Background: Functional imaging methods, such as resting-state functional magnetic resonance imaging, reflect changes in neural connectivity and may help to assess the widespread consequences of disease-specific network changes in Parkinson's disease. In this study we used a relatively new graph analysis approach in functional imaging: eigenvector centrality mapping. This model-free method, applied to all voxels in the brain, identifies prominent regions in the brain network hierarchy and detects localized differences between patient populations. In other neurological disorders, eigenvector centrality mapping has been linked to changes in functional connectivity in certain nodes of brain networks. Objectives: Examining changes in functional brain connectivity architecture on a whole brain and network level in patients with Parkinson's disease. Methods: Whole brain resting-state functional architecture was studied with a recently introduced graph analysis approach (eigenvector centrality mapping). Functional connectivity was further investigated in relation to eight known resting-state networks. Cross-sectional analyses included group comparison of functional connectivity measures of Parkinson's disease patients (n = 107) with control subjects (n = 58) and correlations with clinical data, including motor and cognitive impairment and a composite measure of predominantly non-dopaminergic symptoms. Results: Eigenvector centrality mapping revealed that frontoparietal regions were more prominent in the whole-brain network function in patients compared to control subjects, while frontal and occipital brain areas were less prominent in patients. Using standard resting-state networks, we found predominantly increased functional connectivity, namely within sensorimotor system and visual networks in patients. Regional group differences in functional connectivity of both techniques between patients and control subjects partly overlapped for highly connected posterior brain regions, in particular in the posterior cingulate cortex and precuneus. Clinico-functional imaging relations were not found. Conclusions: Changes on the level of functional brain connectivity architecture might provide a different perspective of pathological consequences of Parkinson's disease. The involvement of specific, highly connected (hub) brain regions may influence whole brain functional network architecture in Parkinson's disease.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 116 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 116 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 19%
Student > Master 14 12%
Researcher 14 12%
Student > Bachelor 12 10%
Other 8 7%
Other 11 9%
Unknown 35 30%
Readers by discipline Count As %
Neuroscience 27 23%
Medicine and Dentistry 13 11%
Engineering 11 9%
Psychology 7 6%
Biochemistry, Genetics and Molecular Biology 4 3%
Other 12 10%
Unknown 42 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 29 June 2018.
All research outputs
#3,283,696
of 23,088,369 outputs
Outputs from Frontiers in Neurology
#2,650
of 12,001 outputs
Outputs of similar age
#67,764
of 329,353 outputs
Outputs of similar age from Frontiers in Neurology
#49
of 315 outputs
Altmetric has tracked 23,088,369 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,001 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 73% 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 329,353 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 79% of its contemporaries.
We're also able to compare this research output to 315 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.