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Detection of Motor Changes in Huntington's Disease Using Dynamic Causal Modeling

Overview of attention for article published in Frontiers in Human Neuroscience, November 2015
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Title
Detection of Motor Changes in Huntington's Disease Using Dynamic Causal Modeling
Published in
Frontiers in Human Neuroscience, November 2015
DOI 10.3389/fnhum.2015.00634
Pubmed ID
Authors

Lora Minkova, Elisa Scheller, Jessica Peter, Ahmed Abdulkadir, Christoph P. Kaller, Raymund A. Roos, Alexandra Durr, Blair R. Leavitt, Sarah J. Tabrizi, Stefan Klöppel, TrackOn-HD Investigators, A. Coleman, J. Decolongon, M. Fan, T. Koren, C. Jauffret, D. Justo, S. Lehericy, K. Nigaud, R. Valabrègue, A. Schoonderbeek, P. E. ‘t Hart, H. Crawford, S. Gregory, D. Hensman Moss, E. Johnson, J. Read, G. Owen, M. Papoutsi, C. Berna, A. Razi, G. Rees, I. R. Scahill, D. Craufurd, R. Reilmann, N. Weber, J. Stout, I. Labuschagne, M. Orth, B. G. Landwehrmeyer, D. Langbehn, H. Johnson, J. Long, J. Mills

Abstract

Deficits in motor functioning are one of the hallmarks of Huntington's disease (HD), a genetically caused neurodegenerative disorder. We applied functional magnetic resonance imaging (fMRI) and dynamic causal modeling (DCM) to assess changes that occur with disease progression in the neural circuitry of key areas associated with executive and cognitive aspects of motor control. Seventy-seven healthy controls, 62 pre-symptomatic HD gene carriers (preHD), and 16 patients with manifest HD symptoms (earlyHD) performed a motor finger-tapping fMRI task with systematically varying speed and complexity. DCM was used to assess the causal interactions among seven pre-defined regions of interest, comprising primary motor cortex, supplementary motor area (SMA), dorsal premotor cortex, and superior parietal cortex. To capture heterogeneity among HD gene carriers, DCM parameters were entered into a hierarchical cluster analysis using Ward's method and squared Euclidian distance as a measure of similarity. After applying Bonferroni correction for the number of tests, DCM analysis revealed a group difference that was not present in the conventional fMRI analysis. We found an inhibitory effect of complexity on the connection from parietal to premotor areas in preHD, which became excitatory in earlyHD and correlated with putamen atrophy. While speed of finger movements did not modulate the connection from caudal to pre-SMA in controls and preHD, this connection became strongly negative in earlyHD. This second effect did not survive correction for multiple comparisons. Hierarchical clustering separated the gene mutation carriers into three clusters that also differed significantly between these two connections and thereby confirmed their relevance. DCM proved useful in identifying group differences that would have remained undetected by standard analyses and may aid in the investigation of between-subject heterogeneity.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Malaysia 1 1%
United States 1 1%
Germany 1 1%
Belgium 1 1%
Unknown 71 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 23%
Student > Ph. D. Student 16 21%
Student > Master 11 15%
Other 5 7%
Professor > Associate Professor 4 5%
Other 12 16%
Unknown 10 13%
Readers by discipline Count As %
Neuroscience 15 20%
Psychology 8 11%
Medicine and Dentistry 7 9%
Agricultural and Biological Sciences 6 8%
Engineering 6 8%
Other 13 17%
Unknown 20 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 05 December 2015.
All research outputs
#14,828,686
of 22,834,308 outputs
Outputs from Frontiers in Human Neuroscience
#4,916
of 7,155 outputs
Outputs of similar age
#214,790
of 386,751 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#101
of 151 outputs
Altmetric has tracked 22,834,308 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,155 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.6. This one is in the 27th percentile – i.e., 27% of its peers scored the same or lower than it.
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 386,751 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 151 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.