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Probabilistic atlases of default mode, executive control and salience network white matter tracts: an fMRI-guided diffusion tensor imaging and tractography study

Overview of attention for article published in Frontiers in Human Neuroscience, November 2015
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  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

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Title
Probabilistic atlases of default mode, executive control and salience network white matter tracts: an fMRI-guided diffusion tensor imaging and tractography study
Published in
Frontiers in Human Neuroscience, November 2015
DOI 10.3389/fnhum.2015.00585
Pubmed ID
Authors

Teresa D. Figley, Navdeep Bhullar, Susan M. Courtney, Chase R. Figley

Abstract

Diffusion tensor imaging (DTI) is a powerful MRI technique that can be used to estimate both the microstructural integrity and the trajectories of white matter pathways throughout the central nervous system. This fiber tracking (aka, "tractography") approach is often carried out using anatomically-defined seed points to identify white matter tracts that pass through one or more structures, but can also be performed using functionally-defined regions of interest (ROIs) that have been determined using functional MRI (fMRI) or other methods. In this study, we performed fMRI-guided DTI tractography between all of the previously defined nodes within each of six common resting-state brain networks, including the: dorsal Default Mode Network (dDMN), ventral Default Mode Network (vDMN), left Executive Control Network (lECN), right Executive Control Network (rECN), anterior Salience Network (aSN), and posterior Salience Network (pSN). By normalizing the data from 32 healthy control subjects to a standard template-using high-dimensional, non-linear warping methods-we were able to create probabilistic white matter atlases for each tract in stereotaxic coordinates. By investigating all 198 ROI-to-ROI combinations within the aforementioned resting-state networks (for a total of 6336 independent DTI tractography analyses), the resulting probabilistic atlases represent a comprehensive cohort of functionally-defined white matter regions that can be used in future brain imaging studies to: (1) ascribe DTI or other white matter changes to particular functional brain networks, and (2) compliment resting state fMRI or other functional connectivity analyses.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 142 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 2 1%
Germany 1 <1%
France 1 <1%
United Kingdom 1 <1%
Brazil 1 <1%
Japan 1 <1%
United States 1 <1%
Unknown 134 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 33 23%
Researcher 24 17%
Student > Master 17 12%
Student > Doctoral Student 12 8%
Other 10 7%
Other 21 15%
Unknown 25 18%
Readers by discipline Count As %
Neuroscience 26 18%
Medicine and Dentistry 23 16%
Psychology 22 15%
Engineering 11 8%
Agricultural and Biological Sciences 8 6%
Other 13 9%
Unknown 39 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 20 November 2015.
All research outputs
#6,799,606
of 22,829,683 outputs
Outputs from Frontiers in Human Neuroscience
#2,844
of 7,152 outputs
Outputs of similar age
#85,783
of 285,125 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#57
of 158 outputs
Altmetric has tracked 22,829,683 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 7,152 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.6. This one has gotten more attention than average, scoring higher than 59% 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 285,125 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 69% of its contemporaries.
We're also able to compare this research output to 158 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 63% of its contemporaries.