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Time-resolved resting-state brain networks

Overview of attention for article published in Proceedings of the National Academy of Sciences of the United States of America, June 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

Mentioned by

twitter
25 tweeters
googleplus
1 Google+ user
video
1 video uploader

Citations

dimensions_citation
282 Dimensions

Readers on

mendeley
480 Mendeley
citeulike
3 CiteULike
Title
Time-resolved resting-state brain networks
Published in
Proceedings of the National Academy of Sciences of the United States of America, June 2014
DOI 10.1073/pnas.1400181111
Pubmed ID
Authors

A. Zalesky, A. Fornito, L. Cocchi, L. L. Gollo, M. Breakspear

Abstract

Neuronal dynamics display a complex spatiotemporal structure involving the precise, context-dependent coordination of activation patterns across a large number of spatially distributed regions. Functional magnetic resonance imaging (fMRI) has played a central role in demonstrating the nontrivial spatial and topological structure of these interactions, but thus far has been limited in its capacity to study their temporal evolution. Here, using high-resolution resting-state fMRI data obtained from the Human Connectome Project, we mapped time-resolved functional connectivity across the entire brain at a subsecond resolution with the aim of understanding how nonstationary fluctuations in pairwise interactions between regions relate to large-scale topological properties of the human brain. We report evidence for a consistent set of functional connections that show pronounced fluctuations in their strength over time. The most dynamic connections are intermodular, linking elements from topologically separable subsystems, and localize to known hubs of default mode and fronto-parietal systems. We found that spatially distributed regions spontaneously increased, for brief intervals, the efficiency with which they can transfer information, producing temporary, globally efficient network states. Our findings suggest that brain dynamics give rise to variations in complex network properties over time, possibly achieving a balance between efficient information-processing and metabolic expenditure.

Twitter Demographics

The data shown below were collected from the profiles of 25 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 480 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 13 3%
Germany 8 2%
United Kingdom 8 2%
Spain 3 <1%
Netherlands 3 <1%
France 2 <1%
China 2 <1%
Sweden 1 <1%
Belgium 1 <1%
Other 9 2%
Unknown 430 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 150 31%
Researcher 108 23%
Student > Master 59 12%
Professor > Associate Professor 32 7%
Student > Doctoral Student 26 5%
Other 105 22%
Readers by discipline Count As %
Neuroscience 94 20%
Psychology 88 18%
Unspecified 67 14%
Agricultural and Biological Sciences 63 13%
Engineering 46 10%
Other 122 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 January 2015.
All research outputs
#901,665
of 12,365,166 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#14,634
of 77,344 outputs
Outputs of similar age
#17,142
of 195,406 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#393
of 1,009 outputs
Altmetric has tracked 12,365,166 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 77,344 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 22.0. This one has done well, scoring higher than 81% 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 195,406 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 1,009 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 61% of its contemporaries.