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The Conundrum of Functional Brain Networks: Small-World Efficiency or Fractal Modularity

Overview of attention for article published in Frontiers in Physiology, January 2012
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Title
The Conundrum of Functional Brain Networks: Small-World Efficiency or Fractal Modularity
Published in
Frontiers in Physiology, January 2012
DOI 10.3389/fphys.2012.00123
Pubmed ID
Authors

Lazaros K. Gallos, Mariano Sigman, Hernán A. Makse

Abstract

The human brain has been studied at multiple scales, from neurons, circuits, areas with well-defined anatomical and functional boundaries, to large-scale functional networks which mediate coherent cognition. In a recent work, we addressed the problem of the hierarchical organization in the brain through network analysis. Our analysis identified functional brain modules of fractal structure that were inter-connected in a small-world topology. Here, we provide more details on the use of network science tools to elaborate on this behavior. We indicate the importance of using percolation theory to highlight the modular character of the functional brain network. These modules present a fractal, self-similar topology, identified through fractal network methods. When we lower the threshold of correlations to include weaker ties, the network as a whole assumes a small-world character. These weak ties are organized precisely as predicted by theory maximizing information transfer with minimal wiring costs.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 104 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 <1%
Italy 1 <1%
South Africa 1 <1%
Finland 1 <1%
United Kingdom 1 <1%
Belarus 1 <1%
Spain 1 <1%
Unknown 97 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 29 28%
Student > Ph. D. Student 22 21%
Student > Master 11 11%
Professor > Associate Professor 8 8%
Student > Doctoral Student 7 7%
Other 15 14%
Unknown 12 12%
Readers by discipline Count As %
Computer Science 14 13%
Neuroscience 12 12%
Agricultural and Biological Sciences 12 12%
Medicine and Dentistry 12 12%
Physics and Astronomy 12 12%
Other 30 29%
Unknown 12 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 13 January 2013.
All research outputs
#20,941,392
of 23,577,654 outputs
Outputs from Frontiers in Physiology
#9,792
of 14,285 outputs
Outputs of similar age
#224,989
of 247,799 outputs
Outputs of similar age from Frontiers in Physiology
#207
of 306 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,285 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one is in the 1st percentile – i.e., 1% 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 247,799 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 306 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.