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Graph theoretical analysis of resting magnetoencephalographic functional connectivity networks

Overview of attention for article published in Frontiers in Computational Neuroscience, January 2013
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Title
Graph theoretical analysis of resting magnetoencephalographic functional connectivity networks
Published in
Frontiers in Computational Neuroscience, January 2013
DOI 10.3389/fncom.2013.00093
Pubmed ID
Authors

Lindsay Rutter, Sreenivasan R. Nadar, Tom Holroyd, Frederick W. Carver, Jose Apud, Daniel R. Weinberger, Richard Coppola

Abstract

Complex networks have been observed to comprise small-world properties, believed to represent an optimal organization of local specialization and global integration of information processing at reduced wiring cost. Here, we applied magnitude squared coherence to resting magnetoencephalographic time series in reconstructed source space, acquired from controls and patients with schizophrenia, and generated frequency-dependent adjacency matrices modeling functional connectivity between virtual channels. After configuring undirected binary and weighted graphs, we found that all human networks demonstrated highly localized clustering and short characteristic path lengths. The most conservatively thresholded networks showed efficient wiring, with topographical distance between connected vertices amounting to one-third as observed in surrogate randomized topologies. Nodal degrees of the human networks conformed to a heavy-tailed exponentially truncated power-law, compatible with the existence of hubs, which included theta and alpha bilateral cerebellar tonsil, beta and gamma bilateral posterior cingulate, and bilateral thalamus across all frequencies. We conclude that all networks showed small-worldness, minimal physical connection distance, and skewed degree distributions characteristic of physically-embedded networks, and that these calculations derived from graph theoretical mathematics did not quantifiably distinguish between subject populations, independent of bandwidth. However, post-hoc measurements of edge computations at the scale of the individual vertex revealed trends of reduced gamma connectivity across the posterior medial parietal cortex in patients, an observation consistent with our prior resting activation study that found significant reduction of synthetic aperture magnetometry gamma power across similar regions. The basis of these small differences remains unclear.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 95 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 3%
Denmark 2 2%
United States 1 1%
Finland 1 1%
Unknown 88 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 22 23%
Student > Ph. D. Student 19 20%
Student > Master 15 16%
Student > Doctoral Student 6 6%
Professor 6 6%
Other 12 13%
Unknown 15 16%
Readers by discipline Count As %
Neuroscience 14 15%
Medicine and Dentistry 13 14%
Psychology 13 14%
Engineering 10 11%
Agricultural and Biological Sciences 9 9%
Other 15 16%
Unknown 21 22%
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 12 July 2013.
All research outputs
#18,942,832
of 24,143,470 outputs
Outputs from Frontiers in Computational Neuroscience
#995
of 1,403 outputs
Outputs of similar age
#218,416
of 288,617 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#85
of 134 outputs
Altmetric has tracked 24,143,470 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,403 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
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We're also able to compare this research output to 134 others from the same source and published within six weeks on either side of this one. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.