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Fluctuations of the EEG-fMRI correlation reflect intrinsic strength of functional connectivity in default mode network

Overview of attention for article published in Journal of Neuroscience Research, May 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Average Attention Score compared to outputs of the same age and source

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11 tweeters
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1 Facebook page

Citations

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8 Dimensions

Readers on

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29 Mendeley
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2 CiteULike
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Title
Fluctuations of the EEG-fMRI correlation reflect intrinsic strength of functional connectivity in default mode network
Published in
Journal of Neuroscience Research, May 2018
DOI 10.1002/jnr.24257
Pubmed ID
Authors

Tuija Keinänen, Seppo Rytky, Vesa Korhonen, Niko Huotari, Juha Nikkinen, Osmo Tervonen, J. Matias Palva, Vesa Kiviniemi

Abstract

Both functional magnetic resonance imaging (fMRI) and electrophysiological recordings have revealed that resting-state functional connectivity is temporally variable in human brain. Combined full-band electroencephalography-fMRI (fbEEG-fMRI) studies have shown that infraslow (<.1 Hz) fluctuations in EEG scalp potential are correlated with the blood-oxygen-level-dependent (BOLD) fMRI signals and that also this correlation appears variable over time. Here, we used simultaneous fbEEG-fMRI to test the hypothesis that correlation dynamics between BOLD and fbEEG signals could be explained by fluctuations in the activation properties of resting-state networks (RSNs) such as the extent or strength of their activation. We used ultrafast magnetic resonance encephalography (MREG) fMRI to enable temporally accurate and statistically robust short-time-window comparisons of infra-slow fbEEG and BOLD signals. We found that the temporal fluctuations in the fbEEG-BOLD correlation were dependent on RSN connectivity strength, but not on the mean signal level or magnitude of RSN activation or motion during scanning. Moreover, the EEG-fMRI correlations were strongest when the intrinsic RSN connectivity was strong and close to the pial surface. Conversely, weak fbEEG-BOLD correlations were attributable to periods of less coherent or spatially more scattered intrinsic RSN connectivity, or RSN activation in deeper cerebral structures. The results thus show that the on-average low correlations between infra-slow EEG and BOLD signals are, in fact, governed by the momentary coherence and depth of the underlying RSN activation, and may reach systematically high values with appropriate source activities. These findings further consolidate the notion of slow scalp potentials being directly coupled to hemodynamic fluctuations.

Twitter Demographics

The data shown below were collected from the profiles of 11 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 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 29 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 10 34%
Student > Ph. D. Student 7 24%
Student > Postgraduate 3 10%
Researcher 2 7%
Professor 1 3%
Other 3 10%
Unknown 3 10%
Readers by discipline Count As %
Neuroscience 14 48%
Medicine and Dentistry 4 14%
Earth and Planetary Sciences 2 7%
Psychology 2 7%
Computer Science 2 7%
Other 2 7%
Unknown 3 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 18 July 2018.
All research outputs
#3,014,942
of 13,243,534 outputs
Outputs from Journal of Neuroscience Research
#785
of 2,735 outputs
Outputs of similar age
#77,493
of 268,747 outputs
Outputs of similar age from Journal of Neuroscience Research
#30
of 49 outputs
Altmetric has tracked 13,243,534 research outputs across all sources so far. Compared to these this one has done well and is in the 77th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,735 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 71% 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 268,747 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 71% of its contemporaries.
We're also able to compare this research output to 49 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.