↓ Skip to main content

Constructing Carbon Fiber Motion-Detection Loops for Simultaneous EEG–fMRI

Overview of attention for article published in Frontiers in Neurology, January 2015
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
28 Dimensions

Readers on

mendeley
52 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Constructing Carbon Fiber Motion-Detection Loops for Simultaneous EEG–fMRI
Published in
Frontiers in Neurology, January 2015
DOI 10.3389/fneur.2014.00260
Pubmed ID
Authors

David F. Abbott, Richard A. J. Masterton, John S. Archer, Steven W. Fleming, Aaron E. L. Warren, Graeme D. Jackson

Abstract

One of the most significant impediments to high-quality EEG recorded in an MRI scanner is subject motion. Availability of motion artifact sensors can substantially improve the quality of the recorded EEG. In the study of epilepsy, it can also dramatically increase the confidence that one has in discriminating true epileptiform activity from artifact. This is due both to the reduction in artifact and the ability to visually inspect the motion sensor signals when reading the EEG, revealing whether or not head motion is present. We have previously described the use of carbon fiber loops for detecting and correcting artifact in EEG acquired simultaneously with MRI. The loops, attached to the subject's head, are electrically insulated from the scalp. They provide a simple and direct measure of specific artifact that is contaminating the EEG, including both subject motion and residual artifact arising from magnetic field gradients applied during MRI. Our previous implementation was used together with a custom-built EEG-fMRI system that differs substantially from current commercially available EEG-fMRI systems. The present technical note extends this work, describing in more detail how to construct the carbon fiber motion-detection loops, and how to interface them with a commercially available simultaneous EEG-fMRI system. We hope that the information provided may help those wishing to utilize a motion-detection/correction solution to improve the quality of EEG recorded within an MRI scanner.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Hungary 1 2%
Germany 1 2%
Unknown 50 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 33%
Researcher 10 19%
Student > Master 10 19%
Lecturer > Senior Lecturer 2 4%
Professor 1 2%
Other 3 6%
Unknown 9 17%
Readers by discipline Count As %
Neuroscience 11 21%
Medicine and Dentistry 8 15%
Engineering 6 12%
Psychology 3 6%
Physics and Astronomy 2 4%
Other 6 12%
Unknown 16 31%
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 05 January 2015.
All research outputs
#20,248,338
of 22,776,824 outputs
Outputs from Frontiers in Neurology
#8,673
of 11,666 outputs
Outputs of similar age
#295,393
of 352,499 outputs
Outputs of similar age from Frontiers in Neurology
#79
of 82 outputs
Altmetric has tracked 22,776,824 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 11,666 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. 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 352,499 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 82 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.