↓ Skip to main content

Moving magnetoencephalography towards real-world applications with a wearable system

Overview of attention for article published in Nature, March 2018
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Readers on

mendeley
820 Mendeley
citeulike
2 CiteULike
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
Moving magnetoencephalography towards real-world applications with a wearable system
Published in
Nature, March 2018
DOI 10.1038/nature26147
Pubmed ID
Authors

Elena Boto, Niall Holmes, James Leggett, Gillian Roberts, Vishal Shah, Sofie S. Meyer, Leonardo Duque Muñoz, Karen J. Mullinger, Tim M. Tierney, Sven Bestmann, Gareth R. Barnes, Richard Bowtell, Matthew J. Brookes

Abstract

Imaging human brain function with techniques such as magnetoencephalography typically requires a subject to perform tasks while their head remains still within a restrictive scanner. This artificial environment makes the technique inaccessible to many people, and limits the experimental questions that can be addressed. For example, it has been difficult to apply neuroimaging to investigation of the neural substrates of cognitive development in babies and children, or to study processes in adults that require unconstrained head movement (such as spatial navigation). Here we describe a magnetoencephalography system that can be worn like a helmet, allowing free and natural movement during scanning. This is possible owing to the integration of quantum sensors, which do not rely on superconducting technology, with a system for nulling background magnetic fields. We demonstrate human electrophysiological measurement at millisecond resolution while subjects make natural movements, including head nodding, stretching, drinking and playing a ball game. Our results compare well to those of the current state-of-the-art, even when subjects make large head movements. The system opens up new possibilities for scanning any subject or patient group, with myriad applications such as characterization of the neurodevelopmental connectome, imaging subjects moving naturally in a virtual environment and investigating the pathophysiology of movement disorders.

X Demographics

X Demographics

The data shown below were collected from the profiles of 471 X users 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 820 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 820 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 162 20%
Researcher 144 18%
Student > Master 76 9%
Student > Bachelor 61 7%
Professor 47 6%
Other 124 15%
Unknown 206 25%
Readers by discipline Count As %
Neuroscience 153 19%
Engineering 97 12%
Physics and Astronomy 79 10%
Psychology 60 7%
Medicine and Dentistry 48 6%
Other 121 15%
Unknown 262 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 926. 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 28 March 2024.
All research outputs
#18,736
of 25,805,386 outputs
Outputs from Nature
#1,844
of 98,828 outputs
Outputs of similar age
#382
of 348,809 outputs
Outputs of similar age from Nature
#32
of 914 outputs
Altmetric has tracked 25,805,386 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 98,828 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 102.7. This one has done particularly well, scoring higher than 98% 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 348,809 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 99% of its contemporaries.
We're also able to compare this research output to 914 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.