CoChat
Sign Up
Cited by 102Atomic and Subatomic Physics ResearchAdvanced MRI Techniques and ApplicationsEEG and Brain-Computer Interfaces

The DOI matches its Crossref record; 62 of the 65 references it cites were found in a registry or an index.

Using OPMs to measure neural activity in standing, mobile participants

Open access
Seymour, Robert A., Alexander, Nicholas, Mellor, Stephanie, O'Neill, George C., Tierney, Tim M., Barnes, Gareth R., Maguire, Eleanor A.·2021·NeuroImage
DOI 10.1016/j.neuroimage.2021.118604PMC PMC8591613

Published version of a preprint

Open this paper in CoChat — free accountOpen PDF

Abstract

Optically pumped magnetometer-based magnetoencephalography (OP-MEG) can be used to measure neuromagnetic fields while participants move in a magnetically shielded room. Head movements in previous OP-MEG studies have been up to 20 cm translation and ∼30° rotation in a sitting position. While this represents a step-change over stationary MEG systems, naturalistic head movement is likely to exceed these limits, particularly when participants are standing up. In this proof-of-concept study, we sought to push the movement limits of OP-MEG even further. Using a 90 channel (45-sensor) whole-head OP-MEG system and concurrent motion capture, we recorded auditory evoked fields while participants were: (i) sitting still, (ii) standing up and still, and (iii) standing up and making large natural head movements continuously throughout the recording - maximum translation 120 cm, maximum rotation 198°. Following pre-processing, movement artefacts were substantially reduced but not eliminated. However, upon utilisation of a beamformer, the M100 event-related field localised to primary auditory regions. Furthermore, the event-related fields from auditory cortex were remarkably consistent across the three conditions. These results suggest that a wide range of movement is possible with current OP-MEG systems. This in turn underscores the exciting potential of OP-MEG for recording neural activity during naturalistic paradigms that involve movement (e.g. navigation), and for scanning populations who are difficult to study with stationary MEG (e.g. young children).

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.neuroimage.2021.118604

Cites

62 of 62 references verified0 citation errors · 0 not checkable

Statistics

Figures

Fig. 1 (A) The experimental setup. Inside the magnetically shielded room OPM sensors were secured in a 3D printed scanner-cast with cables fixed into a backpack. (B) The location of the sensors for participant 1, plotted on a 3D mesh derived from the participant's de-faced structural MRI scan. Sensitive axes are shown by the blue lines. (C) The six degrees of freedom used to describe the translation and rotation of the rigid body.
Fig. 1 (A) The experimental setup. Inside the magnetically shielded room OPM sensors were secured in a 3D printed scanner-cast with cables fixed into a backpack. (B) The location of the sensors for participant 1, plotted on a 3D mesh derived from the participant's de-faced structural MRI scan. Sensitive axes are shown by the blue lines. (C) The six degrees of freedom used to describe the translation and rotation of the rigid body.CC BY · PubMed Central
Fig. 2 Histograms showing the range of movement across each degree of freedom of the continuous rigid body data. For reference, colours match the transformations shown in Fig. 1C.
Fig. 2 Histograms showing the range of movement across each degree of freedom of the continuous rigid body data. For reference, colours match the transformations shown in Fig. 1C.CC BY · PubMed Central
Fig. 3 Bar graph showing, for each participant, Euclidian distance of the rigid body travelled during each 0.5 s trial. Error bars correspond to 95% confidence intervals and individual trial data points are shown in grey.
Fig. 3 Bar graph showing, for each participant, Euclidian distance of the rigid body travelled during each 0.5 s trial. Error bars correspond to 95% confidence intervals and individual trial data points are shown in grey.CC BY · PubMed Central
Fig. 4 Sensor-level data. For each condition (sitting, standing, standing and moving), evoked waveforms are plotted alongside a 2D fieldmap for data from 0.08 s to 0.12 s post-stimulus onset. The fieldmap only shows magnetic fields orientated radially to the head.
Fig. 4 Sensor-level data. For each condition (sitting, standing, standing and moving), evoked waveforms are plotted alongside a 2D fieldmap for data from 0.08 s to 0.12 s post-stimulus onset. The fieldmap only shows magnetic fields orientated radially to the head.CC BY · PubMed Central
Fig. 5 Whole-brain M100 source localisation results. The Neural Activity Index (NAI) was calculated for each run between 0.08–0.12 s post-stimulus onset, corresponding to the M100 auditory evoked field, and plotted on a canonical MRI using FSL. Maps were thresholded at 75% of their maximum value, for illustrative purposes.
Fig. 5 Whole-brain M100 source localisation results. The Neural Activity Index (NAI) was calculated for each run between 0.08–0.12 s post-stimulus onset, corresponding to the M100 auditory evoked field, and plotted on a canonical MRI using FSL. Maps were thresholded at 75% of their maximum value, for illustrative purposes.CC BY · PubMed Central
Fig. 6 Evoked waveforms plotted from the auditory cortex ROI. Note the similarity in t-values across the sitting, standing, standing and moving runs for both participants.
Fig. 6 Evoked waveforms plotted from the auditory cortex ROI. Note the similarity in t-values across the sitting, standing, standing and moving runs for both participants.CC BY · PubMed Central
Fig. 7 Removal of movement-related artefacts. (A-B) Power spectral density (PSD) was calculated for the OPM sensor with the greatest M100 response using both raw data and after pre-processing. (C) PSD was also calculated using the source-level auditory cortex ROI data. For all plots, PSD spectra are plotted between 2 and 10 Hz, and were averaged over the two participants.
Fig. 7 Removal of movement-related artefacts. (A-B) Power spectral density (PSD) was calculated for the OPM sensor with the greatest M100 response using both raw data and after pre-processing. (C) PSD was also calculated using the source-level auditory cortex ROI data. For all plots, PSD spectra are plotted between 2 and 10 Hz, and were averaged over the two participants.CC BY · PubMed Central
Fig. 8 Investigating sensor-level pre-processing steps. (A) Power spectral density (PSD) was calculated for the OPM sensor with the greatest M100 response. PSD was plotted separately for sensor-level data with/without the movement data regression step, and with/without homogenous field correction (HFC). (B) PSD was calculated in the same way using the source-level auditory cortex ROI data. For all plots, PSD spectra were averaged over the two participants.
Fig. 8 Investigating sensor-level pre-processing steps. (A) Power spectral density (PSD) was calculated for the OPM sensor with the greatest M100 response. PSD was plotted separately for sensor-level data with/without the movement data regression step, and with/without homogenous field correction (HFC). (B) PSD was calculated in the same way using the source-level auditory cortex ROI data. For all plots, PSD spectra were averaged over the two participants.CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Research works printed but not linked: 1

  1. Hari, 1990, The neuromagnetic method in the study of the human auditory cortex, Adv. Audiol., 6, 222

Cited by

Sorted by citations

See all 102

Related

See all

Metadata

Authors
Seymour, R. A., Alexander, N., Mellor, S., O'Neill, G. C., Tierney, T. M., Barnes, G. R., & Maguire, E. A.
Affiliations
Wellcome Centre for Human Neuroimaging (GB)
Corresponding author
  • Seymour, Robert A.
  • Maguire, Eleanor A.
ORCID
Venue
NeuroImage
Publisher
Elsevier BV
Published
2021-12
Volume
244
Pages
118604
ISSN
1053-8119 (ISSN-L)
DOI
10.1016/j.neuroimage.2021.118604
PMC
PMC8591613
OpenAlex
W3200893299
Cited by
102
References
65
Citations by year
2026: 16 · 2025: 27 · 2024: 19 · 2023: 19 · 2022: 18 · 2021: 3
FWCI
6.44
Type
journal article
Language
en
Open access
Licence
Locations
  • NeuroImage (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Wellcome Trust
  • University of Nottingham
Topics
  • Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Atomic and Subatomic Physics Research
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
  • Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
Keywords
optically pumped magnetometers, magnetoencephalography, head movement, standing up, motion artifacts, auditory evoked magnetic fields, M100, primary auditory cortex, beamforming, motion capture, naturalistic paradigm
MeSH terms
Proof of Concept Study, Standing Position, Adult, Auditory Cortex, Evoked Potentials, Auditory, Head, Humans, Male, Rotation, Magnetoencephalography, Artifacts, Head Movements

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review