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Sensors (Basel). 2017 Dec 16;17(12). pii: E2926. doi: 10.3390/s17122926.

Choice of Magnetometers and Gradiometers after Signal Space Separation.

Author information

1
Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology, 28223 Madrid, Spain. mpgarces@ucm.es.
2
Biomedical Research Networking Center in Bioengineering Biomaterials and Nanomedicine (CIBER-BBN), Av. Monforte de Lemos 3-5, 28029 Madrid, Spain. mpgarces@ucm.es.
3
Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology, 28223 Madrid, Spain. david.lopez@ctb.upm.es.
4
Biomedical Research Networking Center in Bioengineering Biomaterials and Nanomedicine (CIBER-BBN), Av. Monforte de Lemos 3-5, 28029 Madrid, Spain. david.lopez@ctb.upm.es.
5
Department of Basic Psychology II, Faculty of Psychology, Universidad Complutense de Madrid, 28223 Madrid, Spain. david.lopez@ctb.upm.es.
6
Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology, 28223 Madrid, Spain. fernando.maestu@ctb.upm.es.
7
Biomedical Research Networking Center in Bioengineering Biomaterials and Nanomedicine (CIBER-BBN), Av. Monforte de Lemos 3-5, 28029 Madrid, Spain. fernando.maestu@ctb.upm.es.
8
Department of Basic Psychology II, Faculty of Psychology, Universidad Complutense de Madrid, 28223 Madrid, Spain. fernando.maestu@ctb.upm.es.
9
Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology, 28223 Madrid, Spain. eperdepa@ull.edu.es.
10
Department of Industrial Engineering, Instituto Universitario de Neurociencia, Universidad de La Laguna, 38205 Tenerife, Spain. eperdepa@ull.edu.es.

Abstract

BACKGROUND:

Modern Elekta Neuromag MEG devices include 102 sensor triplets containing one magnetometer and two planar gradiometers. The first processing step is often a signal space separation (SSS), which provides a powerful noise reduction. A question commonly raised by researchers and reviewers relates to which data should be employed in analyses: (1) magnetometers only, (2) gradiometers only, (3) magnetometers and gradiometers together. The MEG community is currently divided with regard to the proper answer.

METHODS:

First, we provide theoretical evidence that both gradiometers and magnetometers result from the backprojection of the same SSS components. Then, we compare resting state and task-related sensor and source estimations from magnetometers and gradiometers in real MEG recordings before and after SSS.

RESULTS:

SSS introduced a strong increase in the similarity between source time series derived from magnetometers and gradiometers (r² = 0.3-0.8 before SSS and r² > 0.80 after SSS). After SSS, resting state power spectrum and functional connectivity, as well as visual evoked responses, derived from both magnetometers and gradiometers were highly similar (Intraclass Correlation Coefficient > 0.8, r² > 0.8).

CONCLUSIONS:

After SSS, magnetometer and gradiometer data are estimated from a single set of SSS components (usually ≤ 80). Equivalent results can be obtained with both sensor types in typical MEG experiments.

KEYWORDS:

beamforming; gradiometer; magnetoencephalography; magnetometer; regularization; signal space separation

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