RT Journal Article
T1 Choice of Magnetometers and Gradiometers after Signal Space Separation
A1 Garcés, Pilar
A1 López-Sanz, David
A1 Maestú Unturbe, Fernando
A1 Pereda, Ernesto
AB 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, r 2 > 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.
PB MDPI
SN 1424-8220
YR 2017
FD 2017
LK https://hdl.handle.net/20.500.14352/19090
UL https://hdl.handle.net/20.500.14352/19090
LA eng
NO Ministerio de Economía y Competitividad (MINECO)
NO UK Biotechnology and Biological Sciences Research Council
NO UK Medical Research Council and University of Cambridge
DS Docta Complutense
RD 30 abr 2024