Choice of Magnetometers and Gradiometers after Signal Space Separation
AbstractBackground: 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. View Full-Text
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Garcés, P.; López-Sanz, D.; Maestú, F.; Pereda, E. Choice of Magnetometers and Gradiometers after Signal Space Separation. Sensors 2017, 17, 2926.
Garcés P, López-Sanz D, Maestú F, Pereda E. Choice of Magnetometers and Gradiometers after Signal Space Separation. Sensors. 2017; 17(12):2926.Chicago/Turabian Style
Garcés, Pilar; López-Sanz, David; Maestú, Fernando; Pereda, Ernesto. 2017. "Choice of Magnetometers and Gradiometers after Signal Space Separation." Sensors 17, no. 12: 2926.
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