Towards Automatic Artifact Rejection in Resting-State MEG Recordings: Evaluating the Performance of the SOUND Algorithm

In this study, a new automated noise rejection algorithm, the SOurce-estimate-Utilizing Noise-Discarding algorithm (SOUND), was evaluated on magnetoencephalographic (MEG) resting-state signals in order to select its optimal configuration parameters. Different values of the epoch length and the regul...

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Bibliographic Details
Main Authors: Rodriguez-Gonzalez, Victor, Poza, Jesus, Nunez, Pablo, Gomez, Carlos, Garcia, Maria, Shigihara, Yoshihito, Hoshi, Hideyuki, Santamaria-Vazquez, Eduardo, Hornero, Roberto
Format: Conference Proceeding
Language:English
Subjects:
Brain
IEEE Senior Members
Lead
Noise level
Noise measurement
Sensors
Signal to noise ratio
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Summary:In this study, a new automated noise rejection algorithm, the SOurce-estimate-Utilizing Noise-Discarding algorithm (SOUND), was evaluated on magnetoencephalographic (MEG) resting-state signals in order to select its optimal configuration parameters. Different values of the epoch length and the regularization parameter λ 0 were assessed in three scenarios with ascending noise levels. Results show that it is possible to remarkably improve the Signal-to-Noise Ratio, without overly altering the signal of interest. An optimal λ 0 value of 0.1 was obtained. However, the epoch length should be adapted to the specific problem. In conclusion, our results suggest that the SOUND algorithm is an appropriate and useful tool to be applied in a preprocessing pipeline for MEG restingstate signals.
ISSN:1558-4615
2694-0604
DOI:10.1109/EMBC.2019.8856587