Abstract
We here compared results achieved by applying popular methods for reducing artifacts in magnetoencephalography (MEG) and electroencephalography (EEG) recordings of the auditory evoked Mismatch Negativity (MMN) responses in healthy adult subjects. We compared the Signal Space Separation (SSS) and temporal SSS (tSSS) methods for reducing noise from external and nearby sources. Our results showed that tSSS reduces the interference level more reliably than plain SSS, particularly for MEG gradiometers, also for healthy subjects not wearing strongly interfering magnetic material. Therefore, tSSS is recommended over SSS. Furthermore, we found that better artifact correction is achieved by applying Independent Component Analysis (ICA) in comparison to Signal Space Projection (SSP). Although SSP reduces the baseline noise level more than ICA, SSP also significantly reduces the signal—slightly more than it reduces the artifacts interfering with the signal. However, ICA also adds noise, or correction errors, to the waveform when the signal-to-noise ratio (SNR) in the original data is relatively low—in particular to EEG and to MEG magnetometer data. In conclusion, ICA is recommended over SSP, but one should be careful when applying ICA to reduce artifacts on neurophysiological data with relatively low SNR.
Highlights
Recordings of evoked-responses with electroencephalography (EEG) or magnetoencephalography (MEG) are widely used methods in cognitive and clinical neuroscience
From grand average waveforms of the event-related responses, it can be seen that the Signal Space Projection (SSP)-based artifact correction reduces the signal amplitude, whereas the signal amplitude is similar before and after the artifact correction based on Independent Component Analysis (ICA)
The application of temporal SSS (tSSS) instead of Signal Space Separation (SSS) was important with respect to the MEG gradiometers, since SSS correction in 6% of the cases resulted in an increase of the noise level in the MEG gradiometer data, and the reliability of the gradiometer data decreased in comparison to that before SSS
Summary
Recordings of evoked-responses ( known as eventrelated potentials, ERPs, or event-related fields, ERFs) with electroencephalography (EEG) or magnetoencephalography (MEG) are widely used methods in cognitive and clinical neuroscience. Nonencephalic electromagnetic activity, such as that from the eyes and from the cardiac and facial muscles, is recorded by EEG or MEG and can be up to a thousand times stronger than the encephalic signal of interest [1]. Since some of these interfering artifactual signals can be synchronous with the brain signal of interest, significant parts of the continuous measurement can be contaminated by artifacts. To ensure a reliable measurement, it is necessary, in addition to applying an average measure of an evoked-response across
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
