![]() ![]() ![]() 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. ![]() Moreover, nonencephalic electromagnetic activity, such as that from the eyes and from the cardiac and facial muscles, is also recorded by EEG or MEG and can be up to a thousand times stronger than the encephalic signal of interest. Since the interfering environmental noise from, for example, laboratory mechanics and electronic devices may be several orders of magnitude stronger than the brain signals of interest (for a review, see, e.g., ), it is necessary to remove this noise from the recordings during or after the measurements. One of the major challenges in research and clinical applications of evoked-responses is the prevalent strongly interfering electromagnetic signals from external objects and devices in the surrounding MEG or EEG measurement environment as well as nearby mechanical and biological electromagnetic sources originating from the head and other parts of the body of the subject. Recordings of evoked-responses (also known as event-related potentials, ERPs, or event-related fields, ERFs) with electroencephalography (EEG) or magnetoencephalography (MEG) are widely used methods in cognitive and clinical neuroscience. 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. 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. 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. Furthermore, we found that better artifact correction is achieved by applying Independent Component Analysis (ICA) in comparison to Signal Space Projection (SSP). 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. We compared the Signal Space Separation (SSS) and temporal SSS (tSSS) methods for reducing noise from external and nearby sources. All rights reserved.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.
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