Q2. How many BCG components can be expected after ICA processing?
Three to six BCG components can be expected after ICA processing, whereas one or two ICs related to both ocular and imaging artifacts are generally separated.
Q3. How many EEG datasets were used for the validation of the proposed method?
The authors used seven EEG datasets acquired during fMRI scanning (right-handed healthy subjects, age 19–24 years) for the validation of the proposed method.
Q4. What are the main types of disturbances that can be found in the EEG and f?
Among them, imaging and BCG artifacts are produced by the MRI environment, whereas ocular artifacts can also be found if the acquisition is performed out of the MRI scanner.
Q5. What is the correlation value of the ICs with the ECG signal?
3.For the BCG artifact components, the correlation values with the ECG signal ranged between 0.25 and 0.47 (p<0.001); conversely, the remaining ICs showed correlations lower than 0.07 (p<0.001).
Q6. What was the effect of the ICA on the removal of the BCG artifact?
Given the characteristics of eye movements, which are fast and occur randomly, the ability of ICA to remove ocular artifacts wastested by setting an amplitude threshold to the EEG recordings: all epochs with amplitude larger than 80 μV were assumed to contain this kind of artifacts and were considered not to be useful for further analysis.
Q7. What is the popular technique for the attenuation of imaging artifact?
The most popular processing technique for the attenuation of imaging artifact is averaged artifact subtraction (AAS) (Allen et al., 1998; Allen et al., 2000).
Q8. What is the amplitude of the BCG artifacts after ICA?
For each subject, noise amplitude in the 100 ms prestimulus baseline after preprocessing, as well after ICA-based artifact removal and standard artifact removal, is shown for rare and frequent events respectively.
Q9. What is the alternative technique for the elimination of BCG artifacts?
An interesting alternative technique for the elimination of BCG artifacts is the independent component analysis (ICA), which has proved to perform better than AAS, because it makes no assumptions about the shape of the source signals and does not require the use of a reference signal (Srivastava et al., 2005).
Q10. What are the main kinds of disturbances that could be detected in the EEG and f?
In general, there are three main kinds of disturbances that could contaminate the EEG signal changes associated to cerebral activity and that should be removed from the recordings before further analysis: imaging, BCG and ocular artifacts.
Q11. What was the first approach to categorizing the EEG signals?
The second approach was based on the use of reference signals, such as the ECG and EOG recordings (whenever available), and the estimate of the imaging artifact: the occurrence of a large correlation value between the single IC and one of these reference signals indicated that the source signal had to be considered as an artifact.
Q12. What is the difference between the AAS and ICA method?
A remarkable result is that the ICA method performs better than the AAS method for the cancellation of the BCG artifact: AAS relies on averaged artifact subtraction and is affected by the variability in BCG artifact wave morphology and duration; conversely, ICA is able to isolate the BCG artifact components simply on the basis of their statistical independence from those produced by other neural signal generators and other artifact sources.
Q13. What was the noise amplitude in ERPs?
The noise amplitude in ERPs was calculated as the average root mean square (RMS) of the signal corresponding to the prestimulus interval.
Q14. What is the result of the removal of the BCG artifact?
The disturbances were subtracted from the preprocessed recordings with appropriate weights for each channel; the result of the artifact removal is shown in Fig.