[Eeglablist] continuous data - why do ICA on continuous data
arno at salk.edu
Thu Apr 7 11:03:06 PDT 2005
>Do you believe the reason 'better' results are obtained by doing ICA on
>continuous data rather than by doing ICA on concatenated epochs (that were
>previously segmented) is because of the discontinuities in the derivative of
>the signal at the concatenation boundries?
No this is unrelated to the discontinuities in the signal since time
points (from all data epochs) are shuffled at each iteration in the ICA
algorithms. From my perspective this is due to baseline removal: for
instance if you have an eye movement in the baseline, you will subtract
a different baseline from each data channel (since the amplitude ot the
eye movement will be different in each channel). This introduces
non-linearity in the data for this eye movement and ICA might have a
hard time dealing with it (possibly dedicating a component to account
for this specific eye movement). The same remark might be true for other
types of artifacts that affect the baseline average potential. This is
just a guess though. Also, the difference between ICA applied to
continuous data and ICA applied to concatenated data epochs (when the
baseline is 'clean') does not seem so dramatic and we are still using
the later one in many occasions (for instance for consistency when we
started this way for other subjects).
Note: do not use the SOBI ICA algorithm on concatenated data epochs.
Since SOBI (unlike other ICA algorithms) uses time correlation, it will
be affected by discontinuities in the data.
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