[Eeglablist] Questions related to event-related (phase) coherence

Jung Hwa Han junghwahan at gmail.com
Thu Dec 10 00:43:16 PST 2015

Dear EEGLAB list,

I am a naive Matlab user (not familiar with math either) who is trying to
learn to use EEGLAB for analyses involving event-related band power change
and (cross-channel) phase coherence. I'm working with Neuroscan .cnt files.
Several questions regarding phase coherence:

1. While I appreciate that it's clearly explained in Delorme and Makeig
(2004) that ERCOH is a measure of the degree of synchronization between two
signals, I would like to know how it differs from other phase
synchronization measures, e.g. PLV. I couldn't find any review that
includes ERCOH in the comparison of synchronization measures. Does anyone
have a reading suggestion?

2. When calculating ERCOH values for every time-frequency points to get the
time-frequency plot from a single subject's epoched data, does EEGLAB
calculate ERCOHs from single epochs then average, or calculate ERCOHs from
the averaged epoch data? My intuition is that phase information will be
somewhat lost (or blurred) when epochs are averaged, so EEGLAB should
calculate ERCOHs from individual epochs first and then average across
epochs. Does it?

3. If PLV and ERCOH are comparable measures of phase synchronization, they
must use the same information from the signals (e.g. phase information) to
calculate the values. Then, if I decide to use PLV instead of ERCOH, I
believe it should be fairly easy to modify the code for ERCOH (substitute
ERCOH equation with PLV equation) to get a time-frequency plot showing PLV
values, and a matrix of PLV values. Is anyone familiar with such procedure,
and willing to provide advice on this?

4. In time-frequency decomposition, how long is the default time steps of
the overlapping time window in EEGLAB? Is there a way to modify the time
steps? For example, I would like to use 3-cycle Morlet wavelet for the
decomposition, and I would like to have this window slide in time steps of

5. For eyeblink reduction method, I understand that it's the most common
practice to use ICA. I also understand that there are particular pluses and
minuses of various artifact reduction methods. From my lit review, I
couldn't find any sort of preference for a method over others in studies
that looked at coherence, and couldn't find any review on this matter
either. Does the fact that ICA is a powerful tool justify using ICA for
artifact reduction in preprocessing data for coherence analysis? Is there
any issue with this method with particular regards to coherence analysis?

6. When missing reference channels, would people prefer using a single
reference (i.e. Cz) or common average reference, in prepping data for later
coherence analysis?

Thanks in advance.



Yonsei University College of Medicine, Korea
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