[Eeglablist] Default Overlap in Spectopo / std_spec and PSD vs. FFT

Erickson ericksonb.eng at gmail.com
Mon Apr 13 17:07:52 PDT 2015

Hi all,
When using Spectopo, I was confused about the overlap used by default. I
did some digging and developed a summary that I think may be useful to
others, as well as some questions for the listserv.

There are two functions one could use to extract power spectra information.

One is Spectopo, which by default calculates the Power Spectral Density
(PSD). When no "overlap" value is given, the default is [0] in timepoints.
This could be confusing, since the default of the underlying function
pwelch() is 50% overlap. However, this is only when pwelch is called
directly. Overlap must be manually specified when called from spectopo().
Spectopo() is the function called when using plot->channel spectra and maps.

The other is std_spec(). When called with the "PSD" option, std_spec()
calls spectopo with no overlap value. (it will always default to [0] and
there is no way to specify an overlap.) I am not aware of where this
std_spec() function is called in the GUI. Can anyone comment on this? Is it
only available from the "Study" function?

std_spec() can also be called in FFT mode, in which case it defaults - on
continuous data only - to 1s epochs with .5s overlap. These variables can
be set by two options specifying the epoch length and epoch "recurrence".

This general information was previously covered (
http://sccn.ucsd.edu/pipermail/eeglablist/2013/006174.html) but the
discussion was difficult to follow. Correction of any errors I've made is

Technical concerns aside, more opaque is the difference between these two
options - Power Spectral Density vs. FFT.

In a previous topic I posted, PSD and FFT have been described as both
essentially equivalent and different by various experts, and the discussion
was left unresolved: see

I am confused, when reporting mean power values across time periods,
whether I should be using the FFT or PSD options and what the essential
differences between these frequency domain transformation methods are. I
think this is a quite essential topic as band power within a time window is
a core method for reporting condition differences in EEG. Would anyone
comment on the contrast between PSD and FFT and in which situations either
should be reported / analyzed?

Brian Erickson

Creativity Research Laboratory
Applied Brain and Cognitive Sciences Program
Drexel University, Department of Psychology
College of Arts and Sciences
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