[Eeglablist] Continuous data - baseline correction

[Liz Chrastil]

Hello List

I'm new to EEG, and have a challenging situation when trying to do baseline
correction.

My study is looking at a fairly continuous task.  It's a navigation study,
and participants are spending ~8 min exploring a new virtual environment.
This exploration is broken up into choice points at intersections (they are
not moving, and they press a button to indicate which way to turn or to go
straight), and then a video showing the turn (or forward movement if they
go straight).  However, we don't have a section that has no task at all,
because we found that was too distracting to participants when they're
trying to learn something.

We have two groups of participants (there is an additional experimental
manipulation), and so are primarily going to be doing group analysis, but
we might also want to do a few analyses on within-subjects differences.
For example, we might contrast theta during the video vs decision point
epochs.  Times for videos range from 1500ms to 5000ms, decision points
could vary quite a bit (depending on how long the person thinks about it),
but average around 2000ms.

My question is, if we don't do any baseline correction for individual
epochs (and just do some general filtering), is this going to lead to a lot
of trouble?  Again, we're not really sure what we would baseline correct to
in this situation.  We could try correcting the videos to the decision
points, but that's basically like doing some other task and could lead to
worse errors.  Or is this a tragic design flaw?

Thanks for your help!
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