[Eeglablist] Warning: change STUDY design

Jet Zoon jetzoon at gmail.com
Tue Jul 17 07:12:27 PDT 2018


 Dear eeglablist,

In using eeglab to perform analyses for a study with a rather complex
design I ran into the following warning: Warning: ***** change STUDY design
as it combines datasets with different ICA decompositions.

A short description of the design:
testday 1: participants receive a high-energy savoury meal
testday 2: participants receive a high-energy sweet meal
Before and after meal intake we measured neural responses (using EEG) to
visual and olfactory stimuli of the following categories:
High-energy savoury food
High-energy sweet food
Low-energy savoury food
Low-energy sweet food
Non-food
Baseline (no product/no odour)
Each stimulus category was presented 18 times before and 18 times after
meal intake.

To keep the statistical power as high as possible, with the limited amount
of items we presented, I would like to combine stimulus categories between
the two test sessions. I think that it is best to end up with the stimulus
categories: fully congruent (between meal and stimulus: e.g. High-energy
sweet meal - high-energy sweet odour), taste congruent, energy congruent,
not congruent, non-food and baseline.

I now included data from two sessions on two separate days in the study
dataset. ICA has been performed for the two datasets separately. I
understand that that is why I get to see the warning I mentioned. However,
in contrast to what is mentioned in an earlier conversation on this topic (
https://sccn.ucsd.edu/pipermail/eeglablist/2011/003669.html), I can run the
analyses and get my results.

Should this be possible? Can I just interpret the results as usual or does
combining items from two datasets provide invalid results? If so, is there
another option to combine the items from the two datasets? In the message I
referred to, it is suggested to only merge sessions with the same ICA
decomposition. However, since the two datasets have been aqcuired on two
separate days I understand that ICA analyses should be performed on the
datasets separately.

I really appreciate your help in resolving this problem.

Kind regards,
Jet Zoon
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