[Eeglablist] Random selection of trials

Philip Michael Zeman pzeman at alumni.uvic.ca
Thu Apr 1 11:36:04 PDT 2010

Hello Kris

This is an issue that I've encountered myself and I've had to come up with 
some logical reasoning.  I am also very interested in hearing what other 
people have to say on this topic so that I know what options exist.

My reasoning is as follows:

If there is any chance of learning or adaptation of the neural systems 
involved in the paradigm to the stimuli or the context of the stimuli, then 
I would chose to use only the first 150 trials of each of the conditions you 
are examining.  There is plenty of ERP research out there that shows that 
the second-half vs. the first have of an experiment has characteristically 
different waveforms. (See, face recognition/unknown face ERP literature, 
e.g., Tanaka - I think that participants begin to learn what could be 
considered the 'odd-ball' in this experiment).

Your concern about averaging a different number of trials for each 
*Yes, this is a concern.  My philosophy is to always compare apples to 
apples --- always try to do the same processing in condition 1 and in 
condition 2 if you are going to ask the question, "are these 2 conditions 
different?" using a statistical test.  If in condition 1 there are 150 
trials and in condition 2 there are 1000 trials (and you use them all) then 
when you average the data within each participant and then look for a 
difference in the distribution across participants you already know there is 
a possible difference simply due to what you did to the data.  Depending on 
the signal-to-noise characteristics (and what we consider to be noise, e.g., 
variability in behaviour, uncorrelated sensor noise, learning and 
adaptation), you might have a distribution of values in condition 2 that are 
tightly distributed around the mean for the condition compared to in 
condition 1 that has a distribution of scores that are spread by a large 
amount around the mean of the condition.

If you are not concerned about learning and adaptation in your experiment, 
(and I think this goes against standard research hypothesis testing rules) 
what I would suggest is doing your hypothesis test in multiple comparisons 
so that you can learn something about your data.  I would answer my 
hypothesis using (1) and then go further by investigating (2) and (3) to see 
what I get.
(1) compare condition 1, trials 1 to 150 vs. condition 2, trials 1 to 150
(2) compare condition 1, trials 1 to 150 vs. condition 2, trials N-150 to N 
(where N is the number of trials in the large set)
(3) compare condition 1, trials 1 to 150 vs. condition 2, random blocks of 
150 trails (and do this multiple times on different random blocks)

Keep me updated as to what you decided to do.



Philip Michael Zeman B.Eng, Ph.D.
Applied Brain and Vision Sciences Inc.
Brain Function Analysis for Novel Paradigms and Serious Games
Analysis of Pharmaceutical Effects on Brain Function
Latest Brain Research Result:
Email:   pzeman at alumni.uvic.ca
Phone: +1-250-589-4234
LinkedIn Profile: http://ca.linkedin.com/in/philipmichaelzeman

----- Original Message ----- 
From: "Kris Baetens" <Kris.Baetens at vub.ac.be>
To: <eeglablist at sccn.ucsd.edu>
Sent: Wednesday, March 31, 2010 8:04 AM
Subject: [Eeglablist] Random selection of trials

> Dear colleagues,
> We employ a paradigm which inherently leads to a different number of 
> trials in both our conditions (oddball-like). We have two conditions, one 
> with an average of about 150 trials, the other with about 1500 
> (artefact-free).
> - Does anybody have research to support my concern that comparing both 
> conditions with the total number of trials may lead to artificial effects 
> due to the different number of trials (and associated variance and 
> "cleanliness" of the gavg's)? (I have seen such things published before.)
> - Does anybody know of an easy way to make a random selection of a 
> predetermined number of trials out of the total number in EEGLAB or 
> MATLAB? (Which would allow for selecting an equal number of trials in both 
> conditions.) Obviously, we don't simply want to take the first or last 150 
> regular trials, since this would possibly lead to erronous conclusions.
> Thank you very much in advance,
> Kris Baetens
> Ph.D. fellow of the Research Foundation - Flanders (FWO)
> Dept. Experimental and Applied Psychology
> Faculty of Psychology and Educational Sciences
> Vrije Universiteit Brussel
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