[Eeglablist] Are the results more significant on the scalp or inside brain?

Makoto Miyakoshi mmiyakoshi at ucsd.edu
Wed May 14 11:53:06 PDT 2014


Dear Cyril,

I agree with you. That's why it's always recommended to show confidence
intervals or error variances whenever possible.

Makoto


2014-05-13 12:44 GMT-07:00 Dr Cyril Pernet <cyril.pernet at ed.ac.uk>:

>   Hi Makoto & Michal,
>
> I agree with Makoto about the ICA subspace which can be quite different -
> there is however another thing to consider
> You said ' Should the effect be stronger (in terms of more statistically
> significant electrodes (dipoles) and timeperiods) on scalp electrodes or in
> DIPFIT clusters?'
>
> the problem here is that statistically significant is an estimate under
> H0, so beside the hypothesis test, you cannot tell if the effect is
> stronger or weaker in one case or the other because a p value tells nothing
> about H1 -- to do that you need to look at the actual effect size (like
> what is the mean uV difference between conditions) and not base your
> judgment the (correted) p values. You could also test if the effects are
> different using a test for apparied measures  (eg. a paired t-test between
> (condition A - condition B) on one compoment vs (A -B) on one channel).
>
> Cyril
>
> --------------------------------
> Dear Michal,
>
>  That's a simple but deep question.
>  Theoretically the difference between condition can't be smaller in ICA
> recults since canceling happens in the mixing process and not the other way
> around (like the law of entropy?)
>
>  However, I believe a major problem in comparing channels with ICs is
> component selection. The question is how you guarantee that the ICs you
> choose is a right representative (projecting source) to the channel? What
> if some subject don't have such ICs? What if some subjects have multiple of
> such ICs (subspace)?
>
>  One way to investigate this problem is run pvaf analysis (you have
> pvaftopo under EEGLAB plugin manager)
>  I have an experience of computing the pvaf analysis across subjects per
> cluster (unpublished data), and the result showed very large standard
> deviations... it was like mean 30% and SD=30, range 5-80. This means a
> cluster can explain a channel activity (in my result, of course) only by
> 30%, and there are huge inter-subject variance.
>
>  This being said, I think it is still ok to stay optimistic and take the
> theoretical conclusion. You haven't observed horrendously contradicting
> results, have you?
>
>  Makoto
>
>
> 2014-05-12 14:02 GMT-07:00 Michal Vavrecka <vavrecka at fel.cvut.cz>:
> Hello,
>
> I do have few simple questions and I am curious about your intuitions and
> arguments:
>
> I am finishing the paper where I did group analysis of two cognitive
> states. I visualized both scalp maps and dipoles and their statistical
> tests. Both visualization are based on fieldtrip monte carlo permutation
> with cluster based statistics (correction for multiple comparison). I would
> like to interpret the difference between results on the scalp and inside
> the brain (DIPFIT). What are your intuitions:
>
> Should the effect be stronger (in terms of more statistically significant
> electrodes (dipoles) and timeperiods) on scalp electrodes or in DIPFIT
> clusters?
>
> How to interpret the stronger effect on the  scalp?
> Does the ICA and DIPFIT calculation somehow weaken the ERSP difference?
> My intuition is opposite as the source reconstruction has to clean the
> noise and strengthen the effect that should result in more statistically
> significant timeperiods in the spectrograms compared to scalp data?
> Is there any paper that compares these two approaches?
>
> Thanks for your answers.
>
> Michal
>
> --
> Dr Cyril Pernet,
> Academic Fellow
> Brain Research Imaging Center
> Neuroimaging Sciences
> University of Edinburgh
>
> Western General Hospital
> Division of Clinical Neurosciences
> Crewe Road
> Edinburgh
> EH4 2XU
> Scotland, UK
>
> cyril.pernet at ed.ac.uk
> tel: +44(0)1315373661
> http://www.sinapse.ac.uk/
> http://www.sbirc.ed.ac.uk/cyril
>
>
>
> --
> The University of Edinburgh is a charitable body, registered in
> Scotland, with registration number SC005336.
>
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-- 
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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