[FieldTrip] Running sensor space stats then source?

[Johanna Zumer]

Hi Peter,

I think your question was aimed at asking: is it, by running the same stats
on transformed data, double-dipping to use the same time window, for
example?  I don't think so in this case of sensor versus source because, as
Jan-Mathijs already mentioned, it's not just a transform of each sensor to
a given source location, but rather a linear mixture, and this linear
mixture may pull out different effects, even when using cluster stats at
the sensor level.

I also don't think that it is double dipping if you first find the optimal
time window in sensor data, and then simply want to ask: where is the most
likely location of the underlying neural source?   Then you are asking a
spatial/where question, not a presence/if question.   Although, see
previous paragraph as to why you may find a different set of significant
findings in source versus sensor space.

Cheers,
Johanna





2013/1/18 jan-mathijs schoffelen <jan.schoffelen at donders.ru.nl>

> Hi Peter,
>
> I don't have a definite answer to your question, but note that analysing
> the data at the level of the sources is something a bit more involved than
> just taking the log-transform...
>
> Here are some pseudo-random thoughts:
>
> Essentially, sensor level signals present themselves as a linear mixture
> of the underlying sources of interest, and the source modelling attempts to
> unmix the sensor signals using biophysical (and additional) constraints.
> In general, source level analysis will allow for a 'cleaner'
> interpretation of the possible location of the sources, where one should
> always account for the fact that the spatial resolution of EEG/MEG source
> reconstruction is not typically very high. In addition, the more relevant
> reason to try to unmix the sensor-level data, is to get a cleaner account
> of the temporal structure in and between the underlying neural generators,
> allowing for less problematic interpretation of univariate and
> bi/multivariate (connectivity) quantities estimated from the data. As a
> result of the source reconstruction, it could be that results are uncovered
> which are not easily visible from the sensor data alone.
>
> It is perfectly valid to constrain yourself to sensor-level analysis, if
> this allows you to make your scientific point. Also, once you manage to
> reject your null-hypothesis (allowing you to speculate about the
> alternative hypothesis in your discussion section of your paper), there is
> no need to go to the source level.
>
> I guess that to some extent it is also a matter of taste, familiarity with
> the methods, and opportunity which drives researchers to choose for one or
> the other approach.
>
> These are just my thoughts and ideas, and it could be that other people on
> this forum have more sensible things to say about it.
>
> Best,
>
> Jan-Mathijs
>
>
>
>
>
> On Jan 15, 2013, at 6:00 AM, Peter Goodin wrote:
>
> Hi fieldtrip list,
>
> I'm about to start running some stats on my data but have run into a bit
> of a problem when it comes to the correct method.
>
> I'm interested in looking at ER "p3" activity and so will first be using
> the cluster based tests in fieldtrip to examine for significant differences
> between my two groups, limiting the TOI to around 300 - 500ms.
>
> The problem comes when I want to to do source localisation, as I'll be
> using the same time window, just in a different (more assumption filled)
> space.  In my head it's like running a t-test on "raw" data then doing it
> again transformed (eg, log transform) numbers, removing any assumption of
> independence and by conventional wisdom shouldn't be done.
>
> Most of the articles I've read seem to go for one or the other but those
> that use both don't make any discussion regarding it. Can anyone point me
> in the right methodology direction?
>
> Thanks,
>
> Peter.
>
> __________________________
> Peter Goodin,
> BSc (Hons), Ph.D Candidate.
>
> Brain and Psychological Sciences Research Centre (BPsych)
> Swinburne University,
> Hawthorn, Vic, 3122
>
> Monash Alfred Psychiatry Research Centre (MAPrc)
> Level 1, Old Baker Building
> Commercial Road
> Melbourne, Vic, 3004
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>    Jan-Mathijs Schoffelen, MD PhD
>
> Donders Institute for Brain, Cognition and Behaviour,
> Centre for Cognitive Neuroimaging,
> Radboud University Nijmegen, The Netherlands
>
> Max Planck Institute for Psycholinguistics,
> Nijmegen, The Netherlands
>
> J.Schoffelen at donders.ru.nl
> Telephone: +31-24-3614793
>
>
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