[FieldTrip] [FIELDTRIP] Independent channels stats question
Sangita Dandekar
sangita.dandekar at gmail.com
Tue Oct 25 19:55:39 CEST 2011
Hi Fieldtrippers,
I have questions similar to the ones asked a while back in the discussion
archive. (See discussion pasted below my email if you're interested)
We have ~200 intracranial EEG electrodes, which we assume are independent,
and the question is how to apply
cluster statistics to time frequency data while accounting for the multiple
comparisons problem.
In the archived discussion below, it was suggested that cluster statistics
be applied to each channel separately, and then, to account for MCP, apply
Bonferroni correction on the resulting p-values. However, as was pointed
out in the discussion below, with ~200 electrodes Bonferroni
correction is overly conservative. Another possibility suggested in the
archived discussion was FDR correction on the results of cluster
statistics, but it isn't clear to me
how this would be done. If anyone can explain how FDR can be applied to the
results of cluster statistics, please let me know.
I think a third possible solution to the problem is to get a 'global' null
distribution as follows:
Repeatedly:
1. Randomly partition data
2. Find time frequency clusters and the associated sum of t-statistics for
each TFR cluster (do this WITHOUT clustering over electrodes/space, thereby
treating each channel independently)
3. Record maximum t-statistic sum in a 'global' null distribution on each
iteration. (Search over all electrodes for this maximum)
Then one could compare the clusters as observed in the actual data (as
determined independently at each electrode) to the global null distribution
to get the false alarm rate
associated with any cluster. I think the above should account for the MCP.
Is there anyway to implement the above procedure in Fieldtrip without
modifying the underlying functions? I know how to do a for loop around
freqstatistics to treat each channel separately and then get the null
distribution of tstat maxima and cluster statistics for each channel
separately, but I am not sure
if it is possible to treat each channel independently as I have outlined
above and also get a global null distribution over all channels (without
making some
changes to the underlying FT functions, that is).
Thanks in advance for any help!
Sangi
On Tue, Jul 6, 2010 at 12:47 PM, Matthew Davidson <sunyata at gmail.com> wrote:
> Jan-Mathis, thanks for the response.
>
> Unfortunately, we tend to have a lot of channels (~120-200), and once
> we start using microelectrodes in the patients, it'll only get worse.
>
> If we were to divide our alpha by 120-200, wouldn't we have to run
> 120-200 times as many permutations in order to get p-values low enough
> to survive Bonferroni correction? That's a large jump; we might have
> to run 100,000 permutations!
>
> What do you think about something like FDR correction instead?
>
> Matthew
>
> On Tue, Jul 6, 2010 at 7:21 AM, jan-mathijs schoffelen
> <jan.schoffelen at donders.ru.nl> wrote:
> > Dear Matthew,
> >
> > Your sensitivity problem is a known issue when using cluster-based test
> > statistics, in which it is difficult to get small clusters significant in
> > the presence of large clusters. This could also occur within a single
> > channel (for example with a time-frequency decomposition, in which the
> > summed spectro-temporal extent of an alpha-band effect could be much
> bigger
> > than a gamma-band effect).
> > In your case I think it would be statistically valid to do the
> cluster-based
> > permutation test on each channel separately (which will involve a for
> loop
> > around ft_freqstatistics, because it is not implemented in the fieldtrip
> > code) and doing a post-hoc Bonferroni correction on the resulting
> p-values.
> > If the number of channels is not too big, this might work.
> >
> > Good luck,
> >
> > Jan-Mathijs
> >
> >
> > On Jul 6, 2010, at 3:26 AM, Matthew Davidson wrote:
> >
> >> Hi, this is Matthew Davidson. I recently took the Fieldtrip EEG/MEG
> >> Toolkit (Hi Robert and Jan-Mathis!), and have been diving into using
> >> Fieldtrip more directly.
> >>
> >> My question pertains to cluster-based correction when channels are
> >> independent. My data is primarily intracranial EEG, and due to the
> >> 1/f^2 power drop-off, electrodes directly on the brain reflect local
> >> activity much more strongly than sensors further away. As a result, we
> >> treat them as independent. Now, I can force the Fieldtrip clustering
> >> algorithm to not cluster across channels by setting:
> >>
> >> cfg.neighbours = [];
> >> cfg.minnbchan = 0;
> >>
> >> but it still computes the maximum cluster size for a particular
> >> permutation based on *all* the data. This seems... less sensitive
> >> somehow, as if large clusters in one channel negatively impact the
> >> significance of clusters in another channel.
> >>
> >> Is there a better way to do this and still solve the MCP? E.g.,
> >> compute the maxsum on each channel separately, and then use something
> >> like FDR or Bonferroni correction on the maxsums across channels?
> >>
> >> Thanks for any advice you may have, and thanks for producing fieldtrip!
> >> Matthew
> >>
> >> ----------------------------------
> >> The aim of this list is to facilitate the discussion between users of
> the
> >> FieldTrip toolbox, to share experiences and to discuss new ideas for
> MEG
> >> and EEG analysis. See also
> >> http://listserv.surfnet.nl/archives/fieldtrip.html and
> >> http://www.ru.nl/neuroimaging/fieldtrip.
> >>
> >
> > Dr. J.M. (Jan-Mathijs) Schoffelen
> > Donders Institute for Brain, Cognition and Behaviour,
> > Centre for Cognitive Neuroimaging,
> > Radboud University Nijmegen, The Netherlands
> > J.Schoffelen at donders.ru.nl
> > Telephone: 0031-24-3668063
> >
> > ----------------------------------
> > The aim of this list is to facilitate the discussion between users of the
> > FieldTrip toolbox, to share experiences and to discuss new ideas for MEG
> > and EEG analysis. See also
> > http://listserv.surfnet.nl/archives/fieldtrip.html and
> > http://www.ru.nl/neuroimaging/fieldtrip.
> >
>
> ----------------------------------
> The aim of this list is to facilitate the discussion between users of the
> FieldTrip toolbox, to share experiences and to discuss new ideas for MEG
> and EEG analysis. See also
> http://listserv.surfnet.nl/archives/fieldtrip.html and
> http://www.ru.nl/neuroimaging/fieldtrip.
>
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