Within-subject coherence statististics for virtual sources

[Jan Mathijs Schoffelen]

Dear Lorina,



Even though my name is not Robert, I hope that is OK. I do not really
understand why you use freqstatistics_test function the way you do, but this
is the way I get it going in your case (so not using the function you sent
along: and I think what went wrong is how you configured your input-data):



Cfg.method = 'montecarlo';

Cfg.statistic = 'diff';

Cfg.parameter = 'powerspctrm'; %these contain coherences in reality, right?

Cfg.numrandomization = something;

Cfg.design = dependent on your input data;

Cfg.ivar = 1; %put condition in the first row of your desing-matrix

Cfg.uvar = 2; %put the subject-index on the second row



And now comes the trick, and I guess that's why you tried it the way you
did, at least so that you would not run into problems with
neighbourselection anymore.



For j = 1:length(dataBlabla.label)

  Cfg.neighbours{j}.label = dataBlabla.label{j};

  Cfg.neighbours{j}.neighblabel = {};

End



You have virtual channel data, so the neighbourhood-structure is irrelevant
for clustering (you don't want to cluster in space, but only in time and
frequency perhaps)



At least it should run through if you call:



Stat = freqstatistics(cfg, dataS1C1, dataS1C2, dataS2C1 etc)



Yours,



Jan-Mathijs











  _____

From: FieldTrip discussion list [mailto:FIELDTRIP at NIC.SURFNET.NL] On Behalf
Of Lorina Naci
Sent: Friday, November 10, 2006 6:41 PM
To: FIELDTRIP at NIC.SURFNET.NL
Subject: Re: [FIELDTRIP] Within-subject coherence statististics for virtual
sources



Hi Robert,

Thank you very much for your help, I was wondering whether I could trouble
you with a couple more questions. I converted my besa data to fieldtrip
format and this seemed to work fine. I got no error messages and the data
structures look like they contain all my data in them (I am attaching an
example mat file with the output structures from a few subjects). However, I
am still having problems with running freqstatistics. The cfg options are
defined OK but the matlab script crushes when it comes to calling
statistics_wrapper. The error message I get is as follows:

"Could not determine type of input data" which leads me to believe there is
a problem with the converted data.


I am also attaching my script for freqstatistics in case you need to see
this file.

Very many thanks for your help,

Lorina




Robert Oostenveld <r.oostenveld at FCDONDERS.RU.NL> wrote:

Hi Lorina

On 8 Nov 2006, at 20:00, Lorina Naci wrote:
> I tried to run the script as you suggested but it did not work. The
> error message I get is to do with
> [stat] = statistics_wrapper(cfg, varargin{:}). It just gives me an
> error message pointing to this line,saying: error using
> fieldtrip-20061003/private/statistics_wrapper, could not determine
> the type of input data.

Then it means that the data structure that you have obtained from
besa2fieldtrip is not recognized. It is also not clear to me how your
data looks like (i.e. as a Matlab structure). It is virtual channel
data, time-frequency analyzed, and then single trial coherences
computed?

Could you show the output that you get on screen after

dataA = besa2fieldtrip('filenameA.tfc') % i.e. without semicolon,
to show the output on screen
dataB = besa2fieldtrip('filenameB.tfc') % i.e. without semicolon,
to show the output on screen

> Also, the function 'cfg.numrandomization' requires a number, but I
> am not sure what the choice of the number depends on? I've inputed
> 500 as in the documentation example.

That is the number of resamplings that is used to construct the
reference distribution, 500 should be fine.

> Finally, at risk making my ignorance of how Fieldtrip works
> entirely transparent, I am not quite sure how the function you send
> me 'statfun_diff.m' links with the 'freqstatistics.m,' and whether
> I do need to use it?

You just have to put it on your Matlab path somewhere, and you specify
cfg.statistic ='diff'
in freqstatistics. In general by specifying cfg.statistic='xxx', the
function statfun_xxx will be called. Please look in the function
statfun_diff.m to see how the statistic for each sample (=time-
frequency-channel point) is computed.

best regards,
Robert



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