[FieldTrip] ft_sourcestatistics and sourcegrandaverage time series

[jan-mathijs schoffelen]

Hi Kaelasha,

Sorry for being unclear. You can do something like:

stat = ft_sourcestatistics(cfg, data1, data2, data3, data4, ....), or stat = ft_sourcestatistics(cfg, data{:}); where data is a cell-array of structures (1 cell for each participant/condition).

Best,
Jan-Mathijs




On Jan 15, 2014, at 9:14 AM, Kaelasha Tyler wrote:

> Hi Jan-Mathijs,
> 
> Thanks for this response.
> I still have a question though.
> You mentioned that it is not necessary to use ft_sourcegrandaverage to perform statistical analysis with source space ERFs across multiple participants. However, what you appeared to suggest in your email, does appear to still use a grand average, e.g. you wrote:
> 
> >you can do something like this
> 
> >cfg = your cfg to ft_sourcestatistics
> >stat = ft_sourcestatistics(cfg, grandavg{:});
> 
> Having played around with it a bit more, I am still unclear how to use multiple inputs (e.g., multiple subjects source data) when using ft_sourcestatistics. I had thought that ft_sourcegrandavarge was a necessity. 
> Can you make this a bit clearer?
> 
> Also, I did go back and use cfg.fixedori='yes' when calling my first ft_srouceanalysis and moved also my source.avg.mom data into source.avg.pow as you suggested, but this still leaves me with the question above- how to use multiple subjects source data in ft_sourcestatistics?
> 
> Once again, any help from anyone would be much appreciated!
> 
> Kaelasha
> 
> From: fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl] on behalf of jan-mathijs schoffelen [jan.schoffelen at donders.ru.nl]
> Sent: Tuesday, 14 January 2014 5:52 PM
> To: FieldTrip discussion list
> Subject: Re: [FieldTrip] ft_sourcestatistics and sourcegrandaverage time series
> 
> Hi Kaelasha,
> 
> You actually don't need to use ft_sourcegrandaverage if your goal is to do statistics. Ft_sourcestatistics in principle knows how to deal with multiple inputs.
> Thus,
> rather than doing
> 
> cfg = [];
> cfg.keepindividual = 'yes';
> grandavg = ft_sourcegrandaverage(cfg, subjectdata{:});
> 
> you can do something like this
> 
> cfg = your cfg to ft_sourcestatistics
> stat = ft_sourcestatistics(cfg, grandavg{:});
> 
> Now, the question boils down to 'how to fool ft_sourcestatistics to swallow my data?'.
> 
> The following should more or less work (but requires some manual labour):
> 
> The time courses at the voxel level are present in source.avg.mom. These are most likely 3xN, 3 dipole orientations times N time points. In order to reduce this, one can project the orientation along the first pca-axis. This can be achieved by a call to ft_sourcedescriptives with cfg.projectmom='yes', or by calling ft_sourceanalysis in the first place with cfg.fixedori = 'yes'. 
> Then, you could do something like:
> 
> pow = zeros(size(source.pos,1),length(source.time);
> pow(source.inside,:) = cat(1,source.avg.mom{source.inside});
> source.avg.pow = pow;
> 
> Just to be sure, add a time-axis to the source structure, i.e. source.time = tlck.time (tlck being the data structure used to create the lcmv-output).
> 
> I think this should bring you close to doing statistics.
> 
> Best,
> Jan-Mathijs
> 
> 
> 
> On Jan 14, 2014, at 7:19 AM, Kaelasha Tyler wrote:
> 
>> Hi all,
>> 
>> Reading through the discussion list, I see others have also had some issues with creating grand averaged source space time series (ERFs) and subsequent statistical analysis,  but I can't see any solutions....
>> 
>> Questions:
>> How can I create time series (ERFs) for grand averaged source space data?
>> And, how can I do cluster analysis on these (yet to be created) grand averaged source  space ERFs?
>> 
>> 
>> I have used ft_SOURCEANALYSIS with method 'lcmv' for individual participants to generate source space time series, in data.avg.mom.
>> 
>> Subsequently I used ft_sourcegrandaverage to combine source space data across subjects. 
>> 
>> However my grand averaged source data.avg only contains 'pow' and no 'mom'. Eg, no time series for the grand averaged source space data. 
>> 
>> As such, I can not do cluster analysis on grand averaged ERFs in source space.
>> 
>> It appears that ft_sourcestatistics only works with parameters that have not more than one value per grid point (e.g. pow, nai etc) and is unable to work with ERF time series? Is this true?
>> 
>> Can any one help with this?
>> 
>> Much obliged.
>> Kaelasha
>> 
>> 
>> 
>> 
>> 
>> _______________________________________________
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> 
> 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
> 
> http://www.hettaligebrein.nl
> 
> _______________________________________________
> 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

http://www.hettaligebrein.nl

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