[FieldTrip] dimord single-trial source data

Schoffelen, J.M. (Jan Mathijs) jan.schoffelen at donders.ru.nl
Thu Nov 16 14:31:53 CET 2017

Hi Stephen,

I think that it is currently not possible to pass the output of ft_sourceanalysis to ft_freqanalysis directly, since ft_freqanalysis expects channel-level type data in the input.
The exact details of the computation depend a bit on the amount of RAM you have, and on what exactly you want to achieve. 

If it’s your intention to generate frequency spectra for many dipole locations (e.g. >1000 or so) I would consider the following:

- compute spatial filters (cfg.keepfilter = ‘yes’);
- use a for-loop across (chunks of) dipole locations to create ‘virtual channel data’, by premultiplying the sensor-level data.trial (loop across trials) with the location specific spatial filter.
- stuff all this into a data-structure that looks like a raw data structure;
- pass this to ft_freqanalysis

Alternatively, you could consider using a parcellation approach, if you think it makes sense to reduce the number of spatial locations a bit, although theoretically it should be possible to create a parcellation that consists of just a single dipole per parcel. In this context, you could look into the inner workings of ft_sourceparcellate, which returns a data structure that ft_freqanalysis can work with. Whether ft_sourceparcellate can swallow single trial source data, I am not sure.

Best wishes,


> On 16 Nov 2017, at 12:36, Stephen Whitmarsh <stephen.whitmarsh at gmail.com> wrote:
> Hi FieldTrippers,
> I was wondering is there is a recommend/most consistent way to represent trial x pos x time data from an LCMV beamformer, also considering the dimord. In other words:
> with:
> data.method = 'singletrial'
> should I use:
> data.trial{pos} = [rpt x time]
> data.dimord = '{pos}_rpt_time'
> or rather:
> data.trial = {pos x rpt x time}
> data.dimord = 'pos_rpt_time'
> or something else? The purpose is to then do a frequency analysis (with keeptrials = 'yes').
> Best,
> Stephen 
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