[FieldTrip] dimord single-trial source data

[Stephen Whitmarsh]

Hi again again Jan-Mathijs,

Ah yes, that does seem like the most elegant and memory-efficient approach!
I will need to figure out how to apply spatial filters to Fourier (and redo
my sensor level spectral analysis to Fourier).

Shout-out to the list: anyone have an example of applying spatial filters
to Fourier that I could use?

Thanks again again,
Stephen

On 16 November 2017 at 14:38, Schoffelen, J.M. (Jan Mathijs) <
jan.schoffelen at donders.ru.nl> wrote:

> Hi again Stephen,
>
> I forgot to mention a third approach: you can compute your spatial filter
> with cfg.method = ‘lcmv’ and cfg.lcmv.keepfilter = ‘yes’, and subsequently
> compute the source level spectra by applying these spatial filters to the
> sensor level fourier spectra.
>
> Best wishes,
> Jan-Mathijs
>
>
>
>
> > 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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>
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