Beamformer time course
marie at PSY.GLA.AC.UK
Tue May 16 18:21:24 CEST 2006
Thanks a lot for your response, your explanations seem clear to me.
I have also talked with Klaus Kessler about this. He has in the past
used DICS to generate the filter for a specific time/freq box, and
then applied this filter to the time locked data in order to compute
synchronization between regions etc.
I realise this would also not be possible smoothly, but does it make
sense to generate a filter using the cross spectral density matrix
for a given time/freq range (cf DICS) - and then applying this
filter to the covariance of the time averaged data?
On 12 May 2006, at 18:22, Robert Oostenveld wrote:
> Dear Marie,
> On 10 May 2006, at 16:31, Marie Smith wrote:
>> I have a question about the solution of a beam-former analysis and
>> would appreciate any suggestions. Having used the beam-former
>> technique to localize a region of interest for a specific time-
>> frequency range, is there some function that can be implemented to
>> compute the time course of activation for this roi?
> For that you would use a time-domain beamformer, i.e. the lcmv
> beamformer (cfg.method='lcmv' in sourceanalysis). That requires
> time-domain data as input, so you should use timelockanalysis to
> compute the covariance and the average. The covariance is used to
> construct the beamformer filter and the average is projected
> through the filter. If you want to project single-trial data
> through the filter, you should keep the trials in timelockanalysis
> and use the option cfg.singletrials='yes' in sourceanalysis (see
> its help).
> If you are interested in a specific frequency band, you can use a
> band-pass filter in timelockanalysis (the options for that are
> hidden in the documentation, but they are the same as in
> preprocessing, e.g. bpfilter='yes' and bpfreq=[low high]). It could
> also be that you want to use a filter based on a narrow frequency
> band and use it to beam the broad-band data. That is also possible,
> but not smoothly: you have to do timelockanalysis twice (broadband
> and narrowband) and replace the broadband covariance with the
> filtered narrowband covariance. I hope this short explanation is
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