Beamforming across trials not time

Marie Smith marie at PSY.GLA.AC.UK
Mon Feb 26 18:49:23 CET 2007


In order to achieve a better temporal resolution with a beamformer
analysis it has been suggested to use single trial data in place of
single time point data. Eg. In an experiment with 1000trials, 400time
points - rather than compute the covariance across the 400 time
points (averaged over trials), compute it over 1000 points (for a
very short fixed time interval e.g. 10ms). I have tried to implement
this and would like some advice on whether or not the steps i have
taken make sense in terms of fieldtrip functions and in general. Any
advice would be welcome.



Effectively what I am doing is:

Step 1) Choose a time point of interest
Step 2) Smooth the single trial data with a 30point moving average to
increase SNR
Step 3) Generate a fake "single trial" which is the concatenation of
each of these points across all trials e.g. the matrix has dims
(nchans, (ntrials*ntimes));
Step 4) Perform time-lock analysis on this "single trial" to compute
the covariance  - avg1
Step 5) Perform time-lock analysis on the actual data over the same
short time range with keeptrials = 'yes'  -avg2
Step 6) Perform lcmv sourceanalysis on avg1 (output of step 4)
Step 7) Apply this filter to avg2 (output of step 5 and
sourceanalysis) to estimate the single trial time courses at each
grid location, across the short time interval.

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