[FieldTrip] Grandaverage after regressing out headposition confounds
stephen.whitmarsh at gmail.com
Fri Jul 20 13:13:47 CEST 2012
As Jorn said calculating the planar on ERF data creates some
additional 'issues', mainly because the signal, as well as the noise,
will always be positive (because of the pythagoras' square operation),
and the noise will therefore be additive - i.e. it won't 'average
out'. However, with similar amount of trials and other such caretaking
comparisons between conditions it is in principle possible.
As I see it there are two main reasons for going to planar:
1) more interpretable locations (of maximum amplitude difference): It
relieves one from the neccecity to visually process the dipole pattern
(positive and negative poles) as showing two sides of a single dipole
with the source probably in between.
2) since you lose the orientation of the dipole in the planar
transformation - an ideal anterior-posterior will give the same
pattern as a left-right dipole when the maximum slope between the two
poles lie on the same location - this can help you to average over
subjects that might have different orientations but are located above
similar regions. In addition the dipole pattern is in effect spatially
smoothed (depending on how many neighbours you use), which might help
your average as well.
On 20 July 2012 12:28, Porada Danja <dporada at uos.de> wrote:
> I just found out that I only have to use the field avg as input for ft_grandaverage...
> But I'm still wondering whether it is necessary to calculate the planar gradient before computing the grand average.
> Am 20.07.2012 um 07:48 schrieb Porada Danja:
>> I would like to compute a grand average of the individual ERFs after I already used ft_regressconfounds (in order to deal with changes in head position during the experiment).
>> Here is the problem:
>> For regressing out head position confounds I have to keep the individual trials during the timelockanalysis. But for computing the grand average afterwards I need averages and not individual trials. Which is the best way to obtain the average?
>> And I have another question: Do I have to calculate the planar gradient before computing the grand average?
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