averaging in sensor space

[Sanja Kovacevic]

On Fri, 12 Aug 2005 12:13:44 +0200
  Ole Jensen <ole.jensen at FCDONDERS.RU.NL> wrote:
> Regarding the discussion on planar gradients and
>averaging over subjects:
>
> As Tom suggests it is always best to average over
>subjects in source space. However, sometimes we do not
>have high enough signal-to-noise in order to reliably
>identify the sources while we still observe consistent
>effects at the sensor level. I think it is an important
>discussion since it pertains to how we approach MEG data
>in general. Therefore I would like to provide an argument
>for why I believe it is sensible to average over subjects
>in sensor space:
>
> Say that a dataset has been analyzed in the frequency
>domain and we have representations of power for each
>sensor. I find it convenient to apply the combined planar
>gradient for power representations since this will tend
>to give the strongest power in sensors above the source.
>An axial gradient representation will result in two
>regions of strong power at each side of the source (i.e.
>where the fields exit and enter). We have had quite good
>luck averaging combined planar gradient power
>representations over subjects at the sensors level both
>with and without realignment. The FieldTrip has
>statistical methods implemented for dealing with the
>multiple comparison problem (multiple sensors). Also, for
>instance the group in Tuebingen has several publications
>were power (albeit using axial gradients) where they
>average over subjects at the sensor level. The approach
>is quite similar to that applied by the ERD/ERS community
>on EEG data. Note that differences in head size, position
>etc might diminish a given effect - however, I do not
>believe that averaging over subjects in sensor space will
>result in false positives.
>
> With respect to event related fields one should be very
>careful averaging the axial gradient over subjects at the
>sensor level. The orientation of sources from subject to
>subject might be different thus partially canceling a
>given effect. One solution is to calculate the RMS of the
>two orientations of the planar gradient and then average
>over subjects. This has for instance been done
>convincingly by the BRU/LTL Helsinki group in N400m
>studies. We have also good experiences with that approach
>at the Donders. The main disadvantage of averaging
>combined planar gradients of ERFs is that we loose
>information about source orientation.
>
> I would advice against doing source modeling on MEG data
>which has been averaged over subjects (this is often done
>for EEG data). Here it is appropriate to average either a
>current estimate of "beamformed" power estimate in source
>space after realigning the source representations to a
>standard brain.
>
> We are often using the following approach
>
> 1) Calculate time-frequency representations (TFRs) of
>power for planar gradients
> 2) Combined the planar gradient for each orientation
> 3) Average over subjects in sensors space
> 4) Use randomization statistics to identify clusters of
>difference
> 5) Use the beamformer to estimate power in source space
>for time and freq tiles identified in 4) in individual
>subjects
> 6) Morph the results of beamformed power to a standard
>brain
> 7) Average morphed power representations in source space
>
>
> Bests,
>
> Ole
>
>
>
>
>
>
>> Oh, as long as I'm here:
>>
>> Personally I wouldn't bother averaging across subjects,
>>because even
>> "aligned", averaging subjects together in sensor space
>>is nearly
>> meaningless.  (Though an interesting project, by analogy
>>to Talairach
>> or MNI space, is to "warp" the sensor space data into a
>>common space,
>> based on "anatomical" landmarks such as the peaks of the
>>AEF and/or
>> SEF.  I still wouldn't do that, though.)
>>
>
>
> --
> Ole Jensen
> Principal Investigator
>F.C. Donders Centre for Cognitive Neuroimaging
> P.O. Box 9101
> NL-6500 HB Nijmegen
> The Netherlands
>
> Office  : +31 24 36 10884
> MEG lab : +31 24 36 10988
>
>Fax     : +31 24 36 10989
>
> e-mail : ole.jensen at fcdonders.ru.nl
> URL    : http://oase.uci.ru.nl/~olejen

Sanja Kovacevic
Research Assistant
MIND Imaging Center
Albuquerque, New Mexico, USA
Phone: +1 (505) 272 3327
Fax: +1 (505) 272 4056