[Eeglablist] Multiple Source Eye Correction using dipfit?

[Tim Curran]

Hi Max,
Hopefully others with greater expertise will weigh in further.

In response to another question:
On May 11, 2017, at 11:25 AM, RICHARDS, JOHN <RICHARDS at mailbox.sc.edu<mailto:RICHARDS at mailbox.sc.edu>> wrote:
  “Presumably” the ICA correction separates the spatio-temporal activity generated by the eye dipoles from the spatio-temporal activity generated by dipoles in frontal brain areas, leaving the frontal brain dipole generated EEG activity.  I use a step with a realistic source model that includes the eyes and source analysis done on the ICA loading weights, and have a further requirement that the “eye” ICA components have dipoles located in or near the eyeballs.  I sometimes find components that appear to be EM components (e.g., distribution on the scalp with pos/neg bilateral loading weights, and similar activation patterns to EOG) but do not have eye dipoles.  These components are included in the regenerated ERP data.

I think this should be doable with dipfit.

Tim


On Jul 18, 2017, at 2:26 PM, Max Cantor <Max.Cantor at Colorado.EDU<mailto:Max.Cantor at Colorado.EDU>> wrote:

Accidentally sent before I was finished! I was also going to mention that the reason I want to use this sort of method is that using ICA alone, barring some other issue, is proving to be insufficient for saccade correction. I'm currently manually removing ICs corresponding to blinks and saccades, but I think that my correction method is either not removing the saccade effect well enough, or removing too much of the neural signal in addition to the saccade. I've also tried a variance-ratio criteria (see citation), which seems to pick out the same ICs as saccade-related as I do manually. This suggests to me that without some sort of spatial filter, I may not be able to remove the effect of the saccade without also removing the cognitive processes I'm interested in. I'm hoping that a dipole-based (or potentially some other) spatial filter can give me better ICs, which can hopefully allow me to remove the saccadic activity without also removing the neural signature.

Thanks,
Max

Plöchl, M., Ossandón, J. P., & König, P. (2012). Combining EEG and eye tracking: identification, characterization, and correction of eye movement artifacts in electroencephalographic data. Frontiers in human neuroscience, 6.

On Tue, Jul 18, 2017 at 2:18 PM, Max Cantor <Max.Cantor at colorado.edu<mailto:Max.Cantor at colorado.edu>> wrote:
Hi,

There is a method for multiple source eye correction (MSEC) using BESA (see citation) which I am interested in using for an EEG + Eye Movement coregistration study. However, is there a way to implement this method without BESA, such as using EEGLAB's dipfit function?



Berg, P., & Scherg, M. (1994). A multiple source approach to the correction of eye artifacts. Electroencephalography and clinical neurophysiology, 90(3), 229-241.


--
Max Cantor
Graduate Student
Cognitive Neuroscience of Language Lab
University of Colorado Boulder



--
Max Cantor
Graduate Student
Cognitive Neuroscience of Language Lab
University of Colorado Boulder
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