[Mne_analysis] Single trial output from TF-MxNE via MVAR regression?

[Per Arnold Lysne]

Hello All,



    My apologies for bringing up the same question regarding single trial output from tf-mxne several times - I hope my questions are getting better each time.



    As Dr. Gramfort has explained in the past, tf-mxne solves for both locations and their timecourses concurrently, and therefore there is no separate inverse operator which can be returned from this process and reused. This solution is based on an average evoked response, so no trial-wise output is possible. My problem is that I would like to use the tf-mxne output to estimate spectral Granger causality, and the spectral estimates this depends upon requires single trial output from the neural sources. It would be perfectly acceptable to use an average evoked response for the tf-mxne localizations, if it was then possible to apply this solution to obtain single trial timecourses at the resulting sources.



    As a solution to this I propose to MVAR regress the tf-mxne timecourses, representing the brain-space response, onto the average evoked response as seen at the sensors. The relationship between the sources and the sensors should be linear and constant in time, and this should yield a set of MVAR regression coefficients which may then be used as the inverse operator to generate single trial brain-space timecourses.



    I believe that the solution timecourses may be altered somewhat by doing this, as tf-mxne is based on discarding Gabor atoms as dictated by the mixed norm cost function, and that there is no guarantee that the resulting timecourses are directly linearly related to the sensor measurements, but I hope this effect to be minimal. (In my application, which depends upon maintaining linearity throughout the analysis pipeline, this may even be beneficial.)



    Does this seem appropriate?



Thanks again,



Per Lysne, The University of New Mexico
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