[Mne_analysis] running artifact rejection and then linear regression

[Dan McCloy]

Epochs objects have a property called "selection" that give you the indices
of the epochs that were not dropped.  You can use those indices to select
only those rows of your design matrix.
-- dan

Daniel McCloy
http://dan.mccloy.info/
Postdoctoral Research Associate
Institute for Learning and Brain Sciences
University of Washington

On Wed, Sep 6, 2017 at 8:36 AM, Roberto Petrosino <
roberto.petrosino at uconn.edu> wrote:

> Hi all,
>
> I am trying to run linear regression on epochs after artifact rejection.
>
> Each epoch in my data refers to a specific stimulus (say, a specific word)
> having specific predictors (i.e., frequency values) associated with it. I
> have constructed a design matrix with all the predictors I would like to
> run regression against for each epoch. Since each stimulus will have
> specific values for the predictors, I assume that if I reject all bad
> epochs before running regression, there will be a mismatch between the
> dimension of the data to be regressed and the dimension of the design
> matrix array.
>
> So, my question is: is there any way around this - e.g., is there a way
> have bad epochs only marked as bad, and run linear regression on good
> epochs only? That way, the dimension of the data to be regressed and the
> design matrix are the same, but the actual regression calculations will be
> run selectively. I know that the function linear_regression_raw has the
> arguments reject and flat that would allow me to do what I want, but I’d
> actually rather use linear_regression on already epoched and
> ICA-corrected data, but I don’t seem to find any similar option that would
> suit my case.
>
> Many thanks in advance,
>
> -Roberto
>
> ----------
> Roberto Petrosino
> Ph.D. Student in Linguistics
> CT Institute for the Brain and Cognitive Sciences
> University of Connecticut
>
>
>
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