PP

Once you extract the physic driver data, then set the non zero values to zero and clip the beginning or the end of your data because of the overshoot effect of convolution. Then you can do an auto-corrolation on your data.

Thank you!

make sense. Sounds reasonable. I also noticed that plotting the data with t and driver gives me huge outliers toward the end of the graph. Any idea what is going on there? I tried for multiple files and they follow similar pattern.

Mathias, I modified the sdeco.m with the following lines and I am extracting the driver data. - Does this sound right to you? filename = erase(leda2.file.filename, '.txt'); driver_data = [t;driver].'; %transpose of matrix writematrix(driver_data,filename+"_driver.csv"); What I am not sure about is what to do with the negative values of the driver. Should I set them to zero?

Thank you!

Hi Mathias, Before diving into your code, I was wondering if I extract leda2.analysis0.driver, will I get the contentious deconvoluted smoothened SC/IRF? Thank you

Thank you Christopher. If we fit linear mixed models and incorporate the random effect of participant id when explaing SCR (as a DV), would'nt that be sufficient?

Thank you Christopher. If we fit linear mixed models and incorporate the random effect of participant id to explaing SCR (as DV), would that take of the individual difference amelioration?