I am a relative newby to Brainstorm and am investigating affect in learning relative to Frontal Asymmetry. The literature seems to say that differential activation in the left v right frontal lobes has an emotional valence (greater left > positive; great right > negative). What advice do you have for this examination? (The study employs a real-world learning task with subtasks lasting from one to several minutes. I plan to epoch the continuous data for each task using 2 second samples.)
Sensor pairs of interest include F3-F4, FC3-FC4, F7-F8. It might also make sense to combine frontal-left and frontal-right sensors into composite values for the bilateral comparison. A variety of frequencies may come into play, as the literature is varied on this.
What techniques/types of analyses should I use? Welch PSD with frequency normalization? Would these values be directly comparable? Data collection just ended so I have real data to work with.
And how would I extract values for comparison in Brainstorm and export to external stats package?
What advice do you have for this examination?
What techniques/types of analyses should I use? Welch PSD with frequency normalization? Would these values be directly comparable?
I'm sorry, I have no experience with this. Maybe some of our collaborators have advices for you? @Sylvain@leahy@jcmosher@pantazis?
And how would I extract values for comparison in Brainstorm and export to external stats package?
It depends on the type of data you want to export.
If you right-click on most data files in the Brainstorm database explorer, you would find a menu File > Export to file. Check the various file formats available depending on the analysis software you want to use.
An example for processing source files in SPM is documented here: http://neuroimage.usc.edu/brainstorm/ExportSpm8 http://neuroimage.usc.edu/brainstorm/ExportSpm12
I can suggest you start with reproducing the analyses you have read from the literature. If you have any more specific physiological hypothesis regarding the expected effects produced by your experimental design, then this will inspire the methods to be used.
Thanks as always for the insight. Here is a bit more info.
I can derive the Frontal Asymmetry Index (FAI) using log(power) values from opposing sensors in frontal areas (eg, F7/F8). I have 2-second epochs. Running Welch PSD then Spectrum Normalization across all trials in a condition gives me average log(power) for the condition. I double-click the result to see the accompanying graph display. I can grab the data (save to file) I want from the accompanying display (eg, F7 alpha=29.9144). Save file then open in Excel. Then FAI can be calculated using FAI=log(alpha power right F8) - log(alpha power left F7). So far so good (I think).
I would also like to get the average log/power for each trial in the condition (so I can export to external stat package and examine things like variance). I can run Welch PSD then Spectrum Normalization for each trial. Double-click on the result and get a display similar to the one for PSD all trials. However, in order to get the corresponding value for each trial, it looks like I have to display the graph for each trial separately in order to get the value I want. Using this method, I would have to manually extract the info per trial which of course would take a very long tedious times.
Is there some way I can export the log(power) values per trial for a given condition? I tried export to Matlab but it doesn’t give me comparable numbers compared to values exported from graph display.
If you want to go beyond what is available in the interface, it is probably simpler if you read the .mat files directly yourself, and run the computation you want on them.
The structures of the various files of the Brainstorm database are documented in the various introduction tutorials, in the sections “On the hard drive”. Example: http://neuroimage.usc.edu/brainstorm/Tutorials/TimeFrequency#On_the_hard_drive