Greetings,

I was investigating within-subjects sensor-level ERPs in response to non-invasive vagus nerve stimulation, but I'd like to investigate the source of the differences. Since I am using an MNI template, I opted for unconstrained sources, partly because I'm interested in deeper sources like the insula, but also because I lack individual MRI scans.

I have read the documentation, and settled on dSPM for examining source-level differences and have tried following guidelines for testing |A| - |B| = 0. Are the following steps I took appropriate?

- Compute sources (2018) on the average ERP: Minimum norm with dSPM, unconstrained, with default options on depth weighting, noise cov. regularization, and SNR.
- Flatten the unscaled dSPM outputs for each subj/condition so I have Ai and Bi.
- To test |A| - |B| = 0, I used Fieldtrip permutation based testing. Got nice results in regions that are consistent with my expectations, but....

For (3) I was pondering the interpretation of "This test does not consider the sign difference within a subject, and therefore cannot detect correctly when A and B have opposite signs. Works well and indicates **which condition has higher values** when A and B have the same sign within a subject". It seemed to me that if you use dSPM to test |A| - |B| = 0, you must necessarily follow the form: norm(z-score(A)) - norm(zscore(B)).

If I have computed norm(z-score(A)) - norm(zscore(B)) that gives you "ambiguous amplitude, but meaningful sign" as described in the Differences tutorial. This seems incompatible with interpretability of the test |A| - |B| = 0 where sign doesn't matter. Can this be reconciled?

Some other questions:

- From computing dSPM to flattening, did I miss a step, i.e. did I not actually norm the orientations for Ai and Bi?

Otherwise said, the only time I can find a way to apply the norm of the three orientations is if I try to compute the subject level difference (i.e. yielding me only one value per subject). - I am better off doing a "where and when" analysis? If so, do I get the subject difference on the unscaled dSPM output, (check the norm box), then flatten the difference?

If I am unclear at all, please let me know and I will attempt to rephrase my confusion.

Thank you, also for answering other recent inquires!