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Caveats There's some points to keep in mind when thinking about this: While it is true that connections in cortex are reciprocal, this does not mean that they are symmetric. Cortical connectivity is quite elaborate and the neurons that send bottom-up signals to the next higher area are not necessarily the same neurons that receive the feedback. The forward ...


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This scenario is practically unsolvable. If one doesn't have any assumptions about when, where, and how the changes may occur, then for 24 subjects (typically in this business, with high inter-subject variance due to age, sex, etc.) x 64 channels (usually, with variable SnR) x 45 frequencies (each signal exists in the frequency space of 1 to 45 Hz, at least) ...


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I fully endorse Benedikt's answer. Further, you have to specify the question you are asking. Let's say you want to know whether activity in a face recognition task differs between conditions in FFA, PPA, STS, and FEF and that the location of the difference is what you want to know, then Bonferroni is the correction of choice. In case you ask the question ...


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It is possible to look at within-subject interactions using cluster permutation tests. I.e. Eric Maris here: https://mailman.science.ru.nl/pipermail/fieldtrip/2011-January/003447.html 2x2x2 with factors A,B,C has 4 interactions AxB, AxC, BxC and AxBxC and 8 cells +--------+-------------+-------------+ | C = 0 | B = 0 | B = 1 | +--------+------...


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You have one p-values for each ROI timecourse (for the largest cluster) indicating whether your conditions are exchangeable. If you want to correct for the 4 ROIs you could use any adequate multiple comparison correction, from classical Bonferroni (which might be too conservative as the tests are likely not completly independent) to Benjamini-Hochberg style ...


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