Question
Asked 10 January 2024

How to use permutation testing for single-channel, single-trial time-frequency analysis to compare post-baseline and baseline differences?

I aim to compare differences between post-baseline and baseline in time-frequency data, but attempting a t-test on average power post-baseline revealed differences across all frequency bands, which seems erroneous for my experiment. There's a suggestion to use permutation testing, but I'm uncertain how to analyze it on a single-channel, single-trial basis, as most tutorials focus on multiple trials, subjects, or channels. Is permutation testing impractical for my data?

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