[FieldTrip] Cluster based permutation test interpretation

[Yvonne Visser]

Dear all,

Thank you for welcoming me to the discussion list, my name is Yvonne Visser and I currently work as a research assistant with dr. Aaron Schurger at Neurospin. During my masters program I learned about cluster based permutation tests for electrophysiological data and distinctly remember how from this type of test one can not conclude that a particular cluster is significant (in line with what is said on the fieldtrip website here, http://www.fieldtriptoolbox.org/faq/how_not_to_interpret_results_from_a_cluster-based_permutation_test)<http://www.fieldtriptoolbox.org/faq/how_not_to_interpret_results_from_a_cluster-based_permutation_test>

We are currently using the cluster based permutation test in the analysis of our experiment, but we are a bit confused on
how to interpret the results from our test.
To give you a short introduction to our experiment: we are looking for a relationship between a behavioural variable and our collected EEG data. So we computed the grand average time frequency spectrum in a single channel of the time bins of interest. Then, we correlated each time/frequency point in this 2d matrix with the behavioural variable in that trial. This resulted in a correlation matrix like you can see in attachment1_correlationmatrix. As you can see, we also computed clusters of time/frequency points with p<0.05. After computing the permutations, we found that the biggest "real" cluster is bigger than any of the permuted clusters.

Now, we would like to conclude something from this result about which frequency band at what time is correlated to our behavioural variable. We found a fieldtrip function called ft_clusterplot that does seem to suggest that you can highlight a specific cluster it if it survives the test, but isn't that exactly what my lectures and the webpage say we should not do? Can we say that activity in the alpha band around -0.75 to 0 (where the biggest cluster is located) is correlated to the size of the movement? Or should we not conclude something about which cluster is significant and can we only say that some time frequency power is correlated to our behavioural variable? If the second is true, do you have any advice for us to make the interpretation more specific?

Thank you so much in advance, and please let us know if anything is unclear.
Kind regards,
Yvonne & Aaron.

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