In the computation of the NxN connectivity matrices, the diagonal values are set to zero, because we are not interested by the connectivity measure between a signal and itself.
If we keep these high values, it may distort the display by forcing the scaling of the colorbars to a range of values that is not representative of the values of interest.
Let’s consider N scouts that all include M dipoles.
[B]Apply scout function before[/B]: First it computes the average of the sources time series by scout (N scouts), then computes the connectivity matrix (NxN).
This connectivity matrix contains zero values on the diagonal, and is saved directly as the output file.
[B]Apply scout function after[/B]: First it estimates the connectivity between all the possible sources in all the scouts (NM sources, [NMxNM] connectivity matrix), this matrix contains zeros on the diagonal. Then it applies the scout function to the connectivity values by pair of scouts: computes NN times the average of MM values. Each average of these MM values, corresponding to the connectivity value for a pair of scouts, has very little chance to be zero (even if there are zeros on the diagonal). The final connectivity measure saved to the output file for a scout with itself is usually not zero. This is why you don’t observe zeros on the diagonal in this case.
Does it make sense?