Running first level analysis with varying number of different trial_types per run

Note sure what you want to do, but indeed there is the possibility to handle all you data as if it were one single session by creating a large block-diagonal design matrix, in which each block is the design matrix for one sessions.
Note that in this case, even the confounds of the different blocks are handled cleanly.

The only caveat I can see is memory cost for the fit.

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