[Mne_analysis] concatenation brainvision raws issue

[Marianne DUYCK]

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Dear mne_analysers,

I’m new to mne and ran into a problem I can’t seem to solve in a timely manner so I’m hoping you might have some suggestions.

To analyse an eeg experiment (brainvision), I need to concatenate several experimental blocks (each participant ran several blocks of different lengths and different number of triggers).

If I load each block separately mne.io.read_raw_brainvision(block_nb_path) and I block_nb.get_data(), I have no problem accessing the data and the ‘STI 014’ channel has the correct trigger data of the correct length.
When I concatenate them using:
    blocks = [mne.io.read_raw_brainvision(block_path) for block_path in blocks_paths]
    pooled_blocks = concatenate_raws(blocks)
Still no errors.

However, when I try accessing the data with pooled_blocks.get_data() I have a concatenation error (details attached). After tracking it down carefully it seems that when the successive segments of data are read, the trigger channel data used is the one of the first block for all the blocks (therefore the error because some later blocks are shorter than the first one).

So I am wondering if I have done something wrong and how I could find a solution to that issue. One idea I had to get around that problem was to add a concatenated event list as an argument to the concatenate_raws  function but I am not sure if it’s a viable solution and how to actually do it.

Thanks a lot in advance for any input,

Marianne

PS: I’m using mne 0.16.2 (anaconda and python 3.6)

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