Creating ERPs contralateral and ipsilateral to response hand

Hi! Iā€™m doing a surface laplacian (or current source density) analysis over the motor cortex for a task where participants had to respond with either their right hand or their left hand. What I want now is to combine the ipsilateral signals over the motor cortex and the contralateral signals over the motor cortex, and compare those. So for the ipsilateral signal: combine the potentials of the C4 channel in the right-hand response trials with the potentials of the C3 channel in the left-hand response trial. For the contralateral signal: combine the potentials of the C3 channel in the right-hand response trials with the potentials of the C4 channel in the left-hand response trials.

Basically, I want to end up with a plot that looks like this:

Iā€™ve already tried to put the ipsilateral signals (C3 right hand and C4 left hand) in two different evoked objects, and then combine them with grand_average, but it gives the error that the channel names donā€™t match. Is there another way to average two signals from two different channel names and two different objects? Or is there an easier way to achieve what I want?

(my question is a lot like this question from eeglab but I couldnā€™t find anything in MNE for this)

Perhaps this question is a bit simpler to answer: how can I merge the contralateral signals from these plots? Basically, how can I merge a signal of two different channels of two different sets of data

Let me know if anything is unclear in my question. Iā€™ve been stuck with this for some time so I could really use your help!

In this case, we need to abandon the existing channel names (C3, C4) and instead name them something like ā€˜ipsilateralā€™ and ā€˜contralateralā€™:

evoked_left.rename_channels({'C3': 'ipsilateral', 'C4': 'contralateral'})
evoked_right.rename_channels({'C4': 'ipsilateral', 'C3': 'contralateral'})

Then, we can combine them:

evoked = mne.combine_evoked([evoked_left, evoked_right], weights='nave')
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