I am looking to replicate the following analysis:
On the left, is the evoked data (GFP) plot for a selection of sensors for one condition vs. another. On the right, is the averaged GFP data represented on the left plot on the corresponding dark grey and light grey time segments.
I searched through the MNE API to see if there is a direct way of extracting two subsets of data of different time windows from a single
mne.epochs output, but there doesn’t seem to be any.
I thought about splitting an epoch into two subsets using
evoked_data.crop(1.0,1.5) but that wouldn’t work since MNE would not be able to simultaneously plot the two data sets since they are of different time windows and they can’t seem be re-centred to 0.0s.
Alternatively, I think it is possible to create two different new events (pre and post event) by manipulating the original data’s time stamp, then add them via
raw.add_events at the data pre-processing stage. But this is extremely tedious for me since I have multiple event types and I will end up with a large, messy set of
So my question is, is there any MNE function out there that I am not aware of that is capable of helping me get what I require here in the neatest way possible? If not, then how do people usually do this using what is already available on MNE? To summarize, I am looking to:
- Be able to extract subsets of an epoch data based on specified time windows,
- Access the epoch data (epoch.data doesn’t work) so I can calculate the mean evoked value (eg. average GFP of GFP activity between -1.5 to -1.0s) explicitly from these extracts.