Subtraction of PSD Topomaps


I would like to make a plot of two subtracted psd topomaps. Is this possible?
I have epoched my data and would like to subtract different epochs from each other. Kind of like this:
epochs[‘Rec1’].plot_psd_topomap() - epochs[‘Rec2’].plot_psd_topomap()


Ps. I found a "Maling List Archive (Read-only) topic about this. Sorry for the duplicate, but the old one has no answers.

Sure, this is possible, but you would have to operate on arrays. First you would use psd_welch function on both you epochs objects (you could also use multitapering if you prefer):

psd1, freq = psd_welch(epochs1, ...)
psd2, freq = psd_welch(epochs2, ...)

(the arguments that would go where the ... are depend on your data and desired frequency resolution etc. see the psd_welch docs)
To subtract the power you can just do:

psd_diff = psd2 - psd1

And then you can plot it using mne.viz.plot_topomap:

# find the index of the frequency you want to plot
frequency = 10
freq_idx = np.argmin(np.abs(freq - frequency))

# plot the desired frequency
mne.viz.plot_topomap(psd_diff[:, freq_idx],
1 Like

Great thanks! It works :slight_smile:
Can it also work on frequency bands? I would like to look the alpha and gamma band?

Sorry, I can also try myself! :wink:

Is it ok to do like this:

# find the index of the frequency you want to plot
frequency_band = [8, 12]
freq_idx = [np.argmin(np.abs(freq - frequency_band[0])), np.argmax(np.abs(freq - frequency_band[1]))]

# plot the desired frequency
mne.viz.plot_topomap(psd_diff[:, freq_idx].mean(axis = 1),

Oh, sorry, I didn’t see your reply, yes it is almost the same solution as mine below.
Be sure to specify a range (i use it with slice) instead of just the two indices.

Sure, instead of one frequency index you could use a range, for example:

freq_limits = [8, 12]
freq_idx = [np.argmin(np.abs(freq - frequency)) for frequency in freq_limits]
freq_range = slice(freq_idx[0], freq_idx[1] + 1)

# average the frequency range:
psd_avg = psd[:, freq_range].mean(axis=1)

# plot

(BTW - for gamma you may prefer to use multitapering with some frequency smoothing instead of welch)