quick way to get lateralisation

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1

hello,

potentially a stupid question, but I don’t think there’s a current implementation in mne for this. Is there a quick way of subtracting activity in one hemisphere from the other, per time point? e.g. after this, PO8 wouldn’t be PO8, but would be PO8-PO7, and vice versa.

the tl;dr is that currently im just making a duplicate object, reordering channels, subtracting their data objects and reassigning, but not sure if this is the best

tfr = mne.time_frequency.read_tfrs(fname); tfr = tfr[0] #it reads in a list of tfr objects idk why
tmp  = tfr.copy()

chs = [ ... ] # long list of channel names
chs_flipped = [ ... ] #manually reorder to have it flipped around z-line

tmp = tmp.copy().reorder_channels(chs_flipped)
tmp2 = np.subtract(tfr.copy().data, tmp.copy().data)

tf_flipped = tfr.copy() #creates EpochsTFR object with original info
tf_flipped.data = tmp2 #assign subtracted data

it’s possibly the best to be done at the moment, but wasn’t sure if there was a less cumbersome way of doing it

thanks!

2

Hi, you can use the bipolar referencing feature to create new virtual channels that are formed by subtracting the signals of two existing channels.

Here’s an example I quickly cooked up:

# %%
import mne

# Load the data
ssvep_folder = mne.datasets.ssvep.data_path()
ssvep_data_raw_path = (
    ssvep_folder / "sub-02" / "ses-01" / "eeg" / "sub-02_ses-01_task-ssvep_eeg.vhdr"
)
raw = mne.io.read_raw_brainvision(ssvep_data_raw_path, preload=True)
raw.set_montage("easycap-M1")

# %%
# Split channel names into Left, Right, Midline
channel_selection = mne.channels.make_1020_channel_selections(
    info=raw.info, return_ch_names=True
)

# %%
# Perform the subtraction
raw_reref = mne.set_bipolar_reference(
    raw,
    anode=channel_selection["Left"],
    cathode=channel_selection["Right"],
)

# %%
# Visualize results
raw_reref.plot()

We also have a somewhat related example, which you can find at Using contralateral referencing for EEG — MNE 1.5.1 documentation

Best wishes,
Richard

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