Conversion of .CSV file into MNE-Python Object

[Upadhayay Bibek]

Hello,

I am wondering if there is any built-in method or an alternative or some Github repo, that contains the example where the exported EEG data in CSV file can be converted to the MNE-Python object.

[luckham jerill]

Hello Bibek.  Thank you for your question.  You can try this string:

import mne
import numpy as np
import pandas as pd

df = pd.read_csv(“<path to psychopy_recording>.csv.gz”)
for c in df.columns:
print(c)

eeg_channels = [‘AF3’, ‘T7’, ‘Pz’, ‘T8’, ‘AF4’] # get from the columns printed above
sampling_frequency = 1 / (df[‘timestamp’][df.shape[0]-1] – df[‘timestamp’][df.shape[0]-2])
print(eeg_channels)
ch_types = [‘eeg’] * len(eeg_channels)
info = mne.create_info(eeg_channels, ch_types=ch_types, sfreq=sampling_frequency)
info.set_montage(‘standard_1020’)

data = np.array(df.loc[:,eeg_channels])
mne_object = mne.io.RawArray(data.T, info)
mne_object.plot(show_scrollbars=False, show_scalebars=False)

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