Posts eeg3/14/2024 ![]() Now we load the saved epochs from last notebook. We imported all the necessary dependencies. import mneįrom autoreject import get_rejection_threshold Note that the plots below will be using print statements for demonstration purposes. ![]() At the end, we plot the ERPs by channels that we are interested in looking and make comparison. Then, we implement autoreject ( ) which automatically attempts to find bad channels and interpolate those based on nearby channels. We look in ICs to identify potentially bad components with eye related artifcats. In this section, we run independent component analysis (ICA) on the epochs we had from the last notebook. In the previous walkthrough notebook, we got to manually inspect raw instance and do some cleaning based on annotations and creating evoked responses from time-locked events. This post is a ported version of Jupyter Notebook from my mne-eeg project:
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