tnbs_stim_clean

Description

tnbs_stim_clean provides functionality to clean EEG, MEG, and other time-series data from mne-python by removing unwanted stimuli using the tnbs_stim_clean function. This is especially useful in preprocessing to remove noise or artifacts from signals caused by stimuli events.

Installation

You can install the package via pip from PyPI:

pip install tnbs_stim_clean

Example use

import tnbs_stim_clean as tnbs

# Example parameters
raw  # Raw time series data in MNE's raw object format
half_win = 100  # Half window size around each stimulus (in samples) that will be chopped away from the artifact peak point
threshold = 0.0001  # Threshold above which stimulus is considered significant

# Apply stimulus cleaning 
raw_cleaned = tnbs.stim_clean(raw, half_win, threshold)