Morlet wavelets for M/EEG analysis, [ˈmiːglɪt]
This package provides a lean implementation of Morlet wavelets designed for power-spectral analysis of M/EEG resting-state signals.
- Distinct frequency-domain parametrization of Morlet wavelets
- Established spectral M/EEG metrics share same wavelet convolutions
- Harmonized & tested Python and MATLAB implementation numerically equivalent
- Comprehensive mathematical documentation
import matplotlib.pyplot as plt
from meeglet import define_frequencies, define_wavelets, plot_wavelet_family
foi, sigma_time, sigma_freq, bw_oct, qt = define_frequencies(
foi_start=1, foi_end=32, bw_oct=1, delta_oct=1
)
wavelets = define_wavelets(
foi=foi, sigma_time=sigma_time, sfreq=1000., density='oct'
)
plot_wavelet_family(wavelets, foi, fmax=64)
plt.gcf().set_size_inches(9, 3)| Background | overview on scope, rationale & design choices |
| Python tutorials | M/EEG data analysis examples |
| Python API | Documentation of Python functions and unit tests |
| MATLAB functionality | MATLAB documentation and data analysis example |
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In your environment of choice, use pip to install meeglet:
pip install meegletPlease clone the software, consider installing the dependencies listed in the `environment.yml.
Then do in your conda/mamba environment of choice:
pip install -e .When using our package, please cite our two reference articles:
Python implementation and covariance computation.
@article{bomatter2024,
author = {Bomatter, Philipp and Paillard, Joseph and Garces, Pilar and Hipp, J{\"o}rg and Engemann, Denis-Alexander},
title = {Machine learning of brain-specific biomarkers from EEG},
year = {2024},
journal = {eBioMedicine},
url = {https://doi.org/10.1016/j.ebiom.2024.105259},
date = {2024/08/05},
publisher = {Elsevier},
isbn = {2352-3964},
month = {2024/08/06},
volume = {106},
}General methodology, MATLAB implementation and power-envelope correlations.
@article{hipp2012large,
title={Large-scale cortical correlation structure of spontaneous oscillatory activity},
author={Hipp, Joerg F and Hawellek, David J and Corbetta, Maurizio and Siegel, Markus and Engel, Andreas K},
journal={Nature neuroscience},
volume={15},
number={6},
pages={884--890},
year={2012},
publisher={Nature Publishing Group US New York}
}M/EEG features based on Morlet wavelets using the more familiar time-domain parametrization can be readily computed is sevaral major software packages for M/EEG analysis: