NPA leverages the FOOOF parametric model of neural power spectra to select, amplify, or attenuate different components of neural time series to compare decoding experiments and investigate the contributions of each component to brain function.
Example usage: https://nbviewer.jupyter.org/github/crocodoyle/npa/blob/master/npa/examples/NPA%20Example.ipynb
If you use this code in your project, please cite:
Doyle, JA, Toussaint, PJ, Evans, AC. (2019) Amplifying the Neural Power Spectrum. bioRxiv, 659268.
doi: https://doi.org/10.1101/659268
Link: https://www.biorxiv.org/content/10.1101/659268v1.abstract
NPA is written in Python, and requires Python >= 3.5 to run. It has the following dependencies:
- numpy
- scipy >= 1.2
- fooof
- mne >= 0.17