Project repository, part of the parameterizing neural power spectra project.

This repository applies spectral parameterization to simulated data.

This repository tests the spectral parameterization algorithm on simulated data.

Simulation tests include:

• testing performance on reconstructing individual periodic and aperiodic parameters
• testing performance with global measures such as the number of fit peaks and model reconstruction error
• testing how sensitive the algorithm is to model assumptions and violations of these assumptions
• testing the algorithm in comparison to other related methods

You can follow along with this project by looking through everything in the notebooks.

The analyses in this repository were done as part of the parameterizing neural power spectra paper.

A guide to all the analyses included in this paper is available here.

This project was written in Python 3 and requires Python >= 3.7 to run.

In addition to general scientific Python packages (available in the Anaconda distribution) this analysis requires the following Python packages:

• fooof == 1.0.0
• neurodsp >= 2.1.0

All required 3rd party packages are described in requirements.txt.

This project repository is set up in the following way:

• code/ contains custom code for this analysis
• notebooks/ is a collection of Jupyter notebooks that perform the analyses and create figures