Reference and Reporting Information¶
This page covers information for how to reference and report on using FOOOF, as well as some collected information and examples of projects, tools, and analyses that have and can be done using FOOOF.
Table of Contents¶
Reference¶
The reference for this power spectrum model and associated code module is the Parameterizing Neural Power Spectra paper.
This link currently leads to a preprint, on biorxiv, which describes the method. The full version of the paper is currently under review, and this link will be updated to the accepted journal version when available.
Please cite this paper if you use this method, and/or if you wish to refer to the our approach for parameterizing neural power spectra, and/or to refer to any ideas and examples from this website.
Reference
Haller M, Donoghue T, Peterson E, Varma P, Sebastian P, Gao R, Noto T, Knight RT, Shestyuk A, Voytek B (2018) Parameterizing Neural Power Spectra. bioRxiv, 299859. doi: https://doi.org/10.1101/299859
Bibtex
Example Applications¶
As well as reporting on the method, the full version of the paper includes simulation work as well as example analyses and applications. The code for the simulations and applications is indexed and available in the Paper repository.
You can also find the full list of articles that cite the Parameterizing Neural Power Spectra paper at this Google scholar link.
Methods Reporting¶
If you use this module and the power spectrum model in your work, there is some information you should include in the methods section.
Specifically, we recommend including the following information in the methods section:
The version number of the module that was used (for example 1.0.0)
The settings that were used for the algorithm that were used
You should report all public settings, even if default values are used
The frequency range of the data that was fit
In addition, we recommend that reports should include information on:
Details of the data, including modality and any preprocessing steps applied
How power spectrum were generated, including the length of segments used to calculate spectra
If and how model goodness-of-fit measures were assessed
Reporting Template & Example¶
To assist in reporting on using FOOOF, we have some templates and examples of methods reports, and some utilities to access the required information from the code.
The following box is an example of what a methods report might look like (where all of the X’s should be filled in with the relevant information).
Methods Report Template
The FOOOF algorithm (version X.X.X) was used to parameterize neural power spectra. Settings for the algorithm were set as: peak width limits : XX; max number of peaks : XX; minimum peak height : XX; peak threshold : XX; and aperiodic mode : XX. Power spectra were parameterized across the frequency range XX to XX Hz.
Generating Methods Reports¶
As of FOOOF version 1.0.0 there are code utilities to extract all required information for reporting, and for generating methods reports.
These utilities require a defined FOOOF object, such as FOOOF or FOOOFGroup, assumed to be called ‘fooof_obj’ in the following examples. This object will be used to extract all the relevant settings and any available meta-data for reporting.
The methods_report_info() function can be used to print out the information you need for reporting:
# Import the utility to print out information for reporting
from fooof.utils.reports import methods_report_info
# Print out all the methods information for reporting
methods_report_info(fooof_obj)
The methods_report_text() function can be used to print out an auto-generated methods report, like the one demonstrated above, with all available information filled:
# Import the utility to print out information for reporting
from fooof.utils.reports import methods_report_text
# Generate methods text, with methods information inserted
methods_report_text(fooof_obj)