Source code for restingIAF, an automated resting-state individual alpha frequency (IAF) estimation routine implemented in MATLAB.
Repo also contains manuscript preprints (long and short(er) versions, archived on bioRxiv) outlining the rationale for programme development, its performance across simulated and non-simulated EEG datasets, and guidelines for parameter settings. The long version includes a detailed examination of some of the problematical features of conventional approaches to IAF estimation. It also contains additional technical details that were omitted from the short version. Most of these details are collated in the latter's accompanying appendix.
Materials required to replicate the simulation analyses reported in the manuscipt can be found in the simulations directory.
Run simsSingle to replicate the preliminary (single component) analysis; run simsMulti for the multiple channels / mixed components analyses.
These scripts include code to reproduce the tables and figures included in the results section of the manuscript.
Simulations depend on the pinknoise function (v1.5), which has been included as part of the simulation materials.
Please see the LICENSE associated with this source code for terms and conditions of its use and distribution.
Updates and more information about the function (along with others for generating red, blue, and violet noise signal) can be accessed from the MATLAB File Exchange.
A tutorial analysis routine (including sample EEG data) is provided to familiarise you with various features of the package.
This script may serve as a useful model for integrating restingIAF within your own pipeline, however we strongly recommend that you carefully consider whether the approach implemented in the tutorial is suitable for your analysis plan.
If you experience any difficulties implementing restingIAF, please attempt to replicate the analysis detailed in the tutorial readme before contacting us for assistance.
All functions were developed and tested in MATLAB 2014b/2015a, and may not be fully compatible with other versions of MATLAB.
The algorithm is dependent on the Signal Processing Toolbox.
Software developed in collaboration with Dr. Phillip Alday, Prof. Matthias Schlesewsky, & Prof. Ina Bornkessel-Schlesewsky at the Centre for Cognitive and Systems Neuroscience, University of South Australia.
Constructive criticism, corrections, and potential improvements are most welcome.
E-mail: andrew{dot}corcoran1{at}monash{dot}edu | Twitter: {at}mr_corcorana
A preliminary implementation in Python for use with MNE-Python is available as part of the philistine package.
If this software was useful for your work, please credit it by citing our methods paper:
Corcoran, A.W., Alday, P.M., Schlesewsky, M., & Bornkessel-Schlesewsky, I. (2018). Toward a reliable, automated method of individual alpha frequency (IAF) quantification. Psychophysiology, 55(7), e13064. doi: 10.1111/psyp.13064
Current/previous release versions may also be cited:
Corcoran, A.W., Alday, P.M., Schlesewsky, M., & Bornkessel-Schlesewsky, I. {year}. restingIAF {version} [Software]. Retrieved from https://github.com/corcorana/restingIAF. {doi}
Each release is issued a unique doi from Zenodo.
v1.0.3
A few minor bug fixes and documentation updates:
- Update publication citation info
- Correct parsing error for
restingIAF'norm' input - Enable zero overlap for
pwelchfunction - Adjust search range in
findF1to prevent potential error
v1.0.2
v1.0.1
v1.0
v0.1
This software was developed in the hope that it would be of some use to the EEG research community, and is freely available for redistribution and/or modification under the terms of the GNU General Public Licence. It is distributed WITHOUT WARRANTY; without even the implied warranty of merchantability or fitness for a particular purpose. See the GNU General Public License for more details.
Copyright (c) 2016--2019 Andrew W. Corcoran. (Any coding errors or inelegancies are solely his fault.)