From 9a8e45baa27225d87b8083b3433faf1881339d90 Mon Sep 17 00:00:00 2001 From: TomDonoghue Date: Tue, 3 Jul 2018 00:21:10 -0700 Subject: [PATCH] Update description in setup --- setup.py | 19 ++++++++++++++----- 1 file changed, 14 insertions(+), 5 deletions(-) diff --git a/setup.py b/setup.py index 73933d0a..3d3f8b89 100644 --- a/setup.py +++ b/setup.py @@ -16,13 +16,13 @@ FOOOF: Fitting Oscillations & One-Over F ======================================== -FOOOF is a fast, efficient, physiologically-informed model to parameterize -neural power spectra, characterizing both the 1/f background, and overlying -peaks (putative oscillations). +FOOOF is a fast, efficient, physiologically-informed model to parameterize neural power spectra, +characterizing both the aperiodic 'background' component, and periodic components as overlying peaks, +reflecting putative oscillations. The model conceives of the neural power spectrum as consisting of two distinct functional processes: -- A 1/f background, modeled with an exponential fit, with: -- Band-limited peaks rising above this background (modeled as Gaussians). +1) an aperiodic component, typically reflecting 1/f like characteristics, modeled with an exponential fit, with: +2) band-limited peaks rising above this background, reflecting putative oscillations, and modeled as Gaussians. With regards to examing peaks in the frequency domain, as putative oscillations, the benefit of the FOOOF approach is that these peaks are characterized in terms of their specific center @@ -32,6 +32,15 @@ modeling) is based on work from the Voytek lab and others that collectively shows that 1/f changes across task demands and participant demographics, and that it may index underlying excitation/inhibition (EI) balance. + +A full description of the method and approach is available in the paper linked below. + +If you use this code in your project, please cite: + +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 + +Paper Link: https://www.biorxiv.org/content/early/2018/04/11/299859 """ setup(