Update description in setup

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(