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OscMethods: Animated Visualizers

This is the source repository for animated visualizations for the OscillationMethods project.

Paper Website

Overview

This repository includes the code to create the animated visualization, as well as copies of the final outputs.

The animated visualizers, with descriptions, are also available on the vizualizations page of the project website.

ReUse

Copies of the animated visualizations are available in the gifs/ folder. These visualization are available for re-use under a Creative Commons CC-BY 4.0 license, meaning re-use, with attribution, is allowed.

The code to create these visualizations is available in the notebooks/ folder, under the MIT License, meaning if you wish to use and adapt this code, you may do so.

If you re-use these animations and/or the code, please cite the associated paper.

Citation

Associated paper:

Donoghue T, Schaworonkow N, & Voytek B (2022). Methodological considerations for studying neural 
oscillations. European Journal of Neuroscience, 55(11-12), 3502-3527 DOI: 10.1111/ejn.15361

Direct Link: https://onlinelibrary.wiley.com/doi/10.1111/ejn.15361

Visualizations

This repository creates the following visualizations:

#0 - Oscillations Introduction

An introductory visualization showing oscillations, with the time series, filtered trace, and power spectrum:

fig0

#1 - Oscillation Presence

A visualization showing illusory oscillations, whereby filtered aperiodic activity can look rhythmic:

fig1

#2 - Center Frequency

A visualization showing how variable center frequency can impact measures:

fig2

#3 - Aperiodic Activity

A visualization showing how dynamic aperiodic activity can impact measures:

fig3

#4 - Temporal Variability

A visualization showing how temporal variability (burstiness) can impact measures:

fig4

#5 - Waveform Shape

A visualization showing how waveform shape can impact measures:

fig5

#6 - Overlapping Sources

A visualization showing how overlapping sources can lead to different results at a recording electrode:

fig6

#7 - Signal-to-noise ratio

A visualization showing how variable signal-to-noise ratio can impact measures:

fig7