Code & Data
Our lab codebase is almost entirely in
Python. Below we break out our software into three domains:
Scientific,
Paper-specific, and
Teaching & Educational.
While we host our code primarily on the lab's
Github repo, several of our projects have expended to full-fledged packages hosted on their own independent project repos (listed below). This is done in the spirit of open source development and not having any one research group "own" a project.
We make heavy use of the kindness of those who are willing to share their datasets with the world. Lab PhD alumnus
Tom Donoghue has curated a fantastic list of open neural electrophysiology datasets
here.
For a friendly introduction to Git, check out our post
here.
We strongly believe in open science, open data, and collaboration over competition. Voytek has published a few Reviews/Perspectives on these topics:
Scientific Software
We've written quite a few open-source Python pacakges for neural data analysis. We've created detailed, step-by-step tutorials for working with those three packages for a day-long invited workshop that we ran at the 2022 Society for Psychophysiological Research conference.
You can work through those materials
here.
- NeuroDSP: neural digital signal processing
- Citation: Cole S, Donoghue T, Gao R, Voytek B. NeuroDSP: A package for neural digital signal processing. J Open Source Softw, 2019.
- repo
- documentation
- fooof: fitting oscillations and one-over-f (parameterization of neural power spectra)
- Citation: Donoghue T*, Haller M*, Peterson E*, Varma P, Sebastian P, Gao R, Noto R, Knight RT, Shestyuk A¶, Voytek B¶. Parameterizing neural power spectra into periodic and aperiodic components. Nature Neuroscience, 2020.
- repo
- matlab wrapper
- documentation
- bycycle: cycle-by-cycle analysis of neural oscillations
Paper-specific Code
We also include code and data (where possible and permitted) for our manuscripts. The list of papers for which these are available are on our GitHub [here](github.com/voytekresearch/VoytekLab).
Teaching & Educational Software
Lab members also teach a number of data science, programming, and neural analytics classes.
- COGS 9 - Introduction to Data Science: Developed by Voytek
- Citation: forthcoming
- repo
- COGS 18 - Introduction to Python: Developed by lab PhD student, Tom Donoghue
- COGS 108 - Data Science in Practice: Developed by Voytek and lab PhD student, Tom Donoghue
- Citation: Donoghue, Voytek, Ellis. Teaching Creative and Practical Data Science at Scale. J Stats Education, 2020.
- repo
- documentation