Electrode Pooling Data and Code
MM 7/12/2021
This repo accompanies our preprint
[Kyu Hyun Lee, Yu-Li Ni, Jennifer Colonell, Bill Karsh, Jan Putzeys, Marius Pachitariu, Timothy D. Harris, and Markus Meister (2021) Electrode pooling: boosting the yield of extracellular recordings with switchable silicon probes. BioRxiv 851691.] (https://www.biorxiv.org/content/10.1101/851691v2)
It contains all the data and code needed to reproduce the published analysis.
Contents of the repo
-
Jupyter notebooks (Python) and m-files (Matlab):
Theory,Saline,Invivo,Simulation,Simulation_Fig,accuracyQC.m. These notebooks develop the various topics of analysis, starting from raw data, producing figure panels and numerical results for the article along the way. They contain a good number of comments and mathematical sections to guide the user. -
code/: Contains routines accessed from the notebooks. -
data/: Data files, both input and output. -
figs/: Image files that make up the figure panels in the article.
How to reproduce all the analysis starting from raw data
- Read our paper. A version from May 3, 2021 is included in the repo.
- Empty the
figs/directory. - Run the notebooks and m-files in this order:
Theory.ipynb- Fig 2Saline.ipynb- Fig 4, Fig 8Invivo.m- Fig 5Simulation.m- Fig 6Simulation_Fig.ipynb- Fig 6accuracyQC.m- Fig 9
- Now the
figs/directory should contain all the figure panels.
How to find code for a specific figure panel
- The names of all the figure panels (as numbered in the preprint) appear as headings in the Jupyter notebooks. Look through these to find your figure of interest. Or...
- In the
figs/directory find the name of the figure file of interest, and search for that name in the Jupyter notebooks or m-files.
Simulation details (optional)
The m-file code/fig_6B_code/main_genSimulation.m creates samples of voltage traces for simulated pooling, with parameters of Amp, Firing rate, and Noise.
Compatibility
Matlab code was tested on Matlab version R2020b.
Jupyter Notebooks were run on MacOS using Python 3.8.