Epiphyte

This project is a processing pipeline for high-dimensional single-unit neural activity colligated with meta data. We present a toolbox for organizing neural activity alongside meta-data and stimulus information, as well as a processing pipeline which allows ad-hoc importing, exporting, annotating, and visualizing of data. Our toolbox is developed for large sets of continuous single-unit recordings and introduces a set of modules for algorithmically and manually annotating data, defining data irregularities, and designating new layers of meta-data for further analyses.

Installing the package

Note: These installation instructions assume that you have basic fluency in Python and command line interfaces. If you would like to set-up this package from scratch, check out the more robust instructions here.

(1) Install the required packages by running the following command (Note: we highly recommend doing so within a virtual environment with Python==3.7):

If using PyPip:

pip install -r requirements_pip.txt

If using Conda:

conda create --name <env> --file requirements_conda.txt

(2) Go to the top-level folder of Epiphyte and install the package itself

pip install -e .

(3) Set up a DataJoint database

Prerequesites:

• install docker
• install docker compose

Actual setup:

• follow instructions on DataJoint tutorial page to set up for using a docker container with database.

  Note for macOS users: we recommend installing MySQL via Homebrew (as opposed to the direct download via Docker or MySQL). For instructions, check out the Homebrew instructions or step 6 of the install tutorial.

• navigate to the top-level directory of Epiphyte and run the docker container:

sudo docker-compose up -d

• run database/database_set_up.ipynb notebook to fill the database with the mock data
• now everything should be set up and ready to go!
• for troubleshooting issues, check out here.