In this tutorial, we will cover the basics of using SpikeInterface for extracellular analysis and spike sorting comparison. We will be using three packages from the SpikeInterface github organization: spikeextractors, spiketoolkit, and spikewidgets.

For this analysis, we will be using a simulated dataset from MEArec. We will show how to:

• load the data with spikeextractors package
• load a probe file
• preprocess the signals
• run a popular spike sorting algorithm with different parameters
• curate the spike sorting output using Phy
• compare with ground-truth information
• run consensus-based spike sorting

For this tutorial we will need the following packages:

• spikeinterface
• MEArec
• klusta
• phy
• matplotlib

• all their dependencies.

To install those you can use the requirements.txt in this directory by running the command:

pip install -r requirements.txt

If you use a conda environment, you can create the spiketutorial environment with:

conda env create -f environment.yml

You might need to run:

ipython kernel install --user --name=tutorial

or:

conda install nb_conda_kernels and change Kernel to run the tutorial notebook.

The data used in this tutorial can be downloaded from Zenodo at this link.