nicespike: Analysis of high-density multi-electrode array (HD-MEA) recordings

doi preprint doi code

Requirements

A GPU with installed CUDA is necessary to run nicespike on Linux (or WSL).

Installation and running in docker container

Running nicespike in a docker container is the recommended option. It is documented in the docker branch.

Installation in a python virtual environment

While the base docker container already contains binaries of Kilosort2, here you will need to install it to a given directory KILOSORT2_PATH, such that it is accessible in spikeinterface. See instructions from spikeinterface and from Kilosort2.

python -m venv venv_nicespike
source venv_nicespike/bin/activate
pip install --extra-index-url https://codeberg.org/api/packages/spiky/pypi/simple/ nicespike
KILOSORT2_PATH=$KILOSORT2_PATH nicespike

Run nicespike GUI

Open http://localhost:8080 and enjoy running nicespike.

Use nicespike as python package

The functionality of nicespike can be also used programatically by usage as a python module, e.g. with

from nicespike import settings, set_value, SpikeSorting
set_value(settings['General']['Number of parallel processes'], 8)
set_value(settings['Spikes']['Minimum firing rate'], 0.05)
set_value(settings['Network bursts']['Minimum number of units'], 5)
set_value(settings['Synchrony']['STTC: time window'], 0.5)
sorting = SpikeSorting(path='brw/div_21_21_chip_A.brw',
 output_dir='output/div_21_21_chip_A',
 settings=settings,
 verbose=True)
sorting.read_and_filter()
sorting.run_kilosort2()
sorting.extract_waveforms()
sorting.export_npz()
sorting.spikenburst_analysis()
sorting.spikeinterface_plot()
sorting.spikenburst_plot()
sorting.spikenburst_export()

Copyright

Copyright 2024 Robert Wolff mahlzahn@posteo.de

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see https://www.gnu.org/licenses/.

How to cite this package?

The nicespike package was introduced in

• Wolff et al. ‘SpikeNburst’ and ‘Nicespike’: Advanced Tools for Enhancing and Accelerating In Vitro High-Density Electrophysiology Analysis. BioRxiv preprint 2025年02月19日.638867 (2025).

The tool uses spikeinterface, python-neo and KiloSort that should be referenced as following:

• Buccino et al. SpikeInterface, a unified framework for spike sorting. eLife 9:e61834 (2020),
• Garcia et al. Neo: an object model for handling electrophysiology data in multiple formats. Front Neuroinform. 8 (2014) and
• Pachitariu et al. Fast and accurate spike sorting of high-channel count probes with KiloSort. In: Advances in Neural Information Processing Systems. Vol 29. Curran Associates, Inc. (2016).

Further, it uses the spikeNburst package and thus all references that are listed here must be referenced:

• References for spikeNburst algorithms

Developer: build and publish the package

For uploading packages on Codeberg (see Forgejo documentation), create ~/.pypirc with following content:

[distutils]
 index-servers =
 codeberg
 pypi
 testpypi
[codeberg]
 repository = https://codeberg.org/api/packages/<user>/pypi
 username = <user>
 password = <token>

After adjusting the version number in pyproject.toml, the package can be build and uploaded with

python -m build
twine upload --skip-existing --repository codeberg dist/*