Welcome to NeuralActivityCubic

Computation of local and signal-close-to-noise calcium activity.

NeuralActivityCubic (NA³) is an open-source calcium image analysis tool published in 2018 by J. Prada and colleagues¹, who describe it as following in their Author Summary:

Calcium imaging has become a standard tool to investigate local, spontaneous, or cell-autonomous calcium signals in neurons. Some of these calcium signals are fast and ‘small’, thus making it difficult to identify real signaling events due to an unavoidable signal noise. Therefore, it is difficult to assess the spatiotemporal activity footprint of individual neurons or a neuronal network. We developed this open source tool to automatically extract, count, and localize calcium signals from the whole x,y-t image series. As demonstrated here, the tool is useful for an unbiased comparison of activity states of neurons, helps to assess local calcium transients, and even visualizes local homeostatic calcium activity. The tool is powerful enough to visualize signal-close-to-noise calcium activity.

Since its publication in 2018, updates to several software packages on which the original implementation of NA3 depends have rendered this version of NA³ virtually un-installable and, thus, effectively inaccessible for its target user audience - the Neuroscientific Community. Given the continued interest in NA³, however, this was not acceptable. Thus, we formed a collaboration between the original developers of NA³ and research software engineering experts from the not-for-profit organization Indoc Research Europe to revamp NA³, with the goal of making it easily accessible to the Neuroscientific Community once again. While on it, we also enhanced NA³´s performance, it´s scope of features, and it´s maintainability to ensure NA³ remains accessible moving forward. Today, we´re happy to present to you this revamped version of NA³ - we hope you´ll like it!

Note: We´re still putting a few finishing touches on this new implementation of NA³, so please be aware that this version remains under active development and should not yet be considered as a stable release. We´re currently also working on a paper describing our work in more details, so make sure you stay tuned and regularly check these docs for updates!

Usage

Installation

If you´re comfortable working with virtual Python environments and installing packages via command line interfaces, please follow one of the subsequent options to install NA³. If you´d prefer a full step-by-step guide instead, we also got you covered: please find our detailed installation guide here.

Install latest from GitHub:

$ pip install git+https://github.com/Indoc-Research/neuralactivitycubic.git

or from pypi

$ pip install neuralactivitycubic

Documentation

Documentation for NA³ can be found here.

How to use - quick start:

After installing neuralactivitycubic, open a Jupyter Notebook and execute the following code to launch the GUI of NA³:

import neuralactivitycubic as na3

na3.open_gui()

Developer Guide

If you are new to using nbdev here are some useful pointers to get you started.

Install NeuralActivityCubic in Development mode

# make sure NeuralActivityCubic package is installed in development mode
$ pip install -e .

# make changes under nbs/ directory
# ...

# compile to have changes apply to NeuralActivityCubic
$ nbdev_prepare

Footnotes

Prada J, Sasi M, Martin C, Jablonka S, Dandekar T, Blum R (2018) An open source tool for automatic spatiotemporal assessment of calcium transients and local ‘signal-close-to-noise’ activity in calcium imaging data. PLoS computational biology 14(3): e1006054. https://doi.org/10.1371/journal.pcbi.1006054↩︎