Open-source neuroscience software packages
This table summarizes a diverse selection of computational software packages and toolboxes widely utilized for the analysis of neural and behavioral data. It highlights open-source resources across Python, R, and MATLAB, covering critical analytical domains such as signal processing, spike inference from calcium imaging, graph theoretical network analysis, and neuroanatomical modeling. By providing direct access to the source code and primary literature, this list serves as a guide for researchers seeking validated, high-performance tools to enhance the reproducibility and efficiency of their neuroscience workflows. Notice something missing? Please contribute.
| # | Package | Description | Citation | Topic | Language |
|---|---|---|---|---|---|
| 1 | Cascade | Cascade translates calcium imaging ΔF/F traces into spiking probabilities or discrete spikes using deep learning networks. | Rupprecht et al., 2021 | Preprocessing (spike inference) | Python |
| 2 | BSD | A software package for inferring spike trains from fluorescence recordings. BSD features a fully unsupervised estimation of metaparameters and a blind sparse deconvolution algorithm. | Tubiana et al., 2020 | Preprocessing (spike inference) | MATLAB |
| 3 | LZeroSpikeInference | A collection of algorithms to determine the exact time at which a neuron spikes on the basis of its fluorescence trace using an L0 penalty. | Jewell & Witten, 2017 | Preprocessing (spike inference) | R |
| 4 | Pynapple | A lightweight package designed to process a broad range of time-resolved data in systems neuroscience. It provides a set of data objects and methods aimed at simplifying the analysis of neurophysiological and behavioral data. | Viejo et al., 2023 | Neural signal processing | Python |
| 5 | GhostiPy | An open source software toolbox with implementations of various signal processing and spectral analysis tools. It prioritizes performance and efficiency through the use of parallelized algorithms. | Chu & Kemere, 2021 | Neural signal processing | Python |
| 6 | Neurodsp | A software package specifically designed for analyzing neural time series data and their time-varying properties. | Cole et al., 2019 | Neural signal processing | Python |
| 7 | Chronux | An open source software package for the analysis of both point process and continuous data that includes preprocessing, exploratory analysis, and confirmatory analysis. | Mitra & Bokil, 2008 | Neural signal processing | MATLAB |
| 8 | NetworkToolbox | A toolbox implementing network analysis and graph theory measures commonly used in neuroscience, cognitive science, and psychology. | Alexander, 2018 | Graph theory and network analysis | R |
| 9 | BCTPY | A software toolbox implementing many graph theoretical measures to analyze brain activity. Based closely on the Brain Connectivity Toolbox for Matlab. | LaPlante, 2013 | Graph theory and network analysis | Python |
| 10 | Brain Connectivity Toolbox | A popular toolbox used for complex brain network analysis that implements a number of graph theoretical measures. | Rubinov & Sporns, 2010 | Graph theory and network analysis | MATLAB |
| 11 | Syntropy | An open source library for multivariate information theoretic analysis of discrete and continuous data. | Varley, 2025 | Information theory | Python |
| 12 | Spyglass | An open source data analysis framework that facilitates the storage, visualization, analysis, and sharing of neuroscience data to promote more reproducible research. | Lee et al., 2024 | Analysis pipeline management | Python |
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Last updated: 26 March, 2026