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.
| Package | Description | Citation | Language | |
|---|---|---|---|---|
| 1 | Pynapple | A lightweight python package designed to process a broad range of time-resolved data in systems neuroscience, which facilitates analysis through data objects and methods that have the potential to simplify data analysis for neural and behavioral data types. | (Viejo et al. 2023) | Python |
| 2 | Spyglass | An open-source, python based data analysis framework that facilitates the storage, analysis, visualization, and sharing of neuroscience data towards more reproducible research | (Lee and Denovellis et al. 2024) | Python |
| 3 | Neurodsp | A python-based software package specifically designed to be used for analyzing neural time series data and their time-varying properties | (Cole et al., 2019) | Python |
| 4 | GhostiPy | A python-based open source software toolbox with implementations of various signal processing and spectral analyses, and prioritizes performance and efficiency through the use of parallelized algorithms | (Chu & Kemere. 2021) | Python |
| 5 | bctpy | Implements many graph theoretical measures to analyze brain activity | (LaPlante, 2013) | Python |
| 6 | natverse | An R-based suite of toolboxes to perform popular analysis of neuroanatomical data | (Bates et al., 2020) | R |
| 7 | NetworkToolbox | Implements network analysis and graph theory measures used in neuroscience, cognitive science, and psychology. | (Alexander 2018) | R |
| 8 | 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) | R |
| 9 | Brain Connectivity Toolbox | A popular toolbox used for complex brain-network analysis. | (Rubinov M, Sporns O 2010) | MATLAB |
| 10 | Syntropy | A python library for multivariate information theoretic analysis of discrete and continuous data | (Varley 2025) | Python |
| 11 | Cascade | Cascade translates calcium imaging ΔF/F traces into spiking probabilities or discrete spikes using deep networks | (Rupprecht et al., 2021) | Python |
| 12 | BSD | Blind Sparse Deconvolution for inferring spike trains from fluorescence recordings. | (Tubiana et al., 2020) | MATLAB |
| 13 | Chronux | Open-source software package for the analysis of neural data for both point process and continuous data, ranging from preprocessing, exploratory and confirmatory analysis | (Mitra & Bokil, 2008) | MATLAB |
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