Package: neurodsp
Tools to analyze and simulate neural time series, using digital signal processing.Overviewneurodspis a collection of approaches for applying digital signal processing, and
related algorithms, to neural time series. It also includes simulation tools for generating
plausible simulations of neural time series.Available modules inNeuroDSPinclude:filt: Filter data with bandpass, highpass, lowpass, or notch filterstimefrequency: Estimate instantaneous measures of oscillatory activityspectral: Compute freqeuncy domain features such as power spectraburst: Detect bursting oscillations in neural signalsrhythm: Find and analyze rhythmic and recurrent patterns in time seriesaperiodic: Analyze aperiodic features of neural time seriessim: Simulate time series, including periodic and aperiodic signal componentsplts: Plot neural time series and derived measuresutils: Additional utilities for managing time series dataDocumentationDocumentation for theNeuroDSPmodule is availablehere.The documentation includes:Tutorials: which describe and work through each module in NeuroDSPExamples: demonstrating example applications and workflowsAPI List: which lists and describes all the code and functionality available in the moduleGlossary: which defines all the key terms used in the moduleIf you have a question about using NeuroDSP that doesn’t seem to be covered by the documentation, feel free to
open anissueand ask!DependenciesNeuroDSPis written in Python, and requires Python >= 3.6 to run.It has the following dependencies:numpyscipymatplotlibOptional dependencies:pytestis needed if you want to run the test suite locallyWe recommend using theAnacondadistribution to manage these requirements.InstallThe current major release of NeuroDSP is the 2.X.X series.See thechangelogfor notes on major version releases.Stable Release VersionTo install the latest stable release, you can use pip:$pipinstallneurodspNeuroDSP can also be installed with conda, from the conda-forge channel:$condainstall-cconda-forgeneurodspDevelopment VersionTo get the current development version, first clone this repository:$gitclonehttps://github.com/neurodsp-tools/neurodspTo install this cloned copy, move into the directory you just cloned, and run:$pipinstall.Editable VersionTo install an editable version, download the development version as above, and run:$pipinstall-e.ContributeThis project welcomes and encourages contributions from the community!To file bug reports and/or ask questions about this project, please use theGithub issue tracker.To see and get involved in discussions about the module, check out:theissues boardfor topics relating to code updates, bugs, and fixesthedevelopment pagefor discussion of potential major updates to the moduleWhen interacting with this project, please use thecontribution guidelinesand follow thecode of conduct.ReferenceIf you use this code in your project, please cite:Cole, S., Donoghue, T., Gao, R., & Voytek, B. (2019). NeuroDSP: A package for
neural digital signal processing. Journal of Open Source Software, 4(36), 1272.
DOI: 10.21105/joss.01272Direct Link:https://doi.org/10.21105/joss.01272Bibtex:@article{cole_neurodsp:_2019,
    title = {NeuroDSP: A package for neural digital signal processing},
    author = {Cole, Scott and Donoghue, Thomas and Gao, Richard and Voytek, Bradley},
    journal = {Journal of Open Source Software},
    year = {2019},
    volume = {4},
    number = {36},
    issn = {2475-9066},
    url = {https://joss.theoj.org/papers/10.21105/joss.01272},
    doi = {10.21105/joss.01272},
}FundingSupported by NIH award R01 GM134363 from theNIGMS.