A tool for digital signal processing for neural time series
NeuroDSP is package of tools to analyze and simulate neural time series, using digital signal processing. Available modules in NeuroDSP include: * filt : Filter data with bandpass, highpass, lowpass, or notch filters * burst : Detect bursting oscillations in neural signals * rhythm : Find and analyze rhythmic and recurrent patterns in time series * spectral : Compute spectral domain features such as power spectra * timefrequency : Estimate instantaneous measures of oscillatory activity * sim : Simulate time series, including periodic and aperiodic signal components * plts : Plotting functions If 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. https://doi.org/10.21105/joss.01272
You can contact the maintainers of this package via email at
python-neurodsp dash maintainers at fedoraproject dot org.