NeuroKit2: A Python toolbox for neurophysiological signal processing

Behavior Research Methods (2021)Cite this article

Abstract

NeuroKit2 is an open-source, community-driven, and user-centered Python package for neurophysiological signal processing. It provides a comprehensive suite of processing routines for a variety of bodily signals (e.g., ECG, PPG, EDA, EMG, RSP). These processing routines include high-level functions that enable data processing in a few lines of code using validated pipelines, which we illustrate in two examples covering the most typical scenarios, such as an event-related paradigm and an interval-related analysis. The package also includes tools for specific processing steps such as rate extraction and filtering methods, offering a trade-off between high-level convenience and fine-tuned control. Its goal is to improve transparency and reproducibility in neurophysiological research, as well as foster exploration and innovation. Its design philosophy is centred on user-experience and accessibility to both novice and advanced users.

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Acknowledgments

We would like to thank Prof. C. F. Xavier for inspiration, all the current and future contributors (https://neurokit2.readthedocs.io/en/latest/authors.html), and the users for their support. Additionally, François Lespinasse would like to thank the Courtois Foundation for its support through the Courtois-NeuroMod project (https://cneuromod.ca)

Author information

Affiliations

  1. School of Social Sciences, Nanyang Technological University, HSS 04-19, 48 Nanyang Avenue, Singapore, Singapore

    Dominique Makowski, Tam Pham, Zen J. Lau & S. H. Annabel Chen

  2. Behavioural Science Institute, Radboud University, Nijmegen, Netherlands

    Jan C. Brammer

  3. Département de psychologie, Université de Montréal, Montréal, Canada

    François Lespinasse

  4. Centre de Recherche de l’Institut Universitaire Geriatrique de Montréal, Montréal, Canada

    François Lespinasse

  5. Eureka Robotics, Singapore, Singapore

    Hung Pham

  6. Life Science Informatics, THM University of Applied Sciences, Giessen, Germany

    Christopher Schölzel

  7. Centre for Research and Development in Learning, Nanyang Technological University, Singapore, Singapore

    S. H. Annabel Chen

  8. Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore

    S. H. Annabel Chen

Authors
  1. Dominique Makowski
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  2. Tam Pham
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  3. Zen J. Lau
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  4. Jan C. Brammer
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  5. François Lespinasse
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  6. Hung Pham
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  7. Christopher Schölzel
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  8. S. H. Annabel Chen
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Correspondence to Dominique Makowski.

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Cite this article

Makowski, D., Pham, T., Lau, Z.J. et al. NeuroKit2: A Python toolbox for neurophysiological signal processing. Behav Res (2021). https://doi.org/10.3758/s13428-020-01516-y

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Keywords

  • Neurophysiology
  • Biosignals
  • Python
  • ECG
  • EDA
  • EMG