École de Neuropsychologie
École de Neuropsychologie is best classified as an academic/open-source project organization rather than a conventional company or an individual. Its principal project, NeuroKit2, is a user-friendly Python toolbox intended to make advanced neurophysiological and biosignal processing accessible to researchers and clinicians with limited programming or signal-processing experience.
At a Glance
- Researchers and clinicians
- Universities and academic laboratories
- Psychology, neuroscience and biomedical engineering groups
- Students and educators learning Python or biosignal analysis
- +1 more
AI Tools by École de Neuropsychologie
(1)
NeuroKit2
Python Biosignal Processing Toolbox
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Latest News
NeuroKit2 0.2.13 released; Langevin 2021 PPG cleaning method added and PyPI package uploaded
NeuroKit2 0.2.12 released with ECG/PPG signal-quality methods, URL-capable read_xdf and a new UNSW QRS detector
NeuroKit2 0.2.11 released with a Peak-Prominence ECG delineator and maintenance updates
NeuroKit2 0.2.10 released with documentation codebook generation and MSPTDfast PPG peak detection
Products & Services
Open-source Python toolbox for neurophysiological signal processing. It provides simulation, cleaning/preprocessing, peak and event detection, feature extraction, visualization, statistical analysis, HRV, ECG delineation, complexity/entropy, signal decomposition and power-spectrum workflows for physiological signals.
Free online documentation with installation guidance, function reference, codebook, tutorials, worked examples, datasets, study resources and contribution guidance.
Market Position
NeuroKit2 positions itself as a broad, user-centered and beginner-friendly open-source alternative to assembling separate signal-processing tools. Its differentiator is a single high-level Python API spanning many physiological modalities and analysis stages, whereas adjacent alternatives such as BioSPPy, MNE-Python and SciPy-based workflows are generally narrower or require more low-level composition. Its community-maintained MIT-licensed model also contrasts with proprietary biosignal-analysis platforms.
Leadership
Founders
Dominique Makowski
Psychology/neuroscience researcher and the project's lead maintainer; the official NeuroKit2 documentation lists him at Nanyang Technological University, Singapore. The broader web describes the original NeuroKit as a PhD side-project, and the repository license credits Makowski as copyright holder.
Executive Team
Dominique Makowski
Lead maintainer / project lead
Researcher associated with Nanyang Technological University, Singapore; original NeuroKit creator and the sole maintainer shown in current PyPI metadata.
Danielle Benesch
Project maintainer
Listed by the official documentation as a current maintainer affiliated with École de technologie supérieure, Canada.
Founding Story
The original NeuroKit began as Dominique Makowski's PhD side-project in 2017. The project was started to turn neurophysiological signal-processing methods into approachable, reusable open-source tooling; NeuroKit2 subsequently evolved into a community-driven Python package with contributions from researchers and developers worldwide.
Business Model
Revenue Model
Free, open-source software distributed under the MIT License through PyPI and conda-forge. The project solicits voluntary contributions through GitHub Sponsors and community contributions rather than charging for software access.
Pricing Tiers
MIT-licensed NeuroKit2 package and online documentation; installable with pip or conda.
Target Markets
- Researchers and clinicians
- Universities and academic laboratories
- Psychology, neuroscience and biomedical engineering groups
- Students and educators learning Python or biosignal analysis
- Developers building physiological-data and wearable-sensor workflows
- Academic neurophysiology and psychology research
- Clinical and biomedical research involving physiological signals
- Processing wearable, laboratory and biosensor data
- Teaching Python and reproducible physiological-signal analysis
- Rapid prototyping and validation of biosignal-processing algorithms
- Event-related, interval-related and HRV studies
- Nanyang Technological University
- Université de Paris
- Duke University
- University of Auckland